Aboozar Vafaei; Kamran Dolatyarian
Abstract
Extended AbstractIntroduction Due to its particular natural, economic and social situation, Kashan as a second-rate city confronts a variety of problems such as horizontal and scattered expansion, unbalanced development of the city in different directions, the spread of marginalization and unauthorized ...
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Extended AbstractIntroduction Due to its particular natural, economic and social situation, Kashan as a second-rate city confronts a variety of problems such as horizontal and scattered expansion, unbalanced development of the city in different directions, the spread of marginalization and unauthorized constructions. These problems have become the basis for major changes in land use and land use incompatibility. Land use evaluation of Kashan city shows that this city has been encountering uneven growth in recent years and many of the surrounding areas that used to be agricultural lands, have gone to urban infrastructure and structures, especially the residential and industrial ones. Since one of the purposes of urban land use plan is the appropriate location of land uses in conjunction with the separation of incompatible uses from each other, accordingly, the current research aims to present applicable solutions for the optimal location detection and distribution of uses throughout the city and to separate incompatible uses from each other in order to achieve the major goal of urban planning, i.e., ensuring people's welfare by creating a better, healthier, more effective and pleasant environment by applying the spatial analysis tools of the geographic information system, while answering the following questions;What is the per-capita status of existing uses in Kashan with standard per capita in urban plans?What is the status of existing uses in Kashan regarding the compatibility index? Research MethodRegarding purpose, the type of research is applied and in terms of its method it is analytical-comparative; explicitly, the literature and sources have been initially examined and the theoretical framework of the subject has been compiled. Then the base map of urban land uses was prepared and reorganized in GIS environment. Subsequently, through surveys of the amounts of surfaces, the per capita for all types of uses was determined and annexed to the information of the base map in the form of separate layers in order to provide the basis for its use in the GIS environment. Afterwards, the evaluation of urban uses was proceeded regarding per capita standards and compatibility index by applying quantitative and qualitative method. Accordingly, the amount of land required by each use in the current situation was initially calculated and determined by specifying the ratio of shortages through the per capita standard and eventually, the location of each use in relation to neighboring users was analyzed in terms of compatibility index via GIS software using the overlap model (IO) and spatial analysis. The Geographical Area of the ResearchKashan city is the geographical area of the research that is currently the second most populous and industrial city after Isfahan city in the province. Results and DiscussionSince examining the compatibility of different uses of the city is the most significant element in evaluating urban land use, therefore this research has proceeded to explain the degree of compatibility and non-disruption of one use to carry out the activities of other uses using the compatibility index. Accordingly, the degree of compatibility of city uses in relation to neighboring uses was primarily drawn using the convenient table of mutual compatibility matrix, then the quality of city uses was investigated through field studies in terms of compatibility according to the amenable fields in explaining compatibility such as land size, slope, accessibility, urban facilities and equipment, air quality, sound, light and smell. ConclusionIn this research, the uses were examined and evaluated at both quantitative and qualitative levels. In the quantitative section, the current situation of the levels and per capita uses throughout the city was discussed with the standard per capita in urban plans. Consequently, statistical calculations showed that except for tourism and religious uses, other uses are encountering a deficiency of level. In the qualitative part, the degree of compatibility of land uses was investigated using the compatibility index through acquiescent components in the explanation of compatibility such as land size, slope, accessibility, urban facilities and equipment, air quality, sound, light and smell, through field studies in the form of mutual compatibility matrix. Finally, the location of each user in relation to neighboring users was analyzed in terms of compatibility index via GIS software applying the overlap model (IO) and spatial analysis. The results of the compatibility percentage of uses with neighboring use in Kashan show that residential use of more than 40 percent, educational use with more than 37 percent, administrative use with 36 percent, medical use with 27 percent and sports use with 19 percent in stand in relatively incompatible to completely incompatible conditions with their neighboring uses, and on the other hand, tourism use with more than 90%, religious and cultural use with more than 85%, and commercial use with more than 80% are in entirely compatible and relatively compatible conditions with their neighboring uses and take the least incompatibility with other uses.
Seyyed Ghasem Rostami; Aliakbar Yahyaabadi
Abstract
Introduction In recent years, studies in seismology have mainly focused on temporal and spatial analysis of earthquakes. This is important for crisis management due to a variety of reasons, including the necessity to estimate the magnitude and the occurrence time of the main aftershock in a given periodafter ...
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Introduction In recent years, studies in seismology have mainly focused on temporal and spatial analysis of earthquakes. This is important for crisis management due to a variety of reasons, including the necessity to estimate the magnitude and the occurrence time of the main aftershock in a given periodafter the mainshock.The present study seeks to identify the relationship between the magnitude and the occurrence time of the main aftershock in the first few hours after the mainshockusing the aftershock classification patterns. Various workshave been performed to model aftershocks of whichthe last centurystudies have yielded good results. However, providing a comprehensive description of how energy is released from seismic sources during an earthquakein different regionsis not easy. As a result, modeling of aftershocks is very complex and a precise model has not yet been provided for estimatingfeatures of the main aftershocks. Material and Methods During the preliminary investigation, magnitude of the mainshock and the number of aftershocks in the initial 12 hours were identified as two important parameters affecting the magnitude and the occurrence time of the main aftershock. However, this simple model lacks sufficient accuracy (accuracy of 0.5 in magnitude estimation and 5.8 hours in the estimation of the main aftershock occurrence time). Therefore, a polynomial function with higher number ofparameterswas used in the present study to reach a more accurate modeling. A linear polynomial model with 15 different parameters was introduced. These parameters includemagnitude of the mainshock, number of aftershocks during the initial time period, and in half and quarter of the period, and the number of aftershocks and mean temporal interval between aftershocks occurringin classes of 2.5 to 3.5, 3.5 to 4.5, 4.5 to 5.5 and greater than 5.5 Richter. The initial time period refers to the minimum number of hours needed after the mainshockto collect information about the aftershocks. Coefficients of occurrence time and magnitude of the main aftershock were calculated in the two proposed modelsusing 32 earthquake events and the least square method. These earthquakeshad occurred with a magnitude of greater than 5.6 from 2006 to 2020.In order to select the best model using the least mean square error (MSE), several models have been considered with a change in their initial time period (using for classification of the aftershocks) and secondary time period(the time duration at which the features of the main aftershock are estimated). Results Based on the mean square error, three models were introduced to estimate features of the main aftershock in short, mid and long-term. These models can be used to estimate features of the main aftershocks occurring 2, 8 and 20 days after the main shock, respectively. The short-term prediction model use aftershocks occurring during the first hour after the main shock to predict the magnitude of the main aftershock with a precision of 0.21 (MN) and its occurrence time with a precision of 3.1 hours. Mid-term prediction model also useaftershocks occurring during the first 3hoursafter the main shock to predict the magnitude of the main aftershock with a precision of 0.23 (MN) and the occurrence time with a precision of 19.3 hours. Finally, the long-term prediction model use aftershocks occurring during the first9hoursafter the main shock to predict the magnitude of the main aftershock with a precision of 0.22 (MN) and the occurrence time with a precision of 38.5 hours. Conclusion To evaluate errorsof the proposed models, information collected from 9 recent earthquakes in Iran and Turkey was used. Magnitude and occurrence time of the main aftershock ineach selected earthquake were calculated using short, mid and long term prediction models. Results demonstrate that these models can predict the magnitude of the main aftershock with an average error of 0.18 (MN). They also can predict the occurrence time of the main aftershock with an average error of 18.1 hours. It is worth noting that the proposed models havepredicted themagnitudeof these recentnine earthquakes with a mean error less than their accuracy estimated using the 32 earthquake events.
Zahra Rezaee; Mohammad Hasan Vahidnia
Abstract
Extended abstract
Introduction
Population growth, urbanization and land use change in recent decades have made floods one of the most devastating natural disasters in the world. Therefore, understanding this phenomenon, its effects and methods used to deal with it is considered to be among the most ...
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Extended abstract
Introduction
Population growth, urbanization and land use change in recent decades have made floods one of the most devastating natural disasters in the world. Therefore, understanding this phenomenon, its effects and methods used to deal with it is considered to be among the most important issues crisis management planners and policymakers in urban and rural areas should pay attention to. Iran faces many natural disasters among which flood is one of the most serious ones. Monitoring and controlling accidents, assessing damages and providing relief are among the main concerns of government and crisis management experts. Continuous monitoring before the occurrence, and accurate assessment during and after the event can decrease damages to human and natural resources. Preventing flood related hazards, organizing and managing flood water in channels and ultimately improving channels require identifying and determining flood zones.
Materials & Methods
Agent-based modeling (ABM) provides simulation and abstract systems used to identify patterns of land forms in the study area. As a new approach, agent-based modeling is used to develop simulation tools for complex phenomena in various fields such as natural disasters, biological studies and relief provision in flood occurrences. In fact, agent-based modeling (ABM) has been increasingly used to confront the risk of flood and its challenges in recent years. The present study applies fuzzy inference approach (using parameters affecting the occurrence of flood and remote sensing data) and agent-based modeling to prepare a flood risk map and provide a deterrent solution for flood risk management and decision making before the occurrence. In the fuzzy inference system, various maps are prepared showing parameters affecting the occurrence of floods such as slope, soil type and rivers. Then, Fuzzy Overlay model is used to define the flood risk zones and overlay the fuzzy parameters. The present study applies fuzzy gamma operator with a coefficient of 0.8 in the final fuzzy overlay calculation.
Results & Discussion
Comparing the results obtained from overlaid maps reveals that most flood plains are located in areas covered with Affisols (clay-rich soil) and low-lying arable lands and orchards. In agent-based modeling, GIS plugin of NetLogo was used to investigate the flood phenomenon based on the digital elevation model of the area. In this model, raindrop cycle was simulated in the DEM raster layer of Gilan. DEM layer can be used to calculate the slope (vertical angle) and slope direction (horizontal angle) of the ground surface. Simulated images shows the movement and accumulation of agents along the rivers and their surroundings and in low altitude areas. Analysis confirms the risk of floods in rivers and low-lying areas. Finally, georeferenced images of points in risk of possible flood (agents in the slopes of the study area), land use map and soil cover map can be overlaid to evaluate the obtained results. Results indicate that the highest number of agents (white markings on the map) are located in agricultural land use covered with Affisols while a relatively moderate number of agents are located in agricultural lands covered with Inceptisols. As previously mentioned, these agents simulate the amount of runoff accumulation due to atmospheric precipitation. Results indicate that precipitation models simulated using artificial intelligence lead to almost the same result Fuzzy analysis method shows (regarding the prediction of flood occurrence).
Conclusion
Finally, these two approaches are compared and their functions are examined. It should be noted that multi-criteria methods such as fuzzy inference approach has a higher level of complexity and accuracy, while methods based on artificial intelligence and agent-based modeling are faster. On the other hand, agent-based modelling method use relatively ready programs and thus has a lower level of complexity. The level of accuracy in this method is also lower than the fuzzy logic method.
Arash Azimi Fard; Ali Hosseininaveh Ahmad Abadian
Abstract
Extended Abstract
Introduction
Due to the complexity of frame processing used for positioning and mapping in visual odometry (VO) and visual simultaneous localization and mapping (VSLAM) algorithms, key-frame selection methods have been introduced to improve the performance and decrease the number ...
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Extended Abstract
Introduction
Due to the complexity of frame processing used for positioning and mapping in visual odometry (VO) and visual simultaneous localization and mapping (VSLAM) algorithms, key-frame selection methods have been introduced to improve the performance and decrease the number of frames required for processing while maintaining accuracy and robustness of the algorithms. Selected key-frames in these methods make a very good representation of all available frames. The current key-frame selection methods rely on heuristic thresholds in their selection procedure. Researchers have used several datasets to find optimum values for these thresholds through trial and error. In fact, proposed methods may not work as expected with a new dataset due to changes occurring in the sensor, environment and the platform.
Materials & Method
The present study has proposed an improved geometric and photogrammetric key-frame selection method built upon ORB-SLAM3, as the state of the art visual SLAM algorithm. The proposed Photogrammetric Key-frame Selection (PKS) algorithm has replaced inflexible heuristic thresholds with photogrammetric principles and thus guaranteed the robustness of the algorithm and the quality of the point cloud obtained from the key-frames. First, an adaptive threshold decides the allowable number of points whose line of sight zone has changed on a four-zone cone built upon each point. Increased number of points whose line of sight zone has changed means increased changes and displacements of the frame and thus, increased need for a new key-frame. Then, a 3*3 grid was formed in each frame and the number of points with a more than 30-degree change in line of sight angle (effective points) in each cell were counted. Later, the Equilibrium of Center Of Gravity (ECOG) criterion decides whether the distribution of points is appropriate using the center of gravity of the points inside the frame. Appropriate distribution of effective points within the frame shows a high geometric strength and thus will improve the strength of key-frames network. IMU sensor is not dependent on the position of the frames and the camera sensor. Thus, it independently obtains the key-frame in case significant changes occur in acceleration. The threshold value of acceleration has been experimentally considered equal to 1 meter per square second, which entirely depends on the type of robot. For ground robots with slower moving speeds, this threshold must be reset.
Results & Discussion
The present study has employed data collected by the European Robotics Challenge (EuRoC) flying robot containing the information collected by the synchronized camera and IMU information, as well as the ground truth data such as the robot trajectory and point cloud formed by the laser scanner. To evaluate the proposed method, extensive experiments have been implemented on the EuRoC dataset in mono-inertial and stereo-inertial modes. Then, trajectory of each algorithm was compared with the reference trajectory and point clouds formed by the key-frames were also compared. Apart from these qualitative evaluations, absolute trajectory error (ATE) obtained from running the PKS and ORB-SLAM3 algorithm 10 times were also compared quantitatively and finally, the error histogram was used to evaluate the point clouds. The processing time of each algorithm was also evaluated for each EuRoC dataset sequence. Results indicated that the proposed algorithm has improved ORB-SLAM3 accuracy in stereo-inertial by 18.1% and in the mono-inertial mode by 20.4% producing a more complete and accurate point cloud and thus, extracting more details from the environment. Furthermore, despite higher density of the point cloud, the error histogram has not changed significantly and fewer errors were observed in the ORB-SLAM3 algorithm.
Conclusion
Findings indicated that the PKS method has succeeded in extracting key-frames using photogrammetric and geometric principles. Apart from improving the positioning accuracy of the robot, the method has produced a much more complete and dense point cloud as compared to the ORB-SLAM3 algorithm. Also, dependency of the PKS method on the environment conditions and the type of system used (stereo camera or mono camera) was greatly reduced. Future studies can expand our key-frame selection method to include fisheye cameras or visual-only systems. More geometric conditions (near and far point condition and the vertex angle in the triangle formed by the points in the current frame, the camera and the corresponding points in the last key-frame) can also be added to the key-frame selection method.
Mohammad Karimi Firozjaei; Amir Sedighi; Najmeh Neisany Samany
Abstract
Introduction Remote sensing data provide valuable information for the agricultural section and natural resources managers. Nowadays, performance management and estimation via using various methods such as classification and mapping have gained great significance. An example of such data is the mapping ...
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Introduction Remote sensing data provide valuable information for the agricultural section and natural resources managers. Nowadays, performance management and estimation via using various methods such as classification and mapping have gained great significance. An example of such data is the mapping of crops cultivation and orchards at national and regional levels, which is one of the key tools in sustainable agricultural planning and management. These studies appear necessary especially in the field of strategic commodities such as rice and citrus which are among the most important food items for the Iranian people. The spatial information on agricultural lands in the field of agricultural planning and management can help the prevention of the spread of pests, management of the environmental stresses, crop performance estimation and vulnerability assessment in crop production. Field surveys and observations for crops mapping in the growing season in different years are very time-consuming, costly, and only suitable for small-scale studies. In contrast, over the past decades, remote sensing has been recognized as a suitable method for crops mapping for large areas in the shortest time and at low cost. Due to the climatic conditions of the areas in North of Iran, green spaces including vegetation and orchards, and rice fields are located near each other. At the time of the maximum growth of rice products, the spectral characteristics of these land covers are very similar. Therefore, the separation of these two land covers using satellite image classification process faces serious challenges. The aim of this study is to investigate the efficiency of the satellite images and the optimization algorithms for separating green spaces and rice fields from each other at the time of maximum growth. The present study differs from others in this field from two aspects; first, the study compares the capabilities of multispectral and hyperspectral satellite images with each other; additionally, it aims at comparing and evaluating the efficiency of the Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA) so as to determine the optimal features for increasing the separation accuracy of green spaces and rice fields. Materials and methodology This research was carried out based on the two objectives of studying the capabilities of the Hyperion and Landsat images and comparing the efficiency of the PSO and GSA to determine optimal features for the separation of green spaces and rice fields. For this purpose, the two Landsat and Hyperion satellite images as well as ground data sets of the case study in North of Iran were employed. In the first step, preprocessing of the Hyperion and Landsat images was performed. In the second step, various features were extracted from the Hyperion and Landsat images using different spectral indices and transformations. In the third step, the Support Vector Machine (SVM) classifier was applied with two strategies, i.e. the usage of spectral bands and the usage of spectral bands as well as indices as the features in the classification process to extract green spaces and rice fields. In the fourth step, PSO and GSA were employed to extract optimal features from the Hyperion image to distinguish between green spaces and rice fields; then, classification was done with the extracted optimal features; and finally, the efficiency of PSO and GSA were compared to determine the optimal features for the separation of green spaces and rice fields using ground data sets. Results and discussion The results indicate that the use of Landsat image is not effective for the separation of rice fields and green spaces. In other words, due to the high spectral similarity of these land covers, a large percentage of pixels related to the two classes are mistakenly classified in another class. However, the accuracy of the producer and user relating to each class has increased by an average of 10 percent with the addition of spectral indices to the classification process. Using Hyperion image is more effective than Landsat image for the separation of rice fields and green spaces. Moreover, the accuracy for the separation of rice fields and green spaces has increased with the simultaneous consideration of the bands and spectral indices in the classification process. It should be noted that one of the key factors in the efficiency evaluation process of the classification methods is the processing time. The results of using optimization algorithms for determining the optimal features indicate that out of the 150 spectral features (including 140 Hyperion image bands and 10 spectral indices and transformations), using PSO and GSA, only 25 and 31 optimal features were selected for the separation of green spaces and rice fields, respectively.The use of optimal features in the classification increases the accuracy for the separation of green spaces and rice fields more, compared to the use of all features in the classification. Additionally, GSA is superior to PSO when used for extracting optimal features for the separation of green spaces and rice fields. Conclusion The results of this research indicate that the separation accuracy of green spaces and rice fields using Landsat image,is less than that of Hyperion image. With the addition of spectral indices to the classification process, the separation accuracy in both Landsat and Hyperion data increases. Moreover, using an optimization algorithm to determine the optimal features in the classification process will increase the separation accuracy of green spaces and rice fields. Given the overall accuracy values, the efficiency of GSA for separating green spaces and rice fields is higher than PSO.
Geographic Data
Mehran Maghsoudi; Mohamad Fathollahzadeh; Hamid Ganjaeian
Abstract
Extended Abstract
Introduction
Surface winds move and transport soil particles on the ground and thus, affect the intensity of erosion to a great degree (Tage Din et al, 1986: 118). Various studies have found a decreasing trend for surface wind speed in different parts of the world in recent years. ...
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Extended Abstract
Introduction
Surface winds move and transport soil particles on the ground and thus, affect the intensity of erosion to a great degree (Tage Din et al, 1986: 118). Various studies have found a decreasing trend for surface wind speed in different parts of the world in recent years. This decrease has been more widely reported in mid-latitudes (McVicar et al, 2008). Continuous drought in consecutive years is one of the factors that can reduce soil moisture and stop the growth of vegetation cover. (Hereher at el, 2009). Iran is located in the arid belt of the world and two thirds of its total area is located in these arid regions (Maghsoudi, 2006). Previous studies have shown that 17 provinces of the country are affected by wind erosion, among which Kerman faces a more severe conditions. Iran has more than 20 relatively large ergs and several small ergs covering an area of approximately 36,000 square kilometers (Mahmoudi, 1991). The present study investigates different characteristics of winds and its effects on morphology and displacement of sand dunes using Sentinel-2 optical and Sentinel_1 radar images.
Materials and Methods
Due to the lack of any synoptic station in the Lut Desert, related data including wind direction and speed were collected from 6 neighboring stations (Bam, Dehsalm, Zabol, Shahdad, Nusratabad and Nehbandan). Then, a wind rose and a sand rose graph were prepared for each station using WR Plot and Sand Rose Graph software. Resultant force vector acting in the displacement of sands and formation of sand dunes was determined. Following an examination of wind characteristics in the study area using Sentinel-2 optical images collected in the 2016 - 2019 reference period, changes of sand dunes and direction of their movements were also analyzed. In order to investigate vertical displacement in the region, radar interference method and SBAS time series have been used. This method only uses pairs of images in which vertical component of the baseline is less than its critical value, and also have a minimum baseline time. 45 Sentinel_1 radar images were used in the present study to measure radar interference.
Results
Recorded data in Dehsalm, Nehbandan, and Nosrat Abad stations indicate that winds blowing in these stations affect the Lut Desert. The prevailing wind recorded in Dehsalm station blows in northwest to southeast direction of the Lut Erg, while in Nehbandan station, the prevailing wind blows in north to south direction of this Erg. The prevailing wind in Nosrat Abad station blows in southeast to northwest direction of this erg. Sand rose graphs show that DPt in Dehsalam station equals 422.6 and in Nehbandan station equals 484.2. Since both DPts are more than 400, wind in this region has a high energy level and is potentially capable of sand displacement. Changes of sand dunes and direction of their movements were analyzed using Sentinel-2 and Sentinel-1 images in 2016-2019 reference period.
Discussion and Conclusion
Hourly wind speed and direction data in Nehbandan, Dehsalam, and Nosratabad stations were investigated in the present study to evaluate their impact on geomorphological changes in the Lut Erg and its sand dunes. Results indicate that the prevailing wind in these stations blows in north, northwest and southeast direction towards the Lut Erg, respectively. Investigating wind speed changes in Nehbandan station shows that during the last 34 years, average monthly wind speed in this station has decreased from 3.7 meters per second in 1986 to about 2.2 meters per second in 2020, which means a 1.5 meters per second decrease has occurred during this period. Apart from wind speed and direction data, Sentinel-2 optical images were also used to monitor changes in sand dunes of the Lut Erg. Results indicate that during the 2017 - 2018 reference period, most changes have occurred in the sand dunes of the northwest and northeast regions and the margins of this erg, while in the 2018 - 2019 reference period, most changes have occurred in the northwest and southeast regions of the Lut Erg. Analysis of satellite images indicates that the direction of wind force vectors is consistent with the direction of sand transport vector. In other words, sand dune changes in the Lut Erg have occurred under the influence of winds blowing in northwest and southeast directions, which is consistent with the direction of the sand transport vector in plots prepared for the three stations (Nehbandan, Dehsalam, and Nusrataba).
In order to validate the results of wind direction and speed analysis and remote sensing of optical images, vertical displacement of the erg surface was measured in 4-year periods using Sentinel_1 radar images and SBAS time series. In general, southern parts of the Lut Erg and especially sand dunes in these parts have experienced an increase in elevation, while the northern parts of Erg have experienced a decrease in elevation. This can be due to erosion and deposition of sediments in the southern regions of the Lut Erg, which is consistent with the sand rose and wind rose graphs prepared for the region .
Qassem Safari; Mohammad Reza Malek
Abstract
Extended Abstract
Introduction
Earthquake is one of the most frequent natural hazardsannually leading to numerous human and economic losses. Both in the planning stage and after the earthquake occurrence in the relief phase,findingappropriate sites for temporary housing is considered to be one ...
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Extended Abstract
Introduction
Earthquake is one of the most frequent natural hazardsannually leading to numerous human and economic losses. Both in the planning stage and after the earthquake occurrence in the relief phase,findingappropriate sites for temporary housing is considered to be one of the most important issues in reduction of damages caused by earthquake. Temporary housing, especially in a crisis situation is always accompanied by elements of uncertainty. Hence, definitive and classical approaches normally do not lead to acceptable results without involving elements of uncertainty. Although using methods based on fuzzy logic and fuzzy set theory are conventional and appropriate for uncertainty modeling, these methods also have their own disadvantages. For an instance, they require a certain and definitive membership function for each parameter. Moreover,fuzzy theory cannot describe verbal variables related to doubt and hesitation.
Temporary housing is always accompanied byuncertainty.Thus, fuzzy theory cannot lead to reliable results in this regard. However, in case sufficient information is not obtained using fuzzy theory, intuitionistic fuzzy logic isconsidered to be an appropriate solution for this problem and uncertaintymodeling. Despite various applications of intuitionistic fuzzy logic in uncertainty modeling, few researches have focused on this method.
Materials & Methods
Designing a qualitative model based on human knowledge requires a rule-based inference system, which is called an Expert System. This system consists of several parts. In the knowledge-based part, data and a set of rules, which are based on expert knowledgearesavedin the form of logical sentences. The input of this system is a set of numbers fuzzified in the inference engine by a set of fuzzy rules. Then,defuzzification is performed to map the fuzzy set and reach a certain point. In other words, the outputs must be readable and easy for the users.
The present study takes advantage of fuzzy and intuitionistic fuzzy approaches todetermine optimal sites for temporary housing. Furthermore, determinant factors of danger and safety followinganearthquakeare used to identify safe places for sheltering in such situations. The present study has applied layers of faults, hospitals, emergency and medical centers, fire stations, parks and green spaces, and roads as determinant factors. New spatial layers were produced for each ofthe aforementioned layers using distance and other similar functions. Then, trapezoidal functionwas used to determine membership and non-membership function of each layer in both fuzzy and intuitionistic fuzzy methods. Membership functions obtained from these methods are different in that they assign different membership values to the pixels surrounding the layer. Following the definition of membership and non-membership functions for each layer in both methods, temporary accommodation maps were obtained using the classical fuzzy as well as intuitionistic fuzzy methods.
Results and Discussion
The results obtained from these two methods were not identical. The main reason for this difference is that they treat data uncertainty differently. Furthermore, the results of membership and non-membership functions inintuitionistic fuzzy are not complementary. This provides us with a powerful tool for interpretation and, of course, decision making about the study area. As the first case, membership and non-membership degreesequal zero and one implying that the membership degree equals one and the non-membership degree equalszero. This occurs when the method identifies the area as quite appropriate for temporary housing after the earthquake. In this case,results are determinative, and data can be used in the area. In the second case, membership and non-membership degreesare low, which occurs in areas lacking enough information. It implies that more information is neededin such areas for decision making. The third condition takes place when both membership and non-membership degrees equal 0.5. In such a case,it can be conclude that either the stated variable belongs to the area with a membership degree of 0.5, or the variable doesn’t belong to the area with a non-membership degree of 0.5. In the fourth condition, the membership degree is high and the non-membership degree is low. In this case, the results can be trusted and used in decision-making. The fifth condition is in contrast with the fourth case. It occurs when the non-membership degree is high and membership degree is low. Under this condition, it can be concluded that the results are not reliable.
Conclusion
The proposed method and model were implemented in the second district of Tehran. According to the results, it can be concluded that the proposed approachperforms better than theclassical fuzzy approach, especially in the presence ofuncertainvariablesand lack of adequate data.
Saeid Hamzeh; Afshin Amiri
Abstract
Extended Abstract Introduction As a type of mass movement involving slow or rapid movement of soil, rock material or both on the lower hillsides, landslide is under the effect of gravity.Landslide is recognized as one of the most common geological disasters causing worldwide damages and casualties.Landslide ...
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Extended Abstract Introduction As a type of mass movement involving slow or rapid movement of soil, rock material or both on the lower hillsides, landslide is under the effect of gravity.Landslide is recognized as one of the most common geological disasters causing worldwide damages and casualties.Landslide susceptibility maps provide important and valuable information,including time scale of possible future landslides, which are usedfor predicting landslide hazards. Since predicting the time of landslide occurrence is beyond the capability of science and knowledge, identifying areas susceptible to landslide and ranking them can extensively restrict the damages caused by landslide. Therefore, it is essential to zone landslide risk and identify factors affecting it. Analytic Network Process(ANP) is aGIS-based Multi-Criteria Decision Analysis(GIS MCDA) method successfully applied to many decision-making systems. The present study seeks to evaluate landslide risk and achieve a zoning map for the sub-basin under study using ANP and Weighted Overlaymethods. Materials and Methods Based on the literature and using different experts’ viewpoint, criteria affecting landslide risk were identified and five major criteria including topography, land use and land cover, geology, hydrometry and infrastructure were selected. The selected criteria include the following sub-criteria: slope, slope direction, curvature, elevation, lithology, soil type, land use, vegetation density, distance from roads, distance from habitat, river and drainage density and precipitation. The effective factor layers were standardized and a specific scale was defined for their units.Then, each layer was assigned a weight based on its role and importanceusing Analytic Network Process.Proposed to modify Analytic Hierarchical Process(AHP), this method (ANP) relies on the analyses of the human brain for complex and fuzzy problems.Network Analysis Process generally includes the following steps: determining indicators, criteria and options;classifying identified criteria into clusters and elements; determining the relationship between clusters, elements and options; performing pairwise comparisons between clusters, elements and options, and finally calculating the final weight of elements and options. UsingWeightedOverlaymethod, these elements were then integrated with their related coefficients and the final landslide risk map was obtained. Results and discussion Each criteria and sub-criteria were weighted using Analytic Network Processmethod.Topographic and land cover criteria had the most and hydrographic criteria had the least impact on the landslide occurrence. According to the final map, most landslides have occurred in eastern and southern slopes at an altitude of 500 to 2,200 meters. Moreover, 17/31% of the study area was located in the very high-risk class and 33% in the high risk class (about half of the area has high potential of landslide). Previous landslide data were used to assess the landslide zoning map results. Results indicate that most landslides have occurred in the high risk class (about 35% of landslides) and only about 4% of landslides have occurred in the very low risk class. Conclusion Landslide is one of the natural hazards causing serious harms and problems for human life. Identifying the factors affecting landslide and zoning its hazard is especially important for the identification of risky and susceptible areas.So, landslides were selected as one of the main topics of the study with the aim of controlling and managing its hazards.The ANP network analysis method was used to model and predict landslide risk in this research.Each criteria and sub-criteria were weighted and overlapped to producethe map of relative landsliderisk.The lowest risk was observed in the northern parts of the region, and the highest landslide risk was observed in the northern hillsides with higher humidity.WeightedOverlaymethod and network analysis model were effective in predicting landslide susceptibility and producing landslide zoning map.
Hadi Fadaei
Abstract
Extended Abstract Introduction One of the major environmental issues and requirementsof the contemporary worldis the acquisition of knowledge and related technologies. Urban Heat Island (UHI) refers to the occurrence of higher surface temperature in urban areas compared to the surrounding rural areas ...
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Extended Abstract Introduction One of the major environmental issues and requirementsof the contemporary worldis the acquisition of knowledge and related technologies. Urban Heat Island (UHI) refers to the occurrence of higher surface temperature in urban areas compared to the surrounding rural areas due to high urbanization. Urban Heat Island (UHI) is an important ecological effect of rapid urbanization. While the temporal and spatial importance of UHIs and their causes have been discussed in previous studies, precise identification of the morphology and shape of the earth and its relation with UHIs have not been studied. Urban heat islands occur primarily due tourban developmentand changes in land surface. This has created unfavorable conditions and many problemsfor citizens. Vegetation cover can reduce the effect of heat island. Satellite data can be used to determine the distribution of urban heat islands, but new methods of measurement are still needed to get better results.Ground data can also help in validation of remote sensing analysis. The present study has investigatedurban heat islands occurring in the city of Tehran and its suburbs due to urbanization and traffic. Method The present study has been carried out in Tehran, the capital city of Iran, located in the northern part of the country,on the southern slopes of the Alborz Mountain Range, along 51⁰ to 51⁰ 40′ easternlongitudeand 35 ⁰ 30′ to 35 ⁰ 51′ northernlatitude. According to the latest population and housing census in 2011 performed by the Statistical Center of Iran, Tehran has a population of 8,154,051 and still is the most densely populated city of Iran with a clear demographic difference with other cities of the country. The study area borders with mountainous areas of the north and desertsof the south, thus the southern and northern regions of the study area have different climates. The northern regions have cold and dry climates, while the southern parts suffer from hot and dry climates. The elevation varies from 900 to 1800 meters. This huge difference inelevationis due to the vast area of the city. In Tehran metropolis, the average annual temperature varies between 18 and 15 ° C, and different parts of the city have an average temperature difference of 3 ° Cdue to the elevation difference in the city. Average monthly relative humidity including minimum and maximum relative humidity recorded at Mehrabad station shows that in in the morningof July to January, humidity changes from at least 38% to a maximum of 79%. Midnight relative humidity varies from 15% to 18% in June to 47% in February. The annual rainfall in Tehran is mainly influenced by the difference in elevation and varies between 422 mm in the north and at least 145 mm in the southeast. The number of rainy days also follows the same pattern and varies between 89 days in the north and 33 days in the south. Also in this urban area, 205 to 213 days of each yearhave a clear sky with some cloud. In this exploratory study, Landsat 8 satellite images for Tehran were obtained and processed (geometrical, radiometric and atmospheric corrections). The Operation Land Imager(OLI)with its three new bands: a deep blue band for coastal / aerosols studies (band 1), a short-wave infrared band for cirrus cloudsdetection and Band Quality Assessment (Band 9), and an Infrared Thermal Sensor (TIRS) which offers two high resolution thermal bands (approx. 30 m) (band 10, 11) were used. In addition, two of the valuable thermal bands at 10.9 µm and 12.0 µm have Landsat 8 images. In this study, spectral reflections of all terrestrial members of spectral phenomena were obtained based on the total wavelengths of Landsat 8 (wavelengths of 430-2290 nm). For UHI estimation,surface temperature can be obtained from the two thermal bandsand improved using split-window methods.The relation between thermal islands can be calculated using air pollution ground data. The present study tries to select suitable indices such as Normalized Difference Vegetation Index (NDVI). The vegetation index (NDVI) of land surface was calculated using spectral bands. Results The LST map was produced using Landsat OLI 8 satellite images. Temperature in this map was obtained using standard deviation from the classified values,and areas affected by the UHI were identified subsequently. According to the LST map, the surface temperature varies between 21.5 ° C and 57.9 ° C. On the day of imaging, the lowest average temperature of water was 35 ° C and the maximum average temperature of bare lands was 48 ° C in the study area. Recommendations It is recommended to use spectral reflectance measurements such as field spectroradiometer in natural conditions to evaluate the spectral reflectance accuracy. At a later stage, spectral reflection of different phenomena can be used to classify satellite images and examine their relationship with the urban heat islands
Amirhossein Halabian; Nader Parvin; Roya Naghibzadeh
Abstract
Extended Abstract
Introduction:
Due to the kind of its usage in a relatively long period, the analysis of temperature levels of modern cities is among the most important subjects that can be considered in the field of geography and environment, and its results can be used in promoting the science and ...
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Extended Abstract
Introduction:
Due to the kind of its usage in a relatively long period, the analysis of temperature levels of modern cities is among the most important subjects that can be considered in the field of geography and environment, and its results can be used in promoting the science and solving the problems of today’s societies. The effect of temperature on climate, is one of the crucial indexes of this procedure, especially in metropolises. The rise in the land surface temperature, which is an indicator of the heat intensity, is among the important elements for identifying theweather changes. The emergence of heat in cities is one of the most known forms of such changes. Urban heat islands are indicated by a temperature inversion and annoying temperatures throughout winters and summers. The temperature of some cities or urban areas has remarkably grown compared to the suburbs or rural areas around them. This phenomenon, called urban heat island, has caused numerous problems.
The term “heat island” was proposed by Havard for the first time almost a century ago in 1833 (Sook, 2004: 10). Afterward, numerous studies were carried out in the large and industrialized cities of the world, whoseresults demonstrated that civilization has exerted significant changes in the meteorological parameters and properties of the ground surface, and consequently, remarkable variations in local climate (Mousavi Baygi et al., 2012: 36).
Research objectives:
The present research is aimed at identifying the places with high heat, which have created the known thermal patterns in theArakcity in Iran. Assessment of the spatial-temporal variations of the urban heat islands can be used as a critical component in the management strategies of natural resources and environmental changes, whose results can be useful for environmental, regional, and urban planners.
Methodology:
The studied area, Arak, is the capital of the Markazi Province in Iran, with an area of 304.8 km2 at 1755 m above mean sea level. The city has temperate weather tending to cold and semi-arid. According to enactment in 2011, Arak has five municipal districts.
The research method was analytical-statistical, and an effort was made to evaluate the relationship between land surface temperature and land cover of the city.
In order to evaluate the development of hot places in Arak and determine its urban thermal patterns and heat islands in the long term, the data of the satellite images of the Landsat scanners 4, 5, 7, and 8, including the data of the TM scanners of Landsat’s 4 and 5, Landsat 7 (+ETM), and Landsat 8 (OLI/TIRS), during the period 1985-2017 were used. These images include two sets of reflective spectral and thermal bands. The thermal bands were used to identify the surface temperature and thermal islands, and the reflective bands were employed to apply the indexes of image processing. The data of the TM, +ETM, and OLI/TIRS scanners were provided in the bands 6, 8, and 11, respectively. The data of the thermal band 6 of Landsats 5 and 7 with wavelengths of 10.40-12.5 micrometers and the band 10 of Landsat 8 with wavelengths of 10.60-11.19 micrometers were used to calculate the surface temperature distribution patterns of Arak. The bands 3 and 4 of Landsats 5 and 7, along with bands 4 and 5 of Landsat 8, were also utilized to calculate the NDVI index (NASA, 2014). In the global imaging system, the images of the Arak areaexist in the 165th And 36th row.
Generally, the following steps were taken to analyze the urban heat islands of Arak:
Calculation of LST and spectral radiance
Conversion of the calculated radiation to Kelvin temperature
Calculation of the temperature levels of five districts of Arak
Calculation of the density percentage of the fourth level of temperature (hot points of the city)
The minimum, maximum, and average temperatures of Arak
Calculation of normalized difference vegetation index (NDVI)
Calculation of the urban thermal field variance index (UTFVI)
Results and discussion
Evaluation of the land surface temperature changes and patterns
The analysis of the vegetation variations demonstrated that depending on different uses of urban lands, vegetation is in accordance with the temperature level. Generally, the low temperature in the southwest of the city, which was observed in the land surface temperature maps, is caused by the gardens of Senejan and Karahroud cities. The eastern and southeastern parts of district 1, which has industrial uses, streets with heavy traffic, and accumulation of uses, and the north of the city, i.e., the north of district 3 with the accumulation of residential uses and heavy traffics, have higher temperatures. Generally, during the study period on vegetation, all areas having this usehad considerable changes, except for the northwestern part. Most of the vegetation in the study period was concentrated in districts 4 and 5, which included the gardens of Senejan and Karahroud. However, other parts of the city, including the northwest and, to some extent, the city center and district 1, whose vegetation includes several parks and green spaces, show decreasing changes in temperature.
Based on the results obtained from evaluating the urban thermal field variance index (UTFV) of Arak, using 20 land surface temperature (LST) maps and normalized difference vegetation index (NDVI), obtained from Landsat satellite, (TM), (ETM+), (OLI/TRS), the very hot temperature level of Arak was widely observed in the north, northeast, east, and southeast of district 1, north and northwest of district 3, west and southwest of district 2, and west ofdistrict 5.
Conclusions
The evaluation of the LST maps to identify the hot points and urban thermal patterns revealed that most of the hot points are located in the areas with idle lands in the suburbs. These lands are mostly observed in the recently developed areas of the suburbs, including districts 1 and 3. Inside the city, most of the hot places conform to the formation of thermal patterns close to industrial towns, streets with heavy traffic and high pollution, and residential areas with dense and urban decay.
The largest area of the third temperature level is observed in district 1 due to the presence of industrial towns, dense residential towns, cultural and governmental organizations, heavy traffics in the streets, the northern and southern belts in the district, and idle lands in the north and east of the district. The presence of the industrial towns and factories in the city of Arak, especially in district 1, is one of the effective factors in increasing the heat and creating thermal patterns. The thermal patterns in district 1 had the highest intensity in 1988/09/08 and 2017/01/08 during the study period.
Ilia Laaliniyat; Mousa Kamanroudi Koujori; Tajeddin Karami
Abstract
Extended AbstractIntroductionThe third millennium has been called the age of urbanization and the urban population is expected to reach about 6.25 billion by 2050. The United Nations also estimates that the urban population of developing regions will grow at an average annual rate of about 2.02 percent, ...
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Extended AbstractIntroductionThe third millennium has been called the age of urbanization and the urban population is expected to reach about 6.25 billion by 2050. The United Nations also estimates that the urban population of developing regions will grow at an average annual rate of about 2.02 percent, from 2.67 billion in 2011 to 3.92 billion in 2030. Indeed, the urbanization process is a phenomenon that has become increasingly concentrated in developing countries in recent decades. Although the pace of change varies considerably between countries and regions, in fact all developing countries are becoming increasingly urbanized. The increase in urbanization has caused many problems in urban areas. This has led to the fact that today land use management of urban infrastructure has become the main challenge of many planners and city managers. Accordingly, this study seeks to investigate the scattering around the Tehran-Eyvanekey communication axis, so Pakdasht cities with about 210 thousand people , Sharifabad with about 12,000 people and Eyvanekey with about 12,000 people, make it one of the busiest axes in the metropolitan area of Tehran. Research MethodsThe main purpose of this study is to analyze the process of space expansion and modeling in the axis of Tehran Eyvanekey between 1985 and 2020 using remote sensing data and GIS. To have a comprehensive study of spatial organization of this metropolis, a deductive or inductive approach with a practical nature has been used. The basis of the study is based on using the satellite data and images (Landsat multi-time images) related to different years. Using IDRISI, GIS and GOOGLE EARTH softwares and Fuzzy Artmap LCM, MARKOV and CA models. Discussion resultsIn this study, in order to evaluate the pattern of expansion of built areas in the corridor of Tehran to Eyvanekey, TM and ETM + images of Landsat satellite related to the years 1985, 2000, 2011, and 2020 have been used. Based on this, the amount of land use changes in the four periods is as follows: The most expansion of practical surfaces in the axis of Tehran-Eyvanekey with an area of 223250 hectares, dedicated to built areas with an increase of 30,495 hectares over the last 35 years. After identifying the urban expansion pattern of Tehran-Eyvanekey corridor, in the next stage, in order to simulate how land use changes in the axis of Tehran-Eyvanekey for the year 2031, the method of automatic cells and chains has been used. For this purpose, to simulate land use changes in the axis of Tehran Eyvanekey in 2031, land use maps in 1985 and 2020 were used. The results show that according to the trend of urban growth in the region in 2031, the land area will reach more than 50,000 hectares. Also, according to the growth rate of urban areas in this region, it can be seen that during different periods, we see a kind of exponential growth in the study area, so that for the period 1985 to 2000, about 240 hectares per year have been built. This trend of growth has expanded and in the next period, ie 2000 to 2011, this number has reached about 580 hectares, and finally in the last period, ie 2011 to 2020, we have witnessed the expansion of about 2251 hectares per year in the built lands, which can be signs of accelerative urbanization. Therefore, the strategy of increasing physical density and using related methods to guide the development of the city towards greater sustainability, should be on the agenda of planners and those in charge of urban affairs. ConclusionModeling land use changes is an effective way to obtain information about how land use changes over time as well as the factors affect it. So, in order to analyze the process of space expansion and modeling in the axis of Tehran-Eyvanekey, it was modeled over a period of 35 years. The results showed that most of the land use changes during this period are related to the built lands, which due to the location of the built areas along the main arteries has a northwest-southeast pattern that is affected by urban growth in the metropolis of Tehran. As a result, they live in these areas, which are either engaged in the urban industries of these areas or use the satellite cities in this corridor as dormitory cities. Interestingly, as we move away from the main center, the metropolis of Tehran, the rate of urban land expansion decreases, which indicates that due to the low cost of housing in satellite cities, this area is a dormitory for the metropolis of Tehran.
Homayoun Khoshravan
Abstract
Extended Abstract:
Introduction
Increased density of Co2 in the atmosphere during the Anthropocene epoch has resulted in pervasive concerns for the global environment. Global warming has resulted in sea level rise and coastal flooding. Forecasting has indicated that a vast area of coastal countries ...
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Extended Abstract:
Introduction
Increased density of Co2 in the atmosphere during the Anthropocene epoch has resulted in pervasive concerns for the global environment. Global warming has resulted in sea level rise and coastal flooding. Forecasting has indicated that a vast area of coastal countries and their economic and social infrastructureswill be damaged due to 200 cm sea level rise by2100. Sea level rise in oceans has caused coastal erosion and flooding. Thus, it is considered as a real threat to coastal environment. The Caspian Sea environment has reacted differently to climate changesduring the last 70 years and vast areas of its coastal lagoons have dried. Therefore, the present study primarily seeks toinvestigate ecological variations of coastal habitats in the Gorgan Bay during the period of 1995 to 2019.
Materials and methods
Gorgan Bay and Miankaleh Lagoon are considered to be among global biosphere reservesand the most important protected areasalong the southern coasts of the Caspian Sea. The present study has evaluated coastal variations, such as shoreline displacement, changes in the depth of sea bed, land cover and coastal habitats using satellite images and GIS processing. Shorelines of Gorgan Bay are determined usingremote sensing software Envi 5.3, while land cover and coastal habitats are evaluated through GIS processing in Arc – Map 10. 5. The shoreline is determined through the calculationsperformedonthe proportion of green and blue bands in reflected electromagnetic waves and histogram thresholding of near infrared (NIR) spectrum in Envi 5.3. The total area of Gorgan Bay was determinedusingthe Normalized Distance Water Index (NDWI).The most important land covers and coastal habitats are classified using Support Vector Machine (SVM). Finally,variations of coastal habitats are calculated using Change Detection Workflow index and the final maps areproduced in Arc Map 10.5.
Results and discussion
Results indicate that due to about 150 cm decrease in the Caspian Sea level from 1995 to 2019, the total area ofGorgan Bay has faced about 176 km decrease. Bathymetric maps shows that the depth of Gorgan Bay has decreased dramatically along the East to west side. The depth of the Ashouradeh and Chopoghlei inlets have also decreased and vast areas of these water bodies haveturned into arid islands. The Gorgan Bay is connected to the Caspian Sea through some narrow channels. The most important land covers and coastal habitats of the Gorgan Bay in 2019 include sandy beach (2%), salt marsh (7%), brackish marsh (14%), wetland (15%), mudflat (7%), coastal forest (10%) and coastal lagoons (45%). The total area of coastal lagoons, vegetation covering and sandy beaches have decreased from 1995 to 2019 and the area of the brackish marsh, salt marsh, mud flat and pit wetlands have increased at the same time. The total area of sandy beaches have decreased about 52 Km2 since 1995.Instead,the area covered by salt marshes and brackish marshes have increased by about 87 and 60 Km2 during the same period.62 Km2 of mud flat have been created during the same time,and thus, the area of Miankaleh Lagoon and Gorgan Bay have decreased by about 176 Km2. The environment of Gorgan Bay and Miankaleh Lagoon is directly related to the fluctuations in theCaspian Sea level. Survival of these coastal lagoons depends on permanent water exchange between the Caspian Sea and Gorgan Bay. Rapid fluctuations of the Caspian Sea level and high levelof deposition are considered to be among the most important factorsof coastal habitats destruction and ecosystems displacement. These natural phenomena happened twice during the Anthropocene period (1945- 1978 and 1995-2019).
Conclusion
Results have confirmed that arid ecosystems have replaced aquatic ecosystems in study area. The main results of the study have confirmed that the fluctuation in the Caspian Sea level has direct impact on coastal habitats of the study area and decreasing sea level could change marginal ecosystems. Due to the decrease in water exchange volume rate between the Caspian Sea and Gorgan Bay during the 1995- 2019 period, a 32 percent decrease has happened in the area ofGorgan Bay and salt marshes have dominated along the Gorgan Bay coastal area. Unfortunately, the continual decrease inthe Caspian Sea level can destroy biodiversity and coastal habitats in the future. Therefore,integrated coastal zone management (ICZM (is influential insaving and preserving of the Gorgan Bay.
Geographic Information System (GIS)
Zhila Yaghoubi; Ali Asghar Alesheikh; Omid Reza Abbasi
Abstract
Extended AbstractIntroductionSelecting a suitable place for a new retail store is a very important decision since new shops cost a lot and new retailers puts themselves at financial risk. Physical location of stores affects the consumer's perception of their first purchase and their subsequent loyalty ...
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Extended AbstractIntroductionSelecting a suitable place for a new retail store is a very important decision since new shops cost a lot and new retailers puts themselves at financial risk. Physical location of stores affects the consumer's perception of their first purchase and their subsequent loyalty to the store. Therefore, spatial analysis is very important for retail stores. Site selection for retail stores has always been difficult and the current competitive market has made decision making even more difficult since stores face increased competition and consumers have many options to satisfy their needs. They generally choose a suitable store in their vicinity which provides high quality, cheap, and diverse products. Therefore, markets and especially retailers shall follow an accurate and valid location strategy for new stores. Retail stores have various marketing and customer service strategies. Marketing strategies require a lot of information about different aspects such as customers, shops, competitors, and products. Many marketing strategies only provide information about consumer behavior or customer satisfaction. However, spatial aspects are more important and in fact determine future success of a store. Several methods are used for spatial analysis in retail sector. The present study use a multiplicative interaction model to forecast sales of confectionaries. This can help retailers develop strategies and find an optimal location for their new stores. Materials & MethodsThe present study has developed a location-based marketing model for online confectioneries in Tehran which can improve site selection strategies of new confectioneries. This marketing model is based on the multiplicative competitive interaction model (MCI) of the retail location theory. To do so, characteristics attracting customers to confectioneries are determined and related data are collected from the Snappfood online platform through web crawling. ArcMap software is then used to analyze and process the collected data. After data normalization, MCI model is implemented using Python programming language. The model is then calibrated using 80% of the collected data and the ordinary least squares (OLS) method. The model is then evaluated using root mean square error (RMSE) method and the remaining data. Results and DiscussionMean errors obtained for districts number 1 to 22 of Tehran municipality show high accuracy of the model. Snappfood site lacked any information about districts number 9 and 18 and thus these districts were not considered in the calculations. Depending on the available data, other districts showed different levels of accuracy. Results indicate that district number 22 had the lowest level of accuracy and district 17 had the highest level of accuracy. In general, this model predicts customer behavior with an error rate of 17.03%. Results of the present study show the probability of purchasing from each confectionery which can be used to map market potential for a new store. This map determines the best place with maximum sale and helps in site selection for new stores based on specific features of the store, competitors and the environment. ConclusionsMCI model predicts sales. From a geomarketing perspective, this model shows that distance between customers and the store and accessibility affect location strategies in new stores. Variables such as pricing and customer satisfaction (scoring) are used to improve the goodness-of- fit of the model. This precise method identifies some key factors to success in a retail strategy. It predicts the probability of purchasing in each district, the number of customers in each store, and distribution of customers in each district. Experts and new retailers can use the results to design various location and sales strategies. Using this model, new retailers in confectionary market can accurately predict their sales before even opening the store and thus protect themselves against possible financial losses. Moreover, this model predicts total sales of different stores and help retailers compare their market shares with those of their competitors. They also can enter features of a new store into the model and find several potential sales strategies. In other words, the model helps determine sales of existing and new shops. In this way, retailers can find an optimum location for their new confectioneries based on the principles of geomarketing.
Fariba Moghani Rahimi; Ahmad Mazidi; Hamid Reza Ghafarian Malamiri
Abstract
Abstract ExtendedIntroductionStudying land cover changes has a very long history which coincides with the beginning of human life. Following the formation of societies, primitive humans began to change the cover of wasteland to form suitable lands for agriculture and animal husbandry. More than half ...
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Abstract ExtendedIntroductionStudying land cover changes has a very long history which coincides with the beginning of human life. Following the formation of societies, primitive humans began to change the cover of wasteland to form suitable lands for agriculture and animal husbandry. More than half of the world's population recently lives in cities, urbanization and urbanism is rapidly increasing, and this trend will continue to reach its peak. Due to their extensive coverage, reproducibility, easy-access, high accuracy and reduction in necessary time and expenses, remote sensing data are generally considered a preferred method used to study land cover, vegetation, and their changes. Many researchers have shown an interest in land cover change in different cities of the world. The history of land cover studies dates back to the early nineteenth century and the studies performed by von Thünen (1826). Von Thünen have determined the economic benefits of different land covers based on their distance from the central city and found an optimal distribution for production and land cover in the form of a series of concentric circles. Land cover changes due to human activities are considered to be an important topic in regional and development planning. Since land cover changes and urban development in the study area have not been previously studied, Landsat time series satellite imagery and a combination of Landsat 7 and 8 panchromatic and multispectral bands were used to identify and detect changes in land cover and urban development in the urban areas of Abarkooh from 2000 to 2020. Materials & MethodsSatellite remote sensing data are used in the present study (Landsat 7 and 8 multi-temporal satellite images collected in 2000, 2010 and 2020). 3 images were retrieved from US Geological Survey website and used in the present study. Raw remote sensing images always contain errors in geometry and the measured pixel values. The former category is called geometric errors and the latter is called radiometric errors. Atmospheric corrections were performed for all images used, and stripping in the imagery collected in 2010 image was also corrected. For image enhancement and extraction of more information from the images, false color composites were used (5-4-3 infrared, red and green bands) for Landsat 8 and Landsat 7 (3-4-3 near infrared, red and green bands) images. Using this technique, vegetation is shown in red. Compared to other methods, Gram-Schmidt based pan sharpening method produced higher spatial resolution images of the study area and thus was used to combine the selected images. Maximum likelihood method is considered to have the highest efficiency among various supervised classification methods. Results & DiscussionThis method assumes the presence of a normal distribution for all training areas. The accuracy of this classification has to be calculated following the classification. To do so, the kappa coefficient and overall accuracy of each class were calculated in ENVI5.3. The results are shown in the error matrix. Overall accuracy is the average of classification accuracy. The kappa coefficient calculates the accuracy of classification as compared to a completely random classification. Based on the available data, spatial resolution of the images and the information researcher has access to, 5 classes of training data (urban constructed space, roads, barren lands, arable lands, and gardens) have been selected for each image. Results obtained from the maximum likelihood classification method in ENVI5.3 environment were changed into the vector format and then used as a shape file in GIS environment. After compiling the land database, land cover maps and its changes were extracted in three periods and the area of each land cover class was determined. Each of the land cover maps, 5 classes with different colors are determined and shown. To ensure the accuracy of the classification, the accuracy of the classification has been evaluated. ConclusionThe resulting kappa coefficient for 2000 and 2020 equaled 86% and overall accuracy equaled 89%, while for 2010 kappa coefficient equaled 90% and overall accuracy equaled 92%. Thus, the error rate is small and acceptable. Finally, post-classification comparison method was used to investigate the nature of changes. 13 square kilometers of land cover were investigated in the present study. To identify the exact type of land cover changes, categorized images collected in these years were compared. Total area of residential land use showed an increasing trend: a total 4.25 square kilometers in 2000 (32.69 percent of the total area under study) has reached 5.58 square kilometers (42.92 percent) in 2020. Overall area of arable land use did not change much in the period of 2000 to 2010. However, a declining trend was observed in 2020 changing a part of this land use into residential and barren lands. Results of satellite image processing and classification indicate that supervised classification and maximum probability algorithm were close to ground realities and had an acceptable accuracy. In general, results indicate that significant amounts of vegetation and agricultural lands have been converted into urban areas and thus, planning for urban growth in these areas should be in favor of preserving gardens and agricultural lands.
Valiollah Karimi; Eassa Kia; Mohammad Ali Maleki
Abstract
Extended AbstractIntroductionIndustrialization of communities and increased greenhouse gasses in the previous decades have resulted in increased global temperature and changes in climate parameters which are generally called climate change in scientific texts. Climate change has resulted in changes of ...
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Extended AbstractIntroductionIndustrialization of communities and increased greenhouse gasses in the previous decades have resulted in increased global temperature and changes in climate parameters which are generally called climate change in scientific texts. Climate change has resulted in changes of temporal and local precipitation patterns all around the world. Consequently, hydrological cycle has changed affecting intensity, duration and frequency of rainfall events. Intensity- duration- frequency curves are used to provide an economic and safe design for drainage facilities, check dams, urban water management structures such as culverts, surface water and sewage systems. They are also used in landslides studies. The present study seeks to compare rainfall intensities in Babolsar Synoptic Station before and after 1993 to understand the effect of climate changes on rainfall intensities during the mentioned 52-year statistical period. Materials&MethodsThe first synoptic station of Mazandaran province was set up in Babolsar city in 1952. With an elevation of -21 m from sea level and 7 m from the Caspian Sea level, it is located at the east longitude of 52o, 39̍, 30̎ and the north latitude of 36o, 43. The station has a mean annual rainfall of 928 mm and an average of 99 rainy days.To understand the effect of climate changes on rainfall intensities in different durations and return periods in Babolsar Synoptic Station, statistical period was divided into two 26-year subperiods (before: from 1968 to 1993 and after: from 1994 to 2019). Rainfall intensities were calculated separately for each of the 14 duration series (10, 20, 30, 40, 50, 60, 90 minutes and 2, 4, 6, 9, 12, 18 and 24 hours) with return periods of 2, 5, 10, 25, 50 and 100 years and compared together. Then, a paired t-test was conducted to prove the difference between two series of rainfall intensity to be significant. Moreover, 5 annual air temperature parameters including minimum absolute temperature, maximum absolute temperature, average minimum temperature, average maximum temperature and average temperature were investigated in both subperiods and analyzed using a paired t-test in SPSS software. Results were used to investigate temperature and precipitation changes during the statistical period and prove the difference between before and after time series data to be significant. Mann-Kendall test was also carried out on 5 air temperature parameters collected during the 52-year time series data to find ascending or descending trends. Results&DiscussionCompared to the first subperiod, the average rainfall intensities have increased in 10, 20, 30 minute and 12, 18 and 24-hour durations of the second statistical subperiod, while the opposite has occurred in 40, 50, 60, 90-minute, and 2, 4, 6 and 9-hour durations. However, statistical analysis has proved increased rainfall intensities in 10 and 20-minute, and 18 and 24-hour durations and decreased rainfall intensities in 50, 60, 90-minute, and 2, 4, 6 and 9-hour durations of the second statistical period to be significant. A paired t-test was conducted to compare rainfall intensity in the statistical subperiods and find out its effects on climate change. Results indicated that except for data collected in 30 and 40-minute and 12-hour durations, the difference between other paired series was significant at a less than 5% level.Moreover, except for maximum absolute air temperature, other air temperature parameters showed a significant difference at less than 0.5% level. Furthermore, all 5 parameters showed an increase in the second study period indicating a warmer climate in Babolsar.However, paired t-test results indicated that despite the reduction of mean annual rainfall in the second statistical period, difference between the two series was not significant at any acceptable level of significance. Moreover, results of the Mann-Kendall test indicated that average air temperature, average maximum air temperature, average minimum air temperature and minimum absolute air temperature have shown an ascending trend at a 1% significant level, while maximum absolute temperature lacked a specific trend and showed leap changes. Annual rainfall also showed random changes and lacked a specific trend during the 52 year statistical period. ConclusionResults of the Man-Kendall and paired t-test have shown that a significant increase have occurred in air temperature during the 52-year statistical period (1968-2019) resulting in climate changes.It can be concluded that climate change has increased the intensity of short-term (shorter than 40 minutes) and long-term (longer than 12 hours) precipitations and reduced the intensity of medium-term precipitations in Babolsar Synoptic Station. Moreover, climate change has increased the intensity of precipitations with short and long return periods while reducing the intensity of precipitations with medium-term return periods in the aforementioned Synoptic Station.
Mina Arast; Abolfazl Ranjbar; Khodayar Abdolahi; Sayed Hojjat Mousavi
Abstract
Introduction Evapotranspiration is one of the most important parts of the water cycle (Boegh and Soegaard 2004). Precise prediction of actual evapotranspiration () is essential for various fields, such as agriculture, water resource management, irrigation planning and plant growth modeling. Therefore, ...
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Introduction Evapotranspiration is one of the most important parts of the water cycle (Boegh and Soegaard 2004). Precise prediction of actual evapotranspiration () is essential for various fields, such as agriculture, water resource management, irrigation planning and plant growth modeling. Therefore, accurate determination of actual evapotranspiration has always been a major concern of experts in these fields. Due to the limited number of weather stations and the fact that collecting ground information is both time consuming and expensive, remote sensing and satellite imagerycan be a suitable tool in determination of actual evapotranspiration (Brisco et al., 2014). Satellite productions are usually divided into images with low, medium and high spatial resolution (Rao et al., 2017). Surface energy balance is a method usually used in combination withremotely sensed spatial data for estimation. Information collected from various sources, such as remotely sensedimageries and meteorological data, are used in this method. The present studyinvestigatesspatial distribution on different scales (from field- to regional-) using remotely sensed imagerieswithdifferent spatial and temporal resolution. TheSurface Energy Balance System (SEBS) is one of the most important methods used for the estimation of in remotely sensed images (Ochege et al., 2019). This model needs thermal maps produced using satellite images. Daily maps produced with RS are usually very large, and their pixelsize is usually so large that it can provide the spatial diversity found in the basins with respect to the errors (Mahour et al., 2017). Material and Methods In order to estimate the actual evapotranspirationin satellite images collected from Zayanderud basin,the effects of Co-Kriging downscaling of surface temperature (LST) were investigated in June 2017 using two different methods.To reach this aim, we first applied a co-kriging downscaling method to a low-power LST product collected from MODIS at 1000 meters. Then based on the results and using the SEBS system, the daily was obtained from images with average spatial resolution (250 m).In the second method, map produced usinghigh resoultion satellite imageswas downscaled to medium resolution (250 m). For both methods, 250 m resolutionMODIS NDVI products were used as co-variables.Then, validation was performed using Landsat-8 imagery, and land surface temperature was extracted from its thermal bands. SEBS algorithm was used to determine in Landsat 8 30-meter resolutionimagery. Accuracy of measurements wasexamined based on a comparison between down scaledLST and maps (250 meterresolution). Results and Discussion In the present study, mean LST equals 3/312 K (SD = 1.74) and average daily equals 12.5 mm / day (SD = 0.86). In the downscaling phase, the relationship between LST parameters and and vegetation index(as a co-variable)was investigated.Moreover, to investigate the relation betweenhigh resolution variables and NDVI, we re-sampled LST and variables from a 1000 mresolution to 250 mresolution.In250 mresolution, there is a negative linear relation (r=-0.85) between LST and NDVI, but the relation betweenand NDVI is positive (r = 0.80). Thus, lower LST (> 305k) indicates more vegetation (NDVI >0.3) inthe region, while higher LST results in lower NDVI or lack of vegetation. As a result, more vegetation can be observed in regions with higher(12 mm/day). Results indicated that the difference between average downscaled-SEBS (12.56 mm/day) and reference (13.11 mm/day) is negligible. The RMSE between the reference and the downscaled equaled 1.66 mm/day (r = 0.73), and RMSE between the reference LST and the downscaled LST equaled4.36 K (r = 0.78). Thus,values obtained from two downscaling methods were similar, but the obtained from downscaled LST showed a higher spatial variation. Therefore, LST has greatly influenced the production of maps using remotely sensing images, and Co-Kriging downscaling has been useful for providing daily maps with intermediate spatial resolution. Conclusion Evapotranspiration downscaling using the co-kriging method is not significantly different from the SEBS product and the results are similar. The results of -SEBS method isalso acceptable, but the derived from the SEBS algorithm is more variable due to the LST downscaling.
Ebrahim Sharifzadeh Aghdam; Mohammad Ajza Shokouhi
Abstract
Extended Abstract
Introduction
It can be argued that among the socially and culturally relevant variables affecting sustainable security and optimal control of border cities, political variables (formulation of the comprehensive plan and other urban plans), physical variables (distance between border ...
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Extended Abstract
Introduction
It can be argued that among the socially and culturally relevant variables affecting sustainable security and optimal control of border cities, political variables (formulation of the comprehensive plan and other urban plans), physical variables (distance between border cities and central or peripheral areas) and legalvariables (adaptingeconomic policies in accordance with themacroeconomic policies of the country by2025) are the basis for developingmatrix of key properties and scenario planning.In this regard, the importance and necessity of the present study lies in the fact that the future border cities research is a process of systematic and calculated effort and a long-term scientific approach toward good urban governance. It seeks to reach a sufficient understanding of strategic research areas, benefit economy of the country and especially border communities through wise management of space and the introduction of related technologiesand offer desirable scenarios for the development of border cities based on the patterns of democratic and ecosystem management.Accordingly, the present study demonstrates a kind of creativity and innovation in the field of strategic planning based on every aspects of sustainable urban development while emphasizing on the prospective and environmental aspects that are an inseparable part of geography and urban planning studies.
Materials & Methods
The present study seeks to answer the main research question which is, what are the key indicators and factors influencing the development analysis of Piranshahr border town?
In this regard, the present study takes advantage of descriptive-analyticaland documentary investigations of strategic planningalong withrelated questionnaires in the framework of Delphi model and software analysis. Based on a consultation with scholars familiar with the status and conditions of the region within the dialectical framework of urban issues, a statistical population of 50, and 23 variables were identified for the present research. The selected variables were classified in 8 general categorizations as the primary variables of the research.Getting output from the Wizards software based on the scores entered into the matrix, the normalized and the standardized matrices were calculated, and the possible scenarios were categorized based on an analysis of the descriptor compatibility. Then, the goals set for strategic planning of Piranshahr, effective factors in strategy development, a competitive map, level of competitiveness in Tamarchinborderand finally challenges and opportunities of each domain were expressed in the framework of the Meta SWOT Strategic Model.
Results & Discussion
Based on experts’ opinions and software output, it can be argued that among the socially and culturally relevant variables affecting sustainable security and optimal control of border cities, political variables (formulation of comprehensive plans and other urban plans), physical variables (distance between border cities and central or peripheral areas) and legalvariables (adaptingeconomic policies in accordance with themacroeconomic policies of the country by2025) are the basis for developingmatrix of key properties and scenario planning.
Finally, the status of key driving forces in cross-border strategic planning of Tamarchinborderand its effects on the development of Piranshahr city over the coming 15 years are explained in the form of three desirable, intermediate and disaster scenarios. Also based on the obtained results, Sairanband border in Bane had the highest score in enhancing the quality of life in border cities and adopting economic policies in accordance with the country’s macroeconomic policies by2025. Thus, Sairanbandis the most important rival of Tamarchin border.
Conclusion
The present study has proposeda desirable model for the development of Piranshahrborder town using a strategic approach toward the sustainability issue in border cities and taking advantage of indexes such as “cultural, human, political, economic, and physical development” indexes. It alsoapplies the pattern of futures studies used in wizard and strategic scenarios. Thus, factors affecting the level of urban development in Piranshahrwere classified based on 5general classes, sub-variables and a 23×23 matrix. So only by putting the indices in the distribution chart, a very favorable situation of the distribution of boundary related variables can be presented. In the context of the above mentioned results and according to the scenario formulation table, it can be concluded that the results of the present study are to a large extent applicable. Moreover, they can be applied for scenario-building and guide management toward the development of border towns within the framework of structural planning.
Mahdi Sedaghat; Hamid Nazaripour
Abstract
Extended Abstract Introduction Soil moisture is considered to be a key parameter in meteorology, hydrology, and agriculture, and the estimation of its temporal-spatial distribution contributes to understanding the relations between precipitation, evaporation, water cycle, and etc. Soil moisture reduction ...
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Extended Abstract Introduction Soil moisture is considered to be a key parameter in meteorology, hydrology, and agriculture, and the estimation of its temporal-spatial distribution contributes to understanding the relations between precipitation, evaporation, water cycle, and etc. Soil moisture reduction results in the creation of centers susceptible to dust storms. With socio-economic impacts ranging from urban to intercontinental and from a few minutes to several decades, this can challenge regional development. The first estimate of potential dust sources is derived from the soil properties. With the reduction of surface soil moisture and the wind speedcrossing a certain threshold level, wind erosion process can cause the formation of dust storms. Field studies have proved that increasing the moisture content in soil from zero to about 3%, reduces the dust concentrationsignificantly. To understand the climatology of dust and develop related numerical predictive methods, continuous recording of dust storms is essential, which requires effective and continuous monitoring of the variations in surface soil moisture. Remote sensing technology is an effective method for calculating soil moisture. This technology was first used for the estimation of energy flux and surface soil moisture in the 1970s. To extract the surface soil moisture content, some remote sensing methods use surface radiation temperature and some others apply water transfer (soil/vegetation/air) (SVAT) model. Various indices have been developed for soil moisture monitoring, such as soil moisture (SM), soil water index (SWI), Temperature-Vegetation-Dryness Index (TVDI), Soil Moisture Index (SMI) and Perpendicular Soil Moisture Index (PSMI), all of which combine vegetation and surface temperature variables. Materials and Methods Soil moisture is considered to be a significant parameter in the exchange of mass and energy between the Earth surface and the atmosphere. Lack of soil moisture or decreased moisture in soil is considered to be a factoraccelerating the process of dust storm formation. During the previous decades, water stresses on the ecosystem of Hour-al-Azim have transformed this wetland into one of the main dust centers in the southwest Iran. Hour-al-Azim is one of the largest wetlands in southwestern Iran. This wetland is shared between in Iran and Iraq. It is located between N 30° 58´- N31° 50´ and E 47° 20´- 47° 55´. The Iranian part of this wetland encompassed an area of 64,100 ha in the 1970s, while in the 2000s, the area has decreased to only 29,000 ha. The present study aims to monitor the spatial-temporal variability of soil moisture in Hour-al-Azim wetland and to investigate the relation between these changes and dust storms in the southwest Iran. To reach this end, we used 8-day images obtained from the Aqua satellite in the period of 2003 to 2017 and also annual frequency of dust storms with a visibility of less than 1000 m in the period of1987–2017. A database consisting of 189 images of the red band, near-infrared band, and ground surface temperature (LST) was created, which contained 4 images per year (one image per season). The resolution of the red / near-infrared band data and daily LST values were 231.65 and 926.62 meters, respectively. Then, soil adjusted vegetation indices (SAVI) and perpendicular soil moisture index (PSMI) were extracted. SAVI index is used to reduce the effect of background soil on vegetation cover in semi-arid and arid environments with less than 30% vegetation cover.Compared to NDVI, SAVIwith L = 0.5reduces the effect of soil changes on green plants. In the next step, a trapezoidal method was used to calculate the PSMI index. In order to investigate changes in the soil moisture content of the Hour-al-Azim wetland, three time series obtained from regional mean of SAVI, LST and PSMI remote sensing indices and a time series consisting of the number of days with dust storms observed in the 9 stations were evaluated using simple linear regression test. Results and discussion Extracting Soil Adjusted Vegetation Index indicated that in the study period, the highest values of this index was observed with a regional mean of 0.15 on 4/7/2014 and the lowest values was observed with a regional mean of 0.08 on 1/1/2005. Land Surface Temperature survey showed that during the study period, the highest values of this index was observed with a regional mean of 54.42 ° C on 7/4/2010 and the lowest values was observed with a regional mean of 17.28 ° C on 1/1/2007. The regional mean of Perpendicular Soil Moisture Index indicates that despite winter is considered to bethe wettest season of the region, PSMI index with a regional mean of 0.2 has experienced the driest soil moisture conditionsat the beginning of winter (1/1/2016),while it had experienced the wettest soil moisture conditionsin the same season on 1/1/2009 with a regionalaverage of 0.13. Conclusion Finding of the present study indicate an increasing trend in the range of remote sensing indicators. The range of SAVI index is increasing, which means that the density of vegetation in the Wetland is decreasing. Perpendicular Soil Moisture Index values also show an increasing trend, indicating a decrease in soil moisture content. As a result of the decrease in soil moisture, the vegetation density also has decreased and the land surface temperature has increased. Results of statistical tests indicate the role of changes in environmental conditions of Hour-al-Azim wetland in the frequency of dust storms. Using findings of the present study, or studies such as Kim et al. (2017), it is possible to take advantage of soil moisture variations for the prediction of dust generation, its emission, and spread level.
Ahmad Rashidinejad; Morad Kaviani Rad; Afshin Mottaghi
Abstract
Introduction According to the United Nations, two out of every three people in the world will face “water stress” by 2025. This estimate is based on the premise that the world’s annual population growth (80 million) requires 64 billion cubic meters of more water. Presently, 700 million ...
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Introduction According to the United Nations, two out of every three people in the world will face “water stress” by 2025. This estimate is based on the premise that the world’s annual population growth (80 million) requires 64 billion cubic meters of more water. Presently, 700 million people in 43 countries of the world are not far from the water stress threshold (1,700 cubic meters per year). As an important economic resource, transboundary water resources are considered to be an influential factor in territorial disputes. Uneven distribution of rainfall and the distance between water resources and catchments and human settlements have also increased concerns in this regard. Territorial disputes over water resources have a long history, and the first war in which water resources have played a significant role is estimated to have occurred 4,500 years ago. Nowadays, 263 transboundary river basins play a vital role in the relations among 151 riparian states. Transboundary water conflicts often occur due to overexploitation of water in the upstream and a decrease in the amount of water flowing to the downstream countries and sometimes a decrease in the water quality due to water pollution in the upstream. Conflicts over the quality of water resources can usually be resolved through the cooperation of the riparian states. Nonetheless, water scarcity and conflicts over the volume of water in these resources are difficult to resolve and many of them are considered to be a threat to the riparian states. This may be in part due to the problems in international laws. Currently the international law lacks decisiveness in the issue of water distribution and one-third of the world’s rivers are subject to local and regional agreements. However, asymmetry of power between riparian states is often the main problem hindering the process of resolving disputes through mutual cooperation. It is often assumed that if the upstream country is stronger than the downstream countries, reaching an agreement will be more difficult. In such a situation, the upstream country sees water as a tool to achieve its goals. However, the avarice of countries like Israel in the downstream of the Jordan River or Egypt in the downstream of the Nile River shows that what is hindering an agreement is not only an “upstream” position, but also a “hydro-hegemonic” position. In other words, a country may be geographically located in the upstream of a river, but this does not necessarily result in its hegemonic dominance over downstream countries since it may be geopolitically weaker or international agreements may not grant dominance to this country. In other words, hydro-hegemonic structure of a region only form when a country can exercise its leadership not only through “compulsion” but also through other material and immaterial sources of political power. According to “Zeytoon” and “Warner”, hydro-hegemony is superiority along a river basin created through the strategy of controlling water resources. This strategy is executed through threatening and pressurizing, signing agreements, and building infrastructure, which due to the weakness of international institutions enable the stronger country to have a larger share in water resources. This implies that infrastructure facilities such as dams not only have physical and economic benefits, but also are considered to be hydro political tools with the potential of changing the structure of hydro-hegemony and hydro-political relations. Method The present study uses the above mentioned definition of hydro-hegemony to examine “construction of infrastructure facilities” in Ethiopia (Renaissance Dam), and scrutinize the role of this hydro-political tool in changing the hydro-hegemonic structure of the region. To reach this aim, a descriptive-analytical methodology is used and data collection is performed using library research method. Results Findings indicate that with the increase of material power (economic and military power), anti-hegemonic mechanisms applied by Ethiopia in the Nile catchment have also increased. Along with the stability and political-economic development of Ethiopia over the past decade, the Egyptian revolution in January 2011 and subsequent internal instability have served as an opportunity for the implementation of the Ethiopian hydropower projects. It should be noted that having the highest military capacity, economic dominance, and political power in comparison with other low-income countries such as Ethiopia, Sudan, Rwanda, and Tanzania, Egypt has been able to supply its needs from the Nile and deny upstream countries of their rights to build projects which may affect its share of this river for decades. This situation can be described as Egyptian hydro-hegemony. Actually, Ethiopia was unable to take advantage of its geographical position in the upstream of the Nile River and the Horn of Africa due to ongoing conflicts, poverty, and distrust. However, recent changes in foreign policy, increased attention to domestic issues and economic growth have made it possible for this country to solve its domestic issues and use its geographical position. Conclusion Findings of the present study indicates that Grid Construction Project can be considered as the beginning of the end of Egyptian hydro-hegemony and power asymmetry in the Nile basin. Some scholars even consider this project as a step towards more equitable shares of the Nile Basin and regional integration. Inspired by a hydro-hegemonic framework in which asymmetric power relations along transboundary rivers are closely examines, these scholars see the Renaissance Dam as a successful case of anti-hegemony resulting in the development of a fair regime in the Nile Basin.
Leyla Karami; Seyed Mohammad Tavakkoli Sabour; Ali Asghar Torahi
Abstract
Extended Abstract
Introduction
Vegetation is considered to be one of the most important elements in all major ecosystems on the Earth. Thus, a proper understanding of vegetation and its growth trends and other environmental factors has always been of particular importance for environmental research. ...
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Extended Abstract
Introduction
Vegetation is considered to be one of the most important elements in all major ecosystems on the Earth. Thus, a proper understanding of vegetation and its growth trends and other environmental factors has always been of particular importance for environmental research. Estimating vegetation phenology parameters (VPPs) requires continuous NDVI data collection over a specific period of time. However, soil moisture, cloud cover, and particulate matter may affect the energy reflected from the vegetation cover and result in noisy images or erroneous data. Vegetation phenology parameters cannot be extracted from raw data due to the presence of random errors. These errors do not follow the phenological process and thus, overestimate or underestimate NDVI and fail to produce accurate results. Smoothing functions and especially the TIMESAT model are used to resolve this issue and eliminate errors in the NDVI time series. There is still no general consensus on which function acts more efficient and accurate in the TIMESAT model especially regarding the highlands. Naturally, each method yields different results in different regions, and thus it is necessary to compare and evaluate different functions used in the TIMESAT model and determine their accuracy in producing a continuous time series. The present study aimed to evaluate the performance of various functions such as asymmetric Gaussian (AG), double-logistic (DL), and Savitzky–Golay (SG) used to extract VPPs especially in mountainous regions.
Materials and Methods
TIMESAT model is a time-series analysis model based on remote sensing (RS) vegetation indices. It includes three functions: Savitzky–Golay, asymmetric Gaussian, and double-logistic, which are used to smooth collected data and identify outliers. Savitzky–Golay is an adaptive-degree polynomial filter (ADPF). The other two functions fit the information using nonlinear functions. These functions use unmodified NDVI data as input to produce modified and smoothed NDVI output. Four wheat farms in cold and warm regions of Khorramabad were used in the present study to investigate plant phenological behaviors and extract VPPs. The northern and eastern parts of Khorramabad have a cold climate, while the southern and western parts have a warm climate. One-year time series (2020) data of MODIS sensor was used in the present study. Using the infrared and near-infrared spectral reflectance values, NDVI was calculated in the Google Earth Engine environment. Errors of the NDVI time series were first corrected and a phenology curve was produced for wheat in both warm and cold farms. Asymmetric Gaussian, double-logistic, and Savitzky–Golay filter functions were also used to adapt the NDVI data. Following the reconstruction of growth curves in the time series of vegetation indices and smoothing the curve, various VPPs such as start of the season (SOS), end of the season (EOS), middle of the season (MOS), length of the growing season (LOS), base limit and value, maximum NDVI, vegetation growth season range, large seasonal integral, and small seasonal integral were extracted.
Results and Discussion
The model indicated that on average, beginning of the wheat growing season (SOS) in the warm regions of Khoramabad coincided with the 31.5th day of the year in the Gregorian calendar, whereas it happened on the 90th day of the year in the cold regions, thus indicating a 1.5-2 month difference between the beginning of the wheat growing season in cold and warm regions. The wheat growing season ended (EOS) on the 163rd day of year in the warm regions and on the 193rd day in the cold regions. In addition, in order to analyze the effect of climate on VPPs such as SOS and EOS, a comparison was made between the parameters obtained from farms in warm and cold regions. On average, the peak of vegetation growth has occurred in late March (Mar. 28, 2020) in farms of warm regions while cold regions experienced the peak of growth on May 20, 2020. In other words, warm regions have experienced peak growth approximately two months earlier than cold regions. Finally, the models were assessed and obtained values were compared with ground-based data collected in field surveys. Validation results showed that with an average RMSE of 2, Savitzky–Golay smoothing model reconstruct data more accurately as compared to asymmetric Gaussian, and double logistic function with an RMSE of 4 and 11, respectively. In other words, Savitzky–Golay estimates SOS and EOS with a higher accuracy and lower errors.
Conclusion
Findings indicate that Savitzky–Golay filter outperformed asymmetric Gaussian and double logistic functions in extracting VPPs in mountainous areas. Accordingly, it is suggested to use Savitzky–Golay in future studies aiming to investigate the phenological behavior of different vegetation covers in other Iranian highlands. The study has also showed that different climatic conditions within the study area affect plant phenological behaviors, which can lead to differences in SOS, peak of growing season, and EOS in different cold and warm regions of the province. Growing season of plants in cold regions of the province has occurred with an approximately two-month delay compared to the warm regions of the province.
Nemat Hosseinzadeh; Ali Reza Estelaji; Tahmineh Daniali
Abstract
Extended Abstract Introduction The growth and expansion of urbanization in the contemporary era and the emergence of metropolitan areas as places in which large number of people live together and capital and assets are accumulated have recently attracted the attention of many planners, governments and ...
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Extended Abstract Introduction The growth and expansion of urbanization in the contemporary era and the emergence of metropolitan areas as places in which large number of people live together and capital and assets are accumulated have recently attracted the attention of many planners, governments and nations topotential natural hazards and the importance of crisis management in these areas.In this regard, land use planning is considered to be critical due to its importance for sustainable development, optimal configuration, and crisis management. Materials & Methods The present study primarily seeks to design a spatial model for spatial evaluation of urban land use in district 19 of Tehran Municipalityusing a crisis management approach. In this descriptive-analytical study,necessary information were collected through library research methods and the analysis of quantitative and qualitative indicators.In quantitative index analysis, per capita land use of the district was compared to the country’s standard level, and in qualitative index analysis, three criteria of compatibility, capacity and desirability have been evaluated. One of the goals of urban land use planning is proper site selection for different land uses and separation of incompatible land uses from each other which is achieved through collection of necessary information about the current situation and evaluation of the collected information. For example, attempts are made to find a proper site forland uses producing pollutants such as smoke, odors, and noise away from residential, cultural, and social areas.In contrast, activities that complement each other are located in vicinity of each other. ArcGIS was used to evaluate and model the compatibility level of neighboring land uses. The proposed model inthe present study aims to evaluate the proximity of activities in order to determine their level of compatibility from the perspective of crisis management. Results of this model can be used for land use planning. This model is based on two principles: the logic behindland uses’ compatibility, and spatial neighborhood relationship and models of this relationship in GIS environment. Model Builder, a visual programming language at the Arc Info \ Editor Level which is undoubtedly one of the most important features offered in this program has been used to achieve the desired goal in this study. This modeler is actually an interface which forms the input-output parameters and processing functions in the processor. In this interface, the user can call several functions in a sequence and the processes will be performed one after the other. The input parameters includeeverysupported format in ArcGIS. Processing functions include all functionsused in the spatial analysis network. Outputs can be stored and used in later steps. Results & Discussion Qualitative analysis of land uses in District 19 of Tehran Municipality Evaluating the compatibility of land uses in District 19 In order to analyze the compatibility levelofneighboring land uses, the number of neighbors in each parcel is determined.Then,a binary compatibility relationship is stipulated for each pair and finally a fixed number is reached in the process of comparing land uses. As required by the land use compatibility matrix, urban uses are hypothetically classified into 5 groupsbased on their current situation: fully compatible, relatively compatible, indifferent, completely incompatible, and relatively incompatible. Following the production of compatibility matrix, details oflandusescollected during the field study have been analyzed and presented as maps. Then, the model is run in Arc GIS and the level of each land use’s compatibility is presented with anespecialcolor. Results indicate that except for Velayat park which is not compatible with the surrounding land uses, most of the incompatible land uses are located in the western and southwestern parts of the district. These incompatible land uses are presented with 5 different color ranges. Investigating the capacity of different land uses in district 19 of Tehran Municipality Qualitative analysis of accessibility zone in the capacity matrix In this matrix, the performance of each major land use in service provision and performance coverage is determined based on the urban population and its area of influence, and the results are presented in the relevant tables and on a map produced using Euclidean analysis in Arc GIS. The basic level of performance for each land use at the regional level and its area of direct influenceis identified based on the population required for standard performance of that specific land use in this area. This identified level of performance was used as the basis for further calculations. According to the proposed model and considering the accessibility zone, a special buffer zone is identified for each land use and its census blocks are determined. Finally,population within the blocks is determined separately for each land use (in this section, a few maps of buffer zones are provided for some land usesas an example). This model determines whether the rules of accessibility have been complied in different land uses. Based on the accessibility zone and censusblocks, decision making about the necessity of different land uses is made possible. Investigating the desirability of land uses in district 19 To reach the desired goal, a land use layerto which a new field of desirability has been added will be consideredaccording to the model (Figures 5 and 7) and the existing rules for specific land uses. Results are exhibited in two different classes (desirable, undesirable). According to the existing rules and maps, the desired parts of the area are marked in green and the undesirable parts of the area are marked in red. Conclusion As one of the most important tools and a major goal of urban planning,land use planning has a vital role in risk mitigation duringurban development. Thus, improving methods and processes of realizing this goal is of great importance and priority. Physical and functional characteristicsof land use have a significant effect on the number of casualties in different urban crisis. Therefore, land use planning is considered to be an important principle of urban planning and an urban planner is primarily expected to make the right decisions and to properly monitor land uses.On the other hand, crisis management and resilience approach have become a pervasive topic of debate in the present decade. Many researchers consider resilience to be the internal ability of a system, community or element to withstand the effects of a natural or social event. In order to determine the level of resilience, land uses in this area are investigated based on different aspects of crisis management. A major difference is observed between the findings of the present study and that of other researchers: most of dimensions, criteria or the main indicator in the present study are related to each other.The dimensions proposed in this model cover all physical and non-physical aspects and the proposed criteria or indicators also show important factors in each dimension. Moreover, the vulnerability of each dimension affects other dimensionsdirectly or indirectly. In fact, a district of Tehran municipality may be more resilient than other districts in some dimensions, but this does not suffice by its own and vulnerability in one dimension reduces the resilience of the whole district.Therefore, a resilient city or district needs to reduce its vulnerability in all dimensions and achieve resilience and crisis management in their real sense. One of the main concerns in the study of urban issues and urban planning is the issue of quantitative and qualitative analysis of the city and urban land uses. In the present study, an attempt has been made to perform quantitative index analysis of urban land uses under the topic of fair distribution of land uses per capita.And for the analysis of quality index, urban land uses were separately investigated based on their compatibility, capacity, and desirability level.This is another innovation of the present study which makes it different from other researches.In the discussion of compatibility,a model has been developed in ArcGIS environmentbased on the rules of urban planning to determine the compatibility of neighboring land uses. The highest level of incompatibility between neighboring land uses was observed in the western and southwestern part of the district. In terms of capacity, a model has been designed for existing uses in the area based on the standard accessibility zone. Regarding desirability, appropriateness of spatial conditions (slope, pollution, odor, location ...) and the land uses in a particular place have been considered as important criterion used to distinguish desirable and undesirable areas.The present studyinvestigates appropriateness of land uses based on standard slope. As previously mentioned, a model has been developed for each case in the GIS environment and the results are provided as a map at the end of each section. Following qualitative analysis, the most incompatible land uses were identified. Finally, the following solutions and suggestions are provided to improve and manage land use and for the managementof possible future crisis: Using empty spaces in the district and worthless lands in the southern and southwestern areas of the district to prevent the physical expansion and encroachment of the district on Tehran and Islamshahr. Considering a special zone around high-risk land uses such as gas stations and applying additional rules and regulations to prohibit increased density in these zones. Collecting physical and environmental data as much as possible, combining these data with each other, and using them statistically. Assessing earthquake risk and including the results in land use planning to mitigate risk and manage possiblecrisis. Distributingthe population in this districtbased on identified hazards in the area. Properly distributing parks and green spaces in the district, maintaining them for the times of possible crisis, ensuring easier access and equitable distribution among citizens. Increasing the quality of buildings in accordance with construction and urban planning standards, planning for the reconstruction and repairing of worn out buildings.
Aerial photography
Zahra Azizi; Mojdeh Miraki
Abstract
Extended Abstract
Introduction
Advances in computer vision and the development of remote sensing instruments have made indirect measurement of tree features possible. Individual tree crown delineation is an important step towards information collection and mapping trees in an urban area. This information ...
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Extended Abstract
Introduction
Advances in computer vision and the development of remote sensing instruments have made indirect measurement of tree features possible. Individual tree crown delineation is an important step towards information collection and mapping trees in an urban area. This information is then used to help planners design strategies for optimization of urban ecosystem services and adapt to climate changes. Common methods of Individual tree crown delineation (ITCD) were based on very high-resolution satellite or Light Detection and Ranging (LiDAR) data. However, satellite data are usually covered by clouds and thus, cannot be appropriate for the measurement of individual trees. Aerial Laser scanning is also relatively expensive. Remote sensing with unmanned aerial vehicle (UAV) captures low altitude imagery and thus, is potentially capable of mapping complex urban vegetation. Automatic delineation of trees with UAV data makes collection of detailed information from trees in large geographic and urban regions possible. Therefore, a multirotor UAV equipped with a high-resolution RGB camera was used in the present study to obtain aerial images and delineate individual trees.
Materials & Methods
The present study has compared the performance of Inverse watershed segmentation (IWS) and region growing (RG) algorithms using point clouds derived from Structure from Motion (SfM) algorithm and UAV imagery captured with the aim of tree delineation in Fateh urban forest located in Karaj. Region growing (RG) is used to separate regions and distinguish objects in an image. It starts at the initial seed points and determines whether the neighboring pixels should be added to the growing region. If the neighboring pixels are sufficiently similar to the seed pixel, they are labeled as belonging to the seed pixel. To implement the algorithm, the window size and the growing threshold were set for all resolutions. In order to obtain the most appropriate size for the search window, we examined different window sizes with a growing threshold of 0.5 for each resolution. Individual trees delineation was performed for each CHM resolution in the three different sites using "itcSegment" package of R software. Watershed segmentation algorithm is also similar to RG algorithm. The only difference is that it sets the growing seeds at the local minima. In other words, the local maxima in this algorithm change into local minima and vice versa. Inverse Watershed Segmentation (IWS) method was implemented in ArcGIS 10.3 because of its capability in delineation of distinct tree entities. In the summer of 2018, three sites with different structures including a mixed uneven-aged dense stand (site 1), a mixed uneven-aged sparse stand (site 2), and a homogeneous even-aged dense stand (site 3) were surveyed and photographed, and a 3D point cloud was extracted from the images. Then, the performance of algorithms was tested using a series of different canopy height models (CHM) with spatial resolutions of 25, 50, 75, 100, and 120 cm. To generate these models, digital surface model (DSM) was subtracted from digital terrain model (DTM). Results of individual tree delineation were validated using data collected in field observation of the aforementioned sites.
Results & Discussion
Results indicated that both RG and IWS algorithms yielded their best performance in the dense homogeneous structure. Moreover, the number of segments resulting from CHMs with low resolution was often much more than the actual number of trees. This was due to the occurrence of several peaks within an individual tree crown especially in low resolution images. With an F-score of 0.88, homogeneous even-aged dense stand (site 3) showed the highest overall accuracy in RG algorithm with a pixel size of 75 cm. Generally, results indicated that RG is an appropriate approach for individual tree delineation due to its flexibility in delineation of varying crown sizes. Furthermore, this method does not assume a circular shape for tree crowns and thus, is capable of detecting and segmenting irregular crowns. Generally, delineation of trees in urban forests using CHMs obtained from UAV-captured aerial imagery was highly accurate in homogeneous sites, while such models lacked efficiency in heterogeneous sites.
Seyyed Reza Ghaffari-Razin; Navid Hooshangi
Abstract
Extended AbstractIntroductionThe Earth's atmosphere (atmosphere) is divided into concentric layers with different chemical and physical properties. To study wave propagation, two layers called the troposphere and ionosphere are considered. The troposphere is the lowest part of the Earth's atmosphere ...
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Extended AbstractIntroductionThe Earth's atmosphere (atmosphere) is divided into concentric layers with different chemical and physical properties. To study wave propagation, two layers called the troposphere and ionosphere are considered. The troposphere is the lowest part of the Earth's atmosphere and extends from the Earth's surface to about 40 kilometers above it. In this layer, wave propagation is mainly dependent on water vapor and temperature. Unlike the ionosphere, the troposphere is not a dispersive medium for GPS signals (seeber, 2003). As a result, the propagation of waves in this layer of the atmosphere does not depend on the frequency of the signals. The delay caused by the troposphere can be divided into two parts of hydrostatic delay and wet delay. The hydrostatic component of the tropospheric delay is due to the dry gases in this layer. In contrast, the wet component of tropospheric refraction is caused by water vapor (WV) in the troposphere. The study of atmospheric water vapor is important in two ways: First, short-term climate change is highly dependent on the amount of atmospheric water vapor. Water vapor has temporal and spatial variations that affect the climate of different regions. Second, long-term climate variation is reflected in the amount of water vapor. Obtaining water vapor using direct measurements and water vapor measuring devices is a difficult task. Radiosonde and radiometers are used to directly measure atmospheric water vapor, but the use of these devices will have problems and limitations, for example, the maintenance cost of these devices is expensive and also these devices do not have a suitable station cover. The best way to get information about water vapor changes indirectly is to use GPS measurements. GPS meteorological technology can provide continuous and almost instantaneous observations of the amount of water vapor around a GPS station.Estimation of precipitable water vapor (PWV) and water vapor density using voxel-based tomography method has disadvantages. The coefficient matrix of tomography method has a rank deficiency. Initial value of water vapor must be available to eliminate it. Also, the amount of WV inside each voxel is considered constant, if this parameter has many spatial and temporal variations. In this method, the number of unknowns is very high and it is computationally difficult to estimate (Haji Aghajany et al., 2020). To overcome these limitations, this paper presents the idea of using learning-based models. To do this, in this paper, 3 models of artificial neural networks (ANNs), adaptive neuro-fuzzy inference system (ANFIS) and support vector regression model (SVR) have been used. Materials and MethodsDue to the availability of a complete set of observations of GPS stations, radiosonde and meteorological stations in the north-west of Iran, the study and evaluation of the proposed models of the paper is done in this area. Observations of 23 GPS stations were prepared in 2011 for days of year 300 to 305 by the national cartographic center (NCC) of Iran. Out of 23 stations, observations of 21 stations are used to training of models and observations of the KLBR and GGSH stations are used to test the results of the models. In the first step, the observations of 21 GPS stations that are for training are processed in Bernese GPS software (Dach et al., 2007) and the total delay of the troposphere in the zenith direction (ZTD) is calculated. It should be noted that for every 15 minutes, a value for ZTD is calculated using the observations of each station. In the second step, the zenith hydrostatic delay (ZHD) is calculated. By subtracting ZHD from ZTD, zenith wet delay (ZWD) are obtained. ZWD values are converted to PWV values. The obtained PWV values are considered as the optimal output of all three models ANN, ANFIS and SVR. Also, the input observations of all three models will be the latitude and longitude values of each GPS station, day of the year and time. Results and DiscussionAfter the training and achievement of the minimum cost function value for all three models, the PWV value is estimated by the trained models and compared at the location of the radiosonde station as well as the test stations. The mean correlation coefficient for the three models ANN, ANFIS and SVR in 6 days was 0.85, 0.88 and 0.89, respectively. Also, the average RMSE of the three models in these 6 days was to 2.17, 1.90 and 1.77 mm, respectively. The results of comparing the statistical indices of correlation coefficient and RMSE of the three models at the location of the radiosonde station show that the SVR model has a higher accuracy than the other two models. The average relative error of ANN, ANFIS and SVR models in KLBR test station was 14.52%, 11.67% and 10.24%, respectively. Also, the average relative error of all three models in the GGSH test station was calculated to be 13.91%, 12.48% and 10.96%, respectively. The results obtained from the two test stations show that the relative error of the SVR model is less than the other two models in both test stations. ConclusionThe results of this paper showed that learning-based models have a very high capability and accuracy in estimating temporal and spatial variations in the amount of precipitable water vapor. Also, the analyzes showed that the SVR model is more accurate than the two models ANN and ANFIS. By estimating the exact amount of PWV, the amount of surface precipitation can be predicted. The results of this paper can be used to generate an instantaneous surface precipitation warning system if the GPS station data is available online.
Saeed Varamesh; Sohrab Mohtaram Anbaran; Zahra Rouhnavaz
Abstract
Extended Abstract
Introduction
awareness of the type and percentage of land use and cover types is a fundamental requirement for understanding and management of a region. The growth of urbanization and increasing use of resources due to the development of the required facilities in urban life has changed ...
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Extended Abstract
Introduction
awareness of the type and percentage of land use and cover types is a fundamental requirement for understanding and management of a region. The growth of urbanization and increasing use of resources due to the development of the required facilities in urban life has changed the pattern of demand for resources and lands, changing the nature and quality of agricultural land, Historical and natural landscapes and surrounding urban areas through the transformation of these lands into residential areas. In recent decades, the suburban lands of cities have changed their use due to the urbanization process and the need of citizens for new residential areas and the surrounding lands, which are often high quality agricultural lands and gardens. This, along with things like industrialization and changing rainfall patterns, has destroyed the cover and natural environment of cities, and thus has posed many social and environmental challenges and endangered sustainable urban development, and as a result of this process, a lot of ecological pressure has been imposed on the natural ecosystem of the region. These changes are considered as one of the important and effective factors of social and environmental challenges. Today, remote sensing technology and GIS due to capabilities such as high monitoring power and resolution, frequent images, cost reduction, etc., To effectively identify and quantify land use changes and their effects on the environment and monitoring And rapid management of the growth and development of cities are used. In the present study, the aim is to evaluate the urban development of Ardabil in the last 30 years using remote sensing technology and satellite images.
Materials & Methods
Landsat satellite imagery was used to prepare land use maps for 1987, 2000 and 2017. In order to ensure the quality of data and bands, the images used in this research were first corrected for radiometric errors in ENVI 5.3 software environment. Then RVI, SAVI, NDVI, BI and IPVI indices were extracted. In the next step, maps related to filter texture, vegetation delineation and tasseled cap were prepared. At the end of this step, all the extracted layers were merged with the corrected image bands. Then satellite imagery using support vector machine algorithms, maximum similarity and artificial neural network with acceptable accuracy in six user classes (residential areas, covered agricultural lands, fallow, barren lands, urban forest and water) floor were classified. Then, to evaluate the classification accuracy, the overall accuracy and kappa coefficient were calculated for each of the maps.
Results & Discussion
According to the values of overall accuracy and kappa coefficient, which in 1987 for the support vector machine algorithm were 90% and 0.86, respectively, the maximum likelihood was 84.5% and 0.78, and the neural net was 90.5% and 0.87, respectively, in 2000. Overall accuracy and kappa coefficient for support vector machine algorithm 92% and 0.90, maximum likelihood 92.5% and 0.90 and neural net 92.6% and 0.90, and in 2017 overall accuracy and kappa coefficient for backup vector machine algorithm 90.6% and 0.88, maximum likelihood of 82.8% and 0.78 and for neural net were 88% and 0.85, it was found that the support vector machine algorithm has the highest accuracy compared to the other two algorithms. According to the results obtained from the study of satellite images classified by the support vector machine algorithm, the area of land built in Ardabil has increased from 20.023 square kilometers in 1987 to 41.554 square kilometers in 2017.
Conclusion
In general, it can be concluded that to evaluate the trend of urban sprawl and awareness of land use change patterns for optimal management and planning of cities, the use of satellite images, especially Landsat images is a suitable and low cost option. The results also showed that the rate of land use change to land uses is increasing and since land is the main element in urban development, so control how to use it and also calculate the real need of the city for land, to In order to provide different uses is effective. As a result, according to the findings of this study, in the absence of proper planning for this city due to favorable lands for urban development around the city, in the not too distant future, witness the destruction of agricultural lands around the city of Ardabil and conversion they will be residential areas.
Hamid Reza Ghafarian Malamiri; Hadi Zare Khormizi
Abstract
Introduction Investigation of vegetation changes can provide valuable information on global warming, the carbon cycle,water cycle and energy exchange. Satellite imagery timeseriesandremote sensing techniques offers a great deal of information on variations and dynamics of vegetation. Harmonic ANalysis ...
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Introduction Investigation of vegetation changes can provide valuable information on global warming, the carbon cycle,water cycle and energy exchange. Satellite imagery timeseriesandremote sensing techniques offers a great deal of information on variations and dynamics of vegetation. Harmonic ANalysis of Time Series (HANTS) has been effectively used to eliminate missing and outliers in time series of vegetation indices and land surface temperature (LST). However, the algorithm has been less frequently used to detect changes in vegetation and phenology. HANTSalgorithm decomposes periodic phenomena into their components(different sines and cosineswith different amplitudes and phases). The value of phases and amplitudes contains valuable information that can be used to investigate variations and identify different characteristics of vegetation such as growth and phenology. The present study aims to determine changes in each componentof vegetation time series in Iranin the past (1982, 1983, 1984 and 1985) and in recent years (2015, 2016, 2017 and 2018). Materials & Methods A daily NDVI product of AVHRR sensor, with a resolution of 0.05 at 0.05 ° (i.e. AVH13C1) was used in the present study. To obtain reliable harmonic components (amplitude and phase images), a reliable curve has to be fitted on the primary time series data. To do so, first,parameters of HANTS algorithm were determined and then Root Mean Square Error (RMSE) of the curves fitted on data related to four one-year time series in the past year’s category (1982, 1983, 1984 and 1985) and four one-year time series in recent year’s category (2015, 2016, 2017 and 2018) was estimated. This classification (i.e. four one-year time series in the past and recent years) was used for two reasons. First, extraction and comparison of harmonic components in a single time series in the past and recentyears’ categories cannot reflect real changes, as these changes may occur under the influence ofimpermanent dynamics of vegetation, such as dryor wet periods. Second, with four one-year time series in the past category (1982, 1983, 1984 and 1985), and four one-year time series (2015, 2016, 2017 and 2018) in recent years, statistical comparison of the harmonic components through one-way analysis of variance becomes possible. Following the production of reliable harmonic components, variations of the harmonic components in recent years were compared with their variations in the past using difference method, and mean difference of the harmonic components’value in four one-year time seriesin the past and present categories wasdetermined using one-way analysis of variance. Finally, some maps were produced to exhibitthe significance of differenceinmeans. Results & Discussion According to the findings of the present study, mean RMSE of the fitted curves in the four one-year periods ofpresent and past time series were always less than 0.1 unit of NDVI. Moreover, mean RMSEof total area of Iranin the past and present time series were 0.037 and 0.039, respectively. This demonstrates high efficiency of the HANTS algorithm in elimination of missing and outlier data in the daily-NDVI time series ofNOAA-AVHRR. Results indicate thatrange of zero amplitude (the mean value of NDVI or the average vegetation coverage) decreasesin the central, eastern and northeastern regions of Iran atthe 95% probability level (F-value <0.05), whileit increases significantly (F-value <0.05)in the north, northwestern and western regions (especially, the Alborz and Zagros mountains). The meandifferenceof phases value in the four-time series of the past and recent years’categories wassignificant at the 95% probability level (F-value <0.05). Compared to the past time series, first harmonic phase average of total area of Iran in the new time series has decreased by almost 14 degrees. This decrease in the value of the annual and 6-month phases indicates a quicker growth phase and phenological processes of plants compared to past times. Conclusion Results indicated that HANTS algorithm can effectively eliminateand reconstruct outliers in the NDVI time series. Zero harmonic (mean value) represents the overall level of vegetation cover and the firstharmonic phase in a one-year time series determines the starting time of growth in seasonal plants or thosewith agrowth period of6-month or less. Annual Phase indicates the angular starting position of the annual cycles and the 6-month phase inherently indicates the fluctuation and angular position of a half-year or 6-month curve. However, interpreting 6-month amplitude and phases are difficult. As most changes are controlled by the first harmonic phase, the first harmonic phase in a one-year time series contains important information about the beginning of growth and the phenological processes of plants. Therefore, harmonic components of a periodic time series canbeusedto identify and determine changes in vegetation coverage and phenological processes.
Hamid Panahi; Davood Amini; Ali Osanlu
Abstract
Extended Abstract
Introduction
To achieve sustainable security in Countries where security regards as a main concern, must implement land use planning programs in order of priority from the border to the interior. In land use studies, geography as a context plays a main role in the realization ...
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Extended Abstract
Introduction
To achieve sustainable security in Countries where security regards as a main concern, must implement land use planning programs in order of priority from the border to the interior. In land use studies, geography as a context plays a main role in the realization of codified plans and programs. All three vertices of the golden triangle of land management mean; Man, activity and space are influenced by the natural and human geographical features of the study area. Border zone planning is a type of planning that integrates border development with security and defense, based on the geographical characteristics of border areas, by establishing a link between development indicators and security plans, introduces strategies for sustainable development of border areas, that are bound to each other.
Security considerations are among those categories that have received less attention in macro-planning. In addition, awareness of the current situation is essential for any kind of careful planning for the development and progress of regions, especially in less developed provinces (Alipour et al., 2016: 159). The most important issues and problems in the formulation and implementation of planning in the country, include; Lack of attention to geographical-security considerations in locating the bases of law enforcement, border and military units, vital and sensitive centers and facilities, commercial, economic and communication uses. These issues have made political borders vulnerable to threats, military and terrorist attacks, border vulnerability to armed and opposition groups, border insecurity, dissatisfaction and conflict among border residents, poverty and underdevelopment, etc. in the country’s border areas.
Materials & Methods
The method of this research is descriptive-analytical and data analysis has been done with a quantitative and qualitative (mixed) analysis approach. To analyze the data, the method of contextual and basic theory (foundation data) has been used. In terms of method, this research is descriptive and survey based on field work, using open questionnaire, closed questionnaire and using SPSS and MAXQDA analytical software and Arc GIS. In MAXQDA software, it was proved that border management indicators are effective in security management, implementation and execution of security plans along the country’s political borders. After classifying the extracted indices, to examine the factor status of each of the indices under the relevant components through factor analysis in SPSS software, factors were classified into three categories. In order to analyze the status of application of selected indicators in the northwestern borders of the country, a questionnaire was designed and referred to the expert community was statistically analyzed.
Results & Discussion
Based on factor analysis; Thirteen border operational plans based on indicators Border planning was evaluated in the form of three factors that after reviewing the indicators: first factor; designing of ambush and anti-ambush operations in the border area is based on the shape of the land, the location of natural features in relation to the passages, the location of the escape routes and the connection points, the second factor; In the border monitoring and control planning, determining the location of telecommunication and communication systems in the region based on the situation of the repression points with enough view of the surrounding areas, the third factor; Determining the optimal routes for border patrols is based on the geographical realities prevailing in the border strip like land slope, distance to zero border, snowfall, flooding, etc., these three main plans were selected among the border operational plans influenced by border planning indicators in the northwestern borders of the country.
Conclusion
By analyzing the status of application of border management indicators in the implementation of plans in the border areas of the studied provinces, which was based on the Likert questionnaire and referring to the expert community, the status of the provinces was determined based on calculations and statistical analysis. Then, by summarizing the mean of the indicators based on which three provinces were examined, the status of the provinces was compared and ranked. Based on the results of statistical analysis, the first place is Ardabil province with an average of 3.92, the second place is East Azerbaijan province with an overall average of 3.64 and the third place is West Azerbaijan province with an overall average of 3.61.
Asyeh Namazi; Sayed Ahmad Hosseini; Sohrab Amirian
Abstract
Extended AbstractIntroductionAs a land use specially designed for physical activity, recreation and leisure, sports facilities are considered to be a public space vital for the society, improving health and well-being of the community. Therefore, special attention should be paid to the pattern of distribution, ...
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Extended AbstractIntroductionAs a land use specially designed for physical activity, recreation and leisure, sports facilities are considered to be a public space vital for the society, improving health and well-being of the community. Therefore, special attention should be paid to the pattern of distribution, easy access to these land uses, and spatial organization of these facilities in accordance with the pattern of road networks. Accordingly, the pattern in which sport facilities are distributed across urban areas can have a direct impact on the desired operational efficiency of the city. Therefore, optimal site selection and easy access to sports facilities are of great importance for a healthy city and a healthy community. A huge difference between per capita sports areas and the standard per capita or imbalanced distribution of sports facilities in the region may result in reduced interest in physical activities and threaten the health of individual and society. Accordingly, the present study has evaluated per capita sports spaces in Kashan, and the spatial distribution of these facilities. The average time required for accessing these spaces has also been measured in accordance with the local road network and the total area each facility serves. Finally, an optimal model has been proposed for sports related land use in Kashan. Materials & MethodsThe present descriptive-analytical study is applied in nature and uses ArcGIS and SuperDecisions software to analyze its descriptive and spatial data. To provide an optimal model, 11 indicators including area each land use serves, its quality, urban land use, population density, health centers, educational centers, distance from faults, distance from urban waterways, fuel centers, distance from industries, parks and green spaces were identified based on expert opinions. The importance of each indicator was also determined based on expert opinions using the ANP model, and weighted linear combination was used to combine the previously mentioned indicators in GIS. A brief summary of the models used are presented in the following section. Results and discussionThe nearest neighbor algorithm is used to evaluate the spatial distribution regardless of the total area of each sports facility. Results indicate the presence of a completely clustered distribution (P = 0.000 and Z = -3.368) at the level of 99%. Finally, the relative weight of each criteria is combined with the relative weight of each option obtained from ANP model using the weighted combination in GIS to reach an optimal model for site selection. The resulting value actually indicates the necessity of new sports facilities. In other words, higher values show higher priority and as it is shown, about 40% of the total area of Kashan is potentially appropriate for new sports facilities while about 60% of the city area is not suitable for such facilities. ConclusionOptimal site selection maximizes the efficiency of sports facilities and improves the quality of services for those using the areas. Therefore, the present study aims to evaluate the area each sports center is serving and provide an optimal model for site selection in Kashan. In 2016, Kashan had a population of about 304 thousand people and about 202 thousand meters of sports related land use. Thus, there was a 0.67 square meters per capita sports related land use in Kashan. Finally, 11 indicators were combined using the weighted combination to reach an optimal model. Results showed that about 40% of the total area of Kashan is potentially appropriate (relatively appropriate and completely appropriate) for new sports centers while about 60% of this urban area is not suitable for construction of such facilities. Moreover, results proves the efficiency of spatial statistics used to evaluate spatial distribution of land uses. As it is shown in the present study, GIS can provide an optimal model for site selection using practical indicators and appropriate data analysis methods. In general, results indicate that sports facilities in Kashan are not generally in a good condition in terms of per capita and distribution pattern which confirms the fact that these issues were not considered important in the process of site selection.
SHadman Darvishi; Karim Solaimani; Morteza Shabani
Abstract
Extended Abstract Introduction Urbanization is a continuous process and the spatial patternsof urban growth havealways played an important role in the transformation of human life throughout history. Urban growth has two dimensions: demographic and spatial, meaning that with increased urban population, ...
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Extended Abstract Introduction Urbanization is a continuous process and the spatial patternsof urban growth havealways played an important role in the transformation of human life throughout history. Urban growth has two dimensions: demographic and spatial, meaning that with increased urban population, the need for shelter increases and cities are faced with spatial growth. Expansion of cities in the spatial dimensions have several consequences,including changes in land use and land covers of areas surrounding cities.Land use change is currentlyone of the major concerns ofthe environmental approach, since land use changes in areas surrounding cities have led to changes in the economic structure of cities and the destruction of vegetation and agricultural lands as one of the main foundations of production in these areas. They have also seriously damaged other water resources, wildlife habitats, and resulted in the reduction of soil organic matter, changes in soil humidity and saltiness, increased energy consumption, increased urban heat islands, climate changes, as well as negative effects on the mental and physical health of urban residents. Nowadays, rapid growth in remote sensing technology and geographic information system, as well as the advancements in computer science and its application in environmental sciences and urban planning have created spatial modeling techniques such as Markov chain, Cellular Automata, intelligent neural networks and statistical models. Due to its dynamic nature, the capability of showing spatial distribution of land use changes, as well as its unique characteristics in modeling of natural and physical geographic featureson the ground and simpler adaptation with remote sensing data and GIS, a combination of Markov chain model and Cellular Automata are used as an important supporting toolfor decision making in urban planning and environmental sciences in many studies performedrecently. Over the past few decades, the population of Iranhas increased from 27 million in 1955 to 79 million in 2016. And according to the 2016census, 74 percent of the population lives in urban areas. In recent years, the population of Kurdistan province has experienced a 1.42% (2011 to 2016)average annual growth rate (especially in Baneh, Marivan and Saghez), which isaround 0.18% more than the average annual growth rate of the country (1.24%). Investigating census data shows that Baneh, Marivan and Saqezhave experienced a higher urban growth rate as compared to other cities in the province, and thus monitoring this growth and predicting its negative effects on the surrounding land use seems crucial.Destruction of vegetation and agricultural lands not only results in climate change, but also directly affect the lives of residents in the region. Therefore, understanding the growth rate is necessary for properplanning and managementofthese areas. Materials and Methodology Images received from Landsat in 1987, 2002 and 2017 were downloaded from the US Geological Surveywebsite and used in the present study. Google Earth images, land useand topography maps, and ground control points (GCP) were also used to perform imagepreprocessing, classification operations, and accuracy assessment. The study area includesBaneh, Marivan and Saqqez cities, which have recently experienced a high level of population growth. Considering the impact of population growth on increased rate of construction and physical development of urban areas, it is therefore necessary to study urban growth. In order to reduce the city’s impact on land use in future, it is necessary to modelurban growth. Using these models, planners can guide the urban development back to the optimal and appropriate routes and minimize the destruction of the land use.Image pre-processing in the present research was performed in ENVI5.3 environment. Then, using Maximum Likelihood algorithm, the images were categorized into five classes of water, residential areas, vegetation, agriculture and open spaces. Then, the overall accuracy of the classification maps was assessed using ground control points. To predict the urban growth, CA-Markov model was used in the IDRISI TerrSet software. Results and Discussion Findings indicate that the classified images have an accuracy of above 80%, and thus, land use maps of the study areas are valid.Investigations shows that the growth inMarivan and Baneh has most severely affected vegetation and agricultural land use. In the time period of 1987 to 2017, 897. 39 and 801 hectares of vegetation in Marivan and Banehhave been transformed into urban areas, respectively.During the same time period, 790.38 hectares of agricultural land in Marivan and 772.29 hectaresinBanehhave changed into urban areas. It is also important to note that unlike Saqez, the degradation of vegetation and agricultural lands in Marivan and Banehwas more severe than bare lands. In other words, bare landsinSaqez were more severely affected (as compared to vegetation and agricultural land), and about 1249,29 hectares of bare lands have turned into urban areas, while only 121.50 hectares of vegetation, and 509.04 hectaresof agriculture lands haveexperienced such a change.Also, results of the CA-Markov model showed that the growth of Baneh and Marivan cities in the 2017-2032 period will be in the Northeast and East directions, respectively. Results also indicate that this urban growth will affect agricultural and bare landsmore significantly. It is predicted that about 511.29 hectares of agricultural lands and 722.70 hectares of bare lands (in Baneh city) and 1080 hectares of agricultural lands and 2402.101 hectares of bare lands (in Marivan city) will turn into urban areas in this time period. Conclusion Based on the findings, it can be concluded that planning urban growth inthe study areas should be performed in a way that vegetation and especially the surrounding agricultural lands are preserved, and the negative effects of land use changesare minimized. Also,plannerscan apply the results of the present study in their future plansto guide the development of Baneh, Marivan and Saqeztoward optimal ways and reduce land use degradation.
Samira Afshari; Ali Lotfi; Saeid Pourmanafi
Abstract
Extended Abstract
Introduction
Industrial and economic developmentalong with population growth and increased exploitation of natural resources may upset the environmental balance. Inappropriate land use, along withpollution and destruction of natural resources are considered to be serious problems ...
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Extended Abstract
Introduction
Industrial and economic developmentalong with population growth and increased exploitation of natural resources may upset the environmental balance. Inappropriate land use, along withpollution and destruction of natural resources are considered to be serious problems caused by environmental imbalance in many parts of the world. These problems indicate the limited capacity of environment to resist human exploitation of land.
Industrial site selectionis considered to be one of the key factors in sustainable regional planning due to the different environmental impacts of industries. Because of the developmentin industrial areas and the existence of numerous mines in GolpayeganCounty, it is necessary to optimize industrialsite selection in accordance with environmental standards and regulations. Therefore, the present studyintegrates hierarchical analysis with multi-criteria evaluation methods to investigate 24 different criteria with the aim ofoptimizing industrial site selection in accordance withenvironmental standards and regulations in GolpayeganCounty.
Materials and methods
In accordance with the rules and regulations of setting up industrial and manufacturing units and similar studies,the conceptual model of Golpayegan county site selection was prepared based on three criteria: physical, biological and socio-economical. Followingthe preparation ofinformation layer for each criterion, spatial analysis ofEuclidean Distance was performed for each of them.
Then, information layers produced in the previous steps were standardized using Boolean and fuzzy logic. The integration and overlapping in Boolean method was performed using AND logic.
At this stage, all the information layers were entered into TerrSet software and standardized using fuzzy model and membership functions of the software’sfuzzy sets. The real scale (from 0 to 1) was used in this study to determine the membership function.Higher membership value in this range indicates higher utility while lower membership value indicates lower utility. In the present study, AND operator was used to integrate maps.
Hierarchical analysis was used to determine the weight of each factor. Afterwards, the maps were integrated using fuzzy overlay method, weighted sum model and weighted linear combination (WLC) method. In this way, a map was produced for the industrial park site selection. Then according to the histogram curve and its breakpoints and also according to the environmental conditions of the region, it was classified into 5 classes.
Results and Discussion
An inconsistency rate of 0.04 was calculated in the present study to evaluate the accuracy of judgments made about the weight of the criteria and sub-criteria.Distance from Mouteh Wildlife Refuge, distance from faults, distance from wells and distance from roadswere identified as the most important criteria for assessing the industrial capacity of the region.
Maps produced using the Boolean method include two classes of 0 and 1,the valuesin the fuzzy overlay, weighted sum and weighted linear combination methods rangebetween 0 and 1, while they range between 0 and 0.7 in the weighted sum method and between 0 and 0.8 in the weighted Linear combinations method.
2783.5 hectares of the study area have the potential of serving as industrial sites based on the Boolean method, indicating that 1.7% of the study area is suitable for industrial construction. Combining moderate, good and highlysuitable classes using fuzzy overlay method showed that 1769.13 hectares or 1.1% of Golpayeganregionare suitable for industrial site construction. Combining good and highlysuitable classes usingweighted sum method showed that 1758.77 hectares or 1.09% of Golpayeganregionare suitable for industrial site construction. Combining good and highlysuitable classes using weighted linear combination method showed that 1902.78 hectares or 1.18% of Golpayeganregionaresuitable for industrial site construction. No matter which method is used, suitable areas for industrial site constructionare located in the southeastern region of the County and in vicinity of the main road.
Conclusion
Comparing the results of the present study with similar studies indicates that the Boolean logic finds the least number of suitable areas for industrial park construction and its selected areas must have an appropriate score in all evaluation criteria.
Findings indicated that due to the specific characteristicsof the Analytical Hierarchy Process, this method can be useful in the investigation of regional planning issues.
It can be concluded that Weighted Sumand WLC are more effective than Boolean and fuzzy overlay methods.
Results indicate that all four models located landssuitable for industrial development in the southeastern areas of the County and in vicinity ofits main road, thus these areas should be prioritizedin future planning, policy making and investment for industrial development. Furthermore, given the concentration of agricultural activities in GolpayeganCounty and its numerous tourism capacities, the development of agricultural conversion industries and ecotourism related industries within the predicted authorized areas can be considered as priorities of regional development.
Nowadays, sustainable economic development in most countries depends on industrial development. Sustainable development of industries creates more opportunities for social and economic growth. Sinceappropriate site selection for industrial parksharmonize the goals of economic development with the goals of urban development, economic enterprises and environmental objectives, it is considered to be a step toward sustainable development. Achieving such a goal requires a revision of the site selection criteria in accordance with the sustainable development indicators. This increases national and local employment rate and accelerates industrial growth without damaging the environment.
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Afrouz Bagheri; Bahram Malekmohammadi; Banafsheh Zahraei; Amirhesam Hasani; Farzam Babaei
Abstract
1. Introduction Nowadays, changes in environmentaldynamics including changes in land cover, land use, water supplies and climate are considered to be challenging issues of human communities. Thus, it is especially important to investigate different aspects of land use change and their effects on the ...
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1. Introduction Nowadays, changes in environmentaldynamics including changes in land cover, land use, water supplies and climate are considered to be challenging issues of human communities. Thus, it is especially important to investigate different aspects of land use change and their effects on the past and future trends ofdifferent plains. Identification of previous changes and prediction of future trends help planners and managers to compensate for losses and avoid similar mistakes in future.Therefore, the present study is divided into two parts. In the first part, land usechanges of Lenjanat Plain in the 1990-2015 period are analyzed. In the second part, future land use changes (2015-2035) of the area are investigated.Adjustment coefficient is calculated to show the effect of land use changes on runoff coefficient. Materials and methods 2.1 Study area and its characteristics Lenjanat Plain is a sub-basin of Gavkhuni Wetland located in the central part of the Iranian plateau with the longitude of 51˚ 8' to 51˚45' E and latitude of 32˚2' to 32˚24' N. 2.2 Land use change In the first step, preprocessing of satellite data and preparation of the information were carried out through geometric and atmospheric correction of the digital imageswith the purpose of correcting errors, removing defects in the images and omitting system errors. Landsat-4 and 5, TM sensor, Landsat-7, ETM+ sensor and Landsat-8 OLI sensor were used to evaluate and predict land use changes in the study area. Image selection was performed based on the availability criteria, and Landsat satellite images were thus obtainedfor 1990, 2005, and 2015. In the next step, unsupervised classification was used to create a general understanding of land use classes in the study area as a useful tool for determining training samples. ENVI software was used to identify suitable training samples for classification. To realize the second goal of the study, Marco integration model and a cellular automaton model were used and future land use changes in Lenjanstudy area were predicted for 2035 based on the base map and the assumption that the current trend in land use changes will continue. For this purpose, the Marco and CA-MARKOV modules were utilizedin IDRISI SELVA. CA-Markov model was used to predict land use changes with spatial contiguity and spatial transitions over time. 3. Results and discussion 3.1 Measuringland usechanges Finall and use maps represent the percentage and spatial distribution of each landuse type in the study area in the past, and at present. These maps area also used to evaluate the effects of management on the intensity of land use changes in the study area. Man-made surfaces have almost doubled in the region and reached from 3922 to 7202 hectares. In the past, 3922, 22516, 81613 and 367 hectaresof man-made areas (such as residential and industrial), agricultural lands, barren lands, and riverbeds were located in the study area which have reached 7202, 17943, 82793 and 229 hectares, respectively. 3.2 Prediction of future land usechanges Land use types in 2035 were predicted using CA-Markov chain model. Results indicate that manmade surfaces will exhibit a rising trend and increase from 7,202 to 9,122 hectaresduring 2015-2035 period.To determine the compatibility or incompatibility of actual maps and modelingresults, model validation was performed. In this regard, land usesof the study area was predicted for 2015 through the aforementionedmodel and the predicted map was compared with the actual land use map in 2015. In this method, the Kappa index of 0-1 was used to interpret the results. 3.3 Adjustment Factor Before anything else, the present study have determinedland usechangespercentage. Then, runoff coefficient of the forecast period was divided by runoff coefficient of land use changes in the pastto calculate the adjustment factor.Based on the findings of this study and the land use changesforecasted forLenjanat plain in 2035, the adjustment coefficient for the region equals 1.051. 4. Conclusions The present study aimed to evaluate various criteria affecting the quantity of water resources. Moreover, it has evaluated and determinedadjustment factor. For this purpose, Lenjan plain was used as a representative of the plainsin the country. Five land use types, including man-made areas (such as residential and industrial), agricultural lands, Barren lands, riverbeds and rock beds were identified for 1990, 2005 and 2015. CA-Markov was applied to predict land use changes for 2035. Adjustment coefficient is also calculated to show the effect of land use changes on runoff coefficient
Hossein Asakereh; Skineh Khani Temeliyeh
Abstract
Extended Abstract
Introduction
As an influential element of climate, precipitation affects human activities and societies. It is thus considered to be the essence of any study conducted as a part of environmental and economic planning. Precipitation in Iran, especially in its west and southwest is ...
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Extended Abstract
Introduction
As an influential element of climate, precipitation affects human activities and societies. It is thus considered to be the essence of any study conducted as a part of environmental and economic planning. Precipitation in Iran, especially in its west and southwest is affected by thermal, dynamic, and thermodynamic low-pressure centers such as the Red Sea trough. The trough is an extension of Sudanese low-pressure with a central pressure of about 1006 hPa. The Red Sea is stretched in a southeast to northwest direction and thus connects tropical and subtropical regions. Considering the importance of the Red Sea low-pressure system for precipitation events in west and southwest Iran, any change in this system will affect precipitation patterns in the region. Analyzing the activity of this system and resulting precipitation in west and southwest Iran will thus provide more accurate understanding of the climate of this region.
Materials and methods
Environmental and precipitation data retrieved from Asfezari national database and atmospheric data (geopotential height) extracted from the European Center for Medium-Range Weather Forecasts (ECMWF) were utilized in the present study. A numerical algorithm was also used to identify the cyclones. The algorithm identified 459 cyclones in the statistical period.
Results and discussion
Time distribution of days in which the Red Sea trough is active showed increased activity in summer (198 days) especially August (99 days) and spring (178 days) especially April. However, the Red Sea trough showed decreased activity in autumn and winter. Activities of the Red Sea trough have shown a slightly decreasing but significant annual trend during the statistical period. A sharply and significantly decreasing slope can be observed in summer which results in a decreasing annual trend. Average daily precipitation of the study area in the statistical period ranged from 0 to 2.5 mm. The minimum average precipitation (less than 1 mm) was observed in 29.58% of the study area while maximum average precipitation (more than 2 mm) was observed in 3.64% of the study area. The largest part of the study area (66.87%) experienced an average daily precipitation of 1 to 2 mm. Moreover, 24.28% of the region with minimum precipitation (less than 1 mm) was located in the south and southwest of the study area. This indicates a relatively less severe impact of the Red Sea trough in this area. Around 70.88% of the study area has experienced a precipitation between 1 and 2 mm. Subtracting average daily precipitation recorded throughout the statistical period from the average daily precipitation occurring simultaneously with the activities of the Red Sea trough showed a positive anomaly (more than 0.4 mm) in the north and northeast of the study area. Therefore, it can be inferred that most of the precipitation in this area is originated over the Red Sea. It seems that the presence of the Zagros Mountains has also had a significant effect on precipitation in the study area. Areas with a negative anomaly (less than -0.4 mm) in which precipitation is not affected by the Red Sea trough include spatially scattered regions in Khuzestan, and Kohkiluyeh and Boyer-Ahmad provinces (0.74% of the study area). In other words, precipitation associated with the activity of the Red Sea trough was less than the total precipitation, and thus, most of the precipitation in these regions has other sources.
Conclusion
Results indicated that during the statistical period, minimum average daily precipitation has occurred in south, southwest, and northeast of the study area. Moreover, south and southwest of the study area experienced precipitation simultaneously with the activity of the Red Sea trough. The maximum precipitation in either cases (during the statistical period and also during the activity of the Red Sea trough) has been concentrated in parts of the northwest, west, and east of the study area (along the Zagros mountain range). Significant latitude difference between the north and south of the study area, and existence of the Zagros Mountains and consequently the heterogeneous topography have created two different zones in the study area experiencing minimum and maximum precipitation. In the presence of the Red Sea trough, a higher percentage of the study area experienced maximum precipitation. The frequency of days with more than one millimeter precipitation and their spatial distribution showed that under general conditions, the maximum precipitation has occurred in the north, northwest, west, and east covering 61.11% of the study area. Kurdistan province has recorded a maximum precipitation in more than 3500 days under the influence of different air masses. More than 73% of the factors associated with precipitation in Iran, especially in its northwest, west, and southwest are various synoptic systems (cyclones and short waves) entering the country from the Mediterranean with westerly winds. The minimum number of rainy days during the whole statistical period and also during the low-pressure activity of the Red Sea were also recorded in the southern and southwestern parts of the study area.
Geographic Data
Shahin Jafari; Saeid Hamzeh; Hadi Abdolazimi; Sara Attarchi
Abstract
Extended AbstractIntroductionHuman activities as well as environmental and climate changes affect the trends of wetlands. Detecting and monitoring aquifers are considered to be very important for evaluation of past, present, and future influential factors, and the findings of such studies are essential ...
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Extended AbstractIntroductionHuman activities as well as environmental and climate changes affect the trends of wetlands. Detecting and monitoring aquifers are considered to be very important for evaluation of past, present, and future influential factors, and the findings of such studies are essential for taking measures and making decisions based on the goals of sustainable water and soil resources management. Over the past decade, many researchers around the world have been attracted to remote sensing and especially satellite remote sensing and used this technology to detect such changes over time. The present study has used Landsat (monitoring the area of water body), TRMM (monitoring rainfall), MODIS (monitoring vegetation and evapotranspiration), Grace (monitoring groundwater) satellite images available in Google Earth Engine to study last two decades changes (from 2000 to 2019) in Maharloo wetland, Goshnegan catchment and their surroundings. Materials & MethodsMaharloo wetland is located in Fars province and Goshnegan catchment (426 square kilometers). The present study has used Landsat 7 and 8 images to extract the area of water body, TRMM images to obtain precipitation values, MODIS products to calculate NDVI and evapotranspiration, and data received from Grace to extract changes in groundwater level. These satellite images were available in Google Earth Engine. Mann-Kendall test was also used to assess the overall trend of the aforementioned factors. Results & DiscussionThe automated water extraction index was used in the present study to identify and estimate the area covered by water bodies in the study area. The largest area belonged to 2006 (216.76 square kilometers) and the smallest belonged to 2018 (66 square kilometers). In 2000 (the beginning of the reference period), an area of 216.52 square kilometers was covered by this wetland which is close to what was observed in 2006. In 2018, this has reduced to 66 square kilometers. Thus, there is about 150.72 square kilometers (69.54 percent) difference between these two years. In 2009, the total area has reduced to 66.67 square kilometers. A numerical comparison between 2000 and 2019 also indicates a reduction of 91.17 square kilometers (42% decrease) in the total area covered by this wetland. Also, a 53.72 square kilometers (29.60%) difference was observed between the average area covered by the water body in the first and second ten years. Since calculated p-value value (< 0.00001) is less than the alpha level (0.05), so a significant trend was observed in the average annual data of the area covered by this wetland. Kendall's tau also indicated declining trend of the collected data. Groundwater level was calculated using data received from Grace Satellite to investigate the role of groundwater level in reducing the area covered by the water body. Results indicated that since 2008, groundwater level have always showed a negative value (a decreasing trend). For an instance, a groundwater level of -10.86 cm in 2019 indicates a decrease in the water level in the study area. As the calculated p-value (< 0.0001) is less than the alpha level (0.05), so a significant decreasing trend was observed in the groundwater level. Results of Mann-Kendall test (-0.6) also indicated that changes in water bodies, vegetation, rainfall and groundwater level had a decreasing, increasing, increasing and decreasing trend, respectively. No significant trend was observed in evapotranspiration. It seems that the expansion of agricultural lands and subsequent water extraction from aquifers have intensified the decreasing trend of water bodies in this wetland. ConclusionWetlands provide many ecological services including water treatment, natural hazard prevention, soil and water protection, and coastline management (Amani et al., 2019). Therefore, understanding the importance of wetlands and their management need to be seriously considered by relevant organizations in different countries of the world, and Iran is no exception. Satellite data and remote sensing methods and techniques are considered to be one of the most important and cost-effective methods of monitoring wetlands. The present study used satellite data collected by Landsat, MODIS, Grace, and TRMM to monitor water bodies, vegetation, groundwater level, and rainfall in Goshnegan catchment in which Maharloo wetland is located. The results of Mann-Kendall test showed a decreasing annual trend for changes in the average area of this wetland. This decreasing trend is considered to be a serious threat to human settlements around the wetland which can intensify over time. It will also affect the thermal islands of Shiraz and Sarvestan in near future. Obviously, management of agricultural and forest land uses with the aim of stopping their increasing trend can improve water balance in catchment areas. A 132.2 ha (approximately 36.16%) difference was observed between the average vegetation cover in this catchment area over the first and second ten years (233.4 vs. 365.6 ha). It seems that the expansion of agricultural lands and subsequent water extraction from aquifers have intensified the decreasing trend of water bodies in this wetland. Due to the proximity of this wetland to the city of Shiraz and its importance as an ecological and tourist attraction, it is suggested that related authorities (Department of Environment and Water Organization) demarcate lake bed and riparian zone with the help of remote sensing researchers to improve the management of this wetland and prevent it from drying up. Also, it is suggested that the Organization of Agriculture Jihad review and improve water consumption methods and cultivation patterns in the areas surrounding this wetland.
Abbas Tajaddini; Zahra Sabzi; Ladan Zarif
Abstract
Extended Abstract Introduction Determining the landfill site for municipal waste is an important issue in the urban planning process due to its great impact on the economy, ecology and environment of each region. In the process of site locating, it is tried to consider areas with the least risks to the ...
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Extended Abstract Introduction Determining the landfill site for municipal waste is an important issue in the urban planning process due to its great impact on the economy, ecology and environment of each region. In the process of site locating, it is tried to consider areas with the least risks to the environment and human health and conservation. During the recent three decades, the production of municipal solid wastes has increased considerably, beside that their specifications has been changed meaningfully due to the change in people’s life style, progress of industrialization and world economies. Still, one of the best methods of waste disposal is waste dumping or burying. Optimized selection of landfill sites may minimize any negative environmental or financial effect. Searching various places to locate landfills requires choosing an appropriate method. Therefore, applying mathematical methods and determining the influence of different criteria the selection of a suitable place can be very useful. This subject was examined here for the city of Karaj, which is one of the Iran’s megacities with a fast and uncontrolled population growth and increase in waste production. Materials & MethodsIn this research, the indicators and effective criteria in locating the landfill of Karaj city were identified, evaluated and prioritized with a sustainable development approach using GIS and Fuzzy Analytical Hierarchy Process (AHP). The research data were collected through literature review, internet searching, and technical survey. Using fuzzy logic and decision making techniques based on expert opinions, it was tried to limit the gap in the research field. The current research is descriptive-survey, and functional. To carry out the research, at first, the major influencing criteria were identified. The criteria were categorized into five major groups of geotechnical, environmental, municipal developing, socio economic, and hydrological items. Afterwards, an initial survey was utilized to control the items, and then, a pairwise comparison questionnaire was designed to collect the expert opinions. The research population was 30 experts, adopted from academia, industry, and environmental engineering sector, that 27 of them were selected randomly to answer the questions. It was adequate according to the Cochran’s formula. To ensure the data collected were acceptable, the validity and reliability of the questions were examined sufficiently. Due to its simplicity and accuracy, the triangular fuzzy number was adopted to assess the descriptive variables. In continue, and based on the GIS analysis method, extra specifications of the potential landfill sites proposed were further examined. It was accomplished through categorizing the information layers, then by weighting the potential landfill sites according to the total scores obtained. The information layers included: geotechnical effect, ground slope, land use, permeability, being subjected to flood, water quality, water level, distance from the city, and distance from power transmission lines. Based on the influence level of these layers upon the landfill sites, they were categorized into four classes of highly suitable, suitable, relatively suitable, and unsuitable. For overall ranking, the score of each landfill site in each information layer was calculated by multiplying each layer score by its weight. After completion of this computation phase, all available information layers obtained their own scores, demonstrating their suitability level to be a landfill site. Using the ArcView software, the simple additive weighting method was utilised for site locating. Results & DiscussionThe results showed that the urban development criteria with a weight of 0.270 was the most important criterion in locating municipal waste landfill, followed by the environmental criterion with a weight of 0.226. Accordingly, the socio-economic criterion with a weight of 0.152 was placed in the last rank. Moreover, in the geological group, the fault index weighted 0.261 and the climatic conditions index weighted 0.236. In the environmental group, the surface water distance index weighted 0.201, and the landfill odor index weighted 0.172. In addition, in the urban development group, the land use index with a weight of 0.283 and the access to equipment and facilities with a weight of 0.258 were the most influencing items. The Inconsistency Ratio of pairwise comparison matrix (I.R) for all matrices was less than 0.1, which confirmed the compatibility of the components. Conclusion In the complementary analysis, using the Fuzzy TOPSIS technique and the Geographic Information System (GIS) and utilizing the simple incremental weighting method (SAW), it was determined that Nazarabad site and Halqe Dare new-site are the most suitable options for constructing a new landfill site.
Seyed Mehdi Yavari; Zahra Azizi
Abstract
Extended AbstractIntroductionLack of uniform light radiation on the objects, reduces the amount of contrast in the images and makes it difficult to extract image features. This problem destroys information about the behavior, shape, size, pattern, texture, and tone of the effects, and compresses the ...
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Extended AbstractIntroductionLack of uniform light radiation on the objects, reduces the amount of contrast in the images and makes it difficult to extract image features. This problem destroys information about the behavior, shape, size, pattern, texture, and tone of the effects, and compresses the image histogram in one or more specific areas. UAV images have been widely used in recent years due to their extensive coverage, high operating speed, use in hard-to-reach areas and up-to-date equipment. If drone images are correctly taken and pre-processed, they provide good accuracy for a variety of applications. The preprocessing is important since the image acquisition conditions cannot be changed in most cases so that the acquired images are contaminated with some distortions or errors which must be removed or their effect reduced to a minimum before any process. Improving the exposure in the image, which increases the amplitude of the histogram, can highlight features with similar gray-scale values, and this is useful in identification. Materials & MethodsIn this study, two aerial images have been used with a variety of vegetation, soil and man-made features using Storm 2 hexacopter drone in Simorgh city (Kiakla) in Mazandaran province with longitude and latitude 52⸰ 54' 1'' and 36⸰ 35' 49''. At first the SMQT algorithm is applied to the input images. So the bits number of the input image is calculated to determine the number of transmission levels. Then with rgb2gray command creates a gray image of the original image. The overall average of the image is calculated and the DN of each pixel is compared to the average. If the DN is greater than the pixel value, the number 1 is assigned to the pixel, otherwise the number zero in another image is assigned to the pixel. The average calculation and segmentation of pixels based on the number of bits continues, each segmentation is called a transfer. Then, by converting the data from these divisions into values in the spectral range of the image, a new image is created. This image has higher radiometric resolution than the original input image but lower spectral resolution. For this reason, the image is fused. Global gamma correction is applied to the fused image. Finding gamma in the image, especially local gamma is time consuming and complex for programming and computing. Therefore, to increase the computing speed, a local gamma of 0.7 was applied to the whole image and then the first step processes are applied again and finally, the SSIM index is checked for image enhancement.Results & DiscussionThe SSIM value for input image 1 and 2 is 0.8372 and 0.8401 while this value before processing was 0.4352 and 0.4161. Examining the histogram of the images before and after processing, in all three bands R, G and B, shows the stretch of the image histogram in the range of 0 to 255. There is a decrease in the number of peaks and valleys in the histogram of the processed images. The density function for input and processed images shows that the more homogeneous the number of effects in the image, the greater the slope of the function graph. The value of the density function has increased after processing, which is due to the stretching of the image histogram. SSIM is used to validate the results in this study. The images have been visually improved significantly, but this is not enough for verification. The goal of quantitative quality recognition is to design computational methods that can accurately and automatically express image quality, which affects all the image pixels in the same way. The SSIM range is between (+1 and 0). The closer the measured value for an image to one, the better image quality will be. SMQT also has less computational complexity and less configuration. If the image of a light object is formed in a completely dark background (such as night shooting), this algorithm does not work in the background pixels. Examining the image samples taken from a complication at night, it was found that the black pixels changed color to purple after fusion. In order to optimize the algorithm, it is suggested to increase the efficiency of the algorithm by examining the spectral behavior of different features in different color spaces and integrating their effective components in image or feature highlighting or the use of plant or soil indicators. The fuzzy method can also be used for semi-shady areas. These improvements should also prevent complexity of computing by increasing efficiency.
Asghar Hosseini; Zahra Azizi; Saeed Sadeghian
Abstract
Introduction LiDAR (Light Detection and Ranging) employs pulse models which penetrates vegetation cover easilyand provides the possibility of retrieving data related to Digital Terrain Model (DTM).Pulses sent by the Lidar sensorhitdifferent geographical features on the surfaceground and scatter inall ...
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Introduction LiDAR (Light Detection and Ranging) employs pulse models which penetrates vegetation cover easilyand provides the possibility of retrieving data related to Digital Terrain Model (DTM).Pulses sent by the Lidar sensorhitdifferent geographical features on the surfaceground and scatter inall directions. Distance to the object is determined by recording the time between transmitted and backscattered pulses and by using the speed of light to calculate the distance traveled by the small portion of pulses backscattered. Most LiDAR receivers at least record the first and last backscattered pulses. The first backscattered pulses are used to produce Digital Surface Models (DSMs) and the last ones are used to produce DTMs. Despite the fact that these data can provide a valuable source for DTM generation, the volume of vegetation (vegetation density) in forest areas reducesthe accuracyof DTMs. Onthe other hand, ground surveying of forest areas is rather expensive and time consuming, especially in largerforests. Aerial images are also used as a source for DTM generation, but this approach requires a 60–80% overlap between images which along with canopy height reduce the potential of this method for DTM generation. Also, low spatial resolution of satellite images collected from forest areas increases errors in DTM generation to a large degree. The present study investigates the accuracy and precision of DTMsproduced from LiDAR data in a forest area. Furthermore, the effect of different methods of filtering and DTM interpolation was explored. Different methods of DTM generation were also closely analyzed and evaluated. Materials & Methods The case study area is located in Doroodforests, a part of Zagros forests, in the southeastern regions of Lorestan province in Iran (48°51’19’’E to 48°54’31’’E and 33°19’21’’N to 33°21’15’’N). Minimum and maximum altitude above sea level were 1143 and 2413m, respectively. The study area covers 100 hectares of mountains with an average slope of 38%. Approximately 50% of the area is covered by forests in which Brant’s oak (Quercusbrantii Lindley) is the most frequent species. LiDAR data were collected by the National Cartographic Center of Iran (NCC) in 2012 using a Laser scanner system (Litermapper 5600) fixed on an aircraft flying at an average altitude of 1000m. LiDAR data consisted of the first and last returns (backscattered pulses), distance and their intensity value. Collected data had an irregular structure and included an average of more than four points per square meter. A DTM was produced using a two-step filtering. First, a morphological filter removed most of non-ground points, and then a slope-based filter detected remaining points. Inforest areas with rough-surface, DTM was producedthrough processing ofLiDAR data with statistical methods likekriging and inverse distance weighting (IDW). These methods apply third and fourth power to detect and remove non-ground points. To assess the accuracy of DTMs produced by different approached, 5 percent of the LiDAR point cloudswererandomly separated as the test data. Amongst these data sets, 62 points with a suitable dispersion were selected and measured using a GPS-RTK. An error matrix, along with accuracy indices (including correlation and Root Mean Square Error (RMSE)) were calculated based on these data. Results & Discussion Results indicated that 44-degree slope is the best threshold for isolation of non-ground points and inverse distance weighting (IDW) is the best third power interpolation method with the highest correlation (0.9986) and the lowest RMSE (0.204 meter). Amongst the filtering methods, slope-based filter used for separation of ground and non-ground points had the best performance. Since this filter combines two parameters of slope and radius, it can remove cloud points related to the vegetation cover and results in high efficiency for steep forest areas. Slope-based filter is suitable for processing of near-surface vegetation, whilst statistical filter is well-suited for vegetation cover consisting of tall trees. Conclusion The present study proposed and investigated different scenarios for the production offorest areas’ DTM using LiDAR data and two interpolation methods. These algorithms were practicallyassessed using LiDAR data collected from Dorood forest areas. The best scenario was slope-based filter with inverse distance weighting (IDW) interpolation. Based on accurate assessment, this approach can produce reliable DTM in forest areas.
Farzaneh Sasanpour; Fateme Mohebbi; َAmir hosein Kazem
Abstract
Extended Abstract
Introduction
Floods are natural hazards that cause a lot of financial and human losses every year. Flood zoning plans contain basic and important information in the study of development projects in the world, sobefore any investment or implementation of development plans, they should ...
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Extended Abstract
Introduction
Floods are natural hazards that cause a lot of financial and human losses every year. Flood zoning plans contain basic and important information in the study of development projects in the world, sobefore any investment or implementation of development plans, they should be reviewed by the relevant organizations. The Taleghan River has faced numerous floods over the years,however, no comprehensive studies have been conducted regarding the damage caused by the flood of Taleghan River and its zoning. Taleghan town, which is the main population settlement in the region, the river passes through and the construction of residential and commercial buildings along the river, is expanding. By Using the ARC GIS software,Taleghan most affected areas by flood risk have been determined in the form of a zoning map. Flood risk zoning map has been preparedby using FuzzyVIKOR method, determining the weight through the critic for 7 effective criteria in evaluating flood zones including: altitude, slope, slope directions, land use, geology, distance from waterway and average rainfall. The results of this study, which has been prepared in five categories, show that 83% of the total area of the basin includes safe or low-risk areas. However, 17% of its lands have moderate and high flood risk, which includes areas around the main waterway and sub-waterways with residential and agricultural uses in the basin. Therefore, in order to reduce floods,in low and medium slope lowlands of Taleghan River, in development of rural urban uses in the region, it should be implemented.
Materials and Methods
The present research is descriptive-analytical in terms of method and applied research in terms of purpose. Many factors must be considered in flood zoning, with different degree of importance. In this study, based on previous experiences, the factors that had the greatest impact on flood occurrence in the Taleghan watershed were selected in the VIKOR Fuuzy model. The data used in this study include sea level elevation, slope, slope directions, average rainfall, distance from waterway lines, land use and formation, which were used to determine areas vulnerable to floods.Some part of the required data including Digital Elevation Model (DEM), land use map of the region and map of geological formations have been collected in raw form with a shape file format in the scale of 1: 250,000 from the rangeland and watershed management department of the Faculty of Agriculture and Natural Resources, University of Tehran. Elevation, slope and geographical aspect, maps were extracted from DEM 10 m. The layer of waterways, including permanent canals and rivers, was provided by the National Forests, Rangelands and Watershed Management Organization. The map contains same rain line that is received from the Meteorological Organization. The raster map of the average precipitation of the basin that was prepared based on the information of the precipitation rain lines and the statistics of rainfall data related to 5 stations of Dizan, Ciancranchal, Gotehdeh, Jostan, Glird, Armut and Zidasht, using the Interpolation technique. The criteria were normalized after preparing the maps (GIS READY) and applying the required edits such as defining the unit coordinate system for the maps, eliminating the errors that occurred during digitization and reducing the descriptive data by adding a new column to the related descriptive information table.
In all of the maps thatwere converted from Vector format to Raster, after the normalization step, the layers were weighed through the Critic method. Using the VIKOR model and the weights obtained by the Critic method, which were calculated in Excel software, the value of the VIKOR index (Q) was obtained for every option (pixel). Finally, the ultimate map of flood risk zoning in Taleghan watershed resulted from assigning the values of VIKOR index (Q) obtained from the previous step for every relevant point (option), by ARC GIS software.
Results and discussion
The results of flood zoning map show that 83% of the total area of the basin includes safe or low risk areas. However, 17% of this area has a moderate and high flood risk, which mostly includes urban, rural settlements, orchards and agricultural lands, which shows the importance of paying attention to proper management in these areas. According to the results, it can be said thatthe distance from the waterway in Taleghan watershed has had a significant effect on the amount of flooding, so by moving away from the main waterway and sub-waterways of the basin, the risk of floods and flooding can be reduced. The results of the terming flood risk zoning, show that 27 villages and settlements out of 68 villages in the region are in high-risk areas, including the villages of Eskan, Gotehdeh, Narian, Prachan, Mehran, Joostan, Nisa Olga, Hasanjoon, Jazan, and Mochan are at the highest risk.
Conclusion
It has been proved that Multi-criteria decision analysis methods in GIS is a robust approach to generating risk maps with acceptable accuracy. The judgment about the acceptabilityof the model can be made byusing external information from real ground data. In this study, relatively high compliance with the final zoning map was obtained by checking the history of floods in the study area.
Ali Akbar Anabestani; Hedayatollah Noori Zamanabadi; Masoumeh Mollanorozi
Abstract
Extended Abstract
Introduction
Evaluating the ecological capability is so important that if the selected land lacks the appropriate ecological potential for the implementation of a specific land use, implementing the plan (even if there is a socio-economic need for that specific land use) not only ...
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Extended Abstract
Introduction
Evaluating the ecological capability is so important that if the selected land lacks the appropriate ecological potential for the implementation of a specific land use, implementing the plan (even if there is a socio-economic need for that specific land use) not only does not improve the environmental status of the region, but also causes more environmental damages. As an economic activity that somehowsells the natural and cultural heritage of different regions, and depends on the natural environment and its exploitation, tourism is one of the most important environmental potentials. Therefore, tourism is considered to be a path to sustainable development, which through its multidimensional nature not only meets the needs of tourists, but also creates major changes in the systemof the host society. Consequently, in order to achieve sustainability, tourismshould be planned in a way that it does not negatively affect the environment, economy and culture of the host societyand meets the needs of the current generation without overusing what also belongs to the next generations.
Materials & Methods
The present studywas applied in nature and took advantage of a descriptive-analytical method to study the parameters in two main sub-sections.The first part included a library research performed with the aim of investigating related theoretical literature and the research background.The second part included some interviews and a field research performed for data collection. To evaluate the regional environmental capability and overlayingmaps in ArcGIS environment, Weighted Linear Combination (WLC) methodand Fuzzy operatorswere used. First, the final map of ecological capability for the development of sustainable rural tourism was analyzed and evaluated using WLC method based on highly appropriate, appropriate, limited appropriateness, inappropriate, and highly inappropriate classes. Then, fuzzy maps were produced with a gamma value of 0.7, 0.8 and 0.9 to obtain the tourism capacity of the region. And finally, the Kappa coefficient was used to compare the accuracy of classifications obtained from the WLC and fuzzy methods.
Results & Discussion
Findings indicate that with a weight of 0.33,tourism resources are the most important factor or capability in the development of sustainable rural tourism in Neyshabur County. The topography, with a weight of 0.192 is considered to be the second most important factor according to the experts and specialists. The third most important factor is the land cover with a weight of 0.138 and then, climate criteria with a weight of 0.117, hazards with a weight of 0.088, socioeconomic factors with a weight of 0.084 and water resources with a weight of 0.051 had the highest scores. Finally, the scores were applied to the GIS environmentusing the WLC method, and the final map of land capability for sustainable rural tourism in Neyshabur County was obtained.
Also, the statistical information obtained from the final map of land capability shows that 27.27% of the area is located in the very appropriate class, and31.76%is located in the appropriate class, while 22.23% and 4.28% of the region belongs to the highly inappropriate and inappropriate classes respectively.In the next step, tourism capacity maps of the region were prepared using a Fuzzy model with 0.7, 0.8 and 0.9 operators. The study area was divided into five categories: very high, high, medium, low and very low in terms of tourism capability.
The last and the most important step was to find the most accuratemap from those produced using AHP and fuzzy methods with different gamma values of 0.7, 0.8 and 0.9. To reach this aim, field observations and interviews with experts and specialists ofthe field were performed. Therefore, results obtained from the maps were compared with the experts’ opinions. Findings indicates that the operator with a gamma value of0.7 and a kappa coefficient of 0.84 is considered to bemore reliable than the operators with a gamma value of0.8, and 0.9 and AHP model. Thus, the 0.7 gamma operator is considered to bethe most suitable model for environmental capabilityassessmentin the region regarding tourism.
Conclusion
Using natural capabilities and potentials is the most cost-effective and lucrative way to achieve sustainable development. Findings of the present studyindicated that the operator with a gamma value of 0.7 and a Kappa coefficient of 0.84 is considered to be the most suitable model for the assessmentof the region’senvironmental capability for the development of sustainable rural tourism and it is more reliable and appropriate than the AHP model and operators with a gamma value of 0.9 and 0.8.Finally, considering the capabilities and potentials of the Neyshabur County for the development of sustainable rural tourism, it is recommended to consider development of tourism in this county as the priority of rural development plans and to use the natural resources of the area especially in the appropriate and highly appropriate classesas a way to achieve sustainable tourism development of the county in the most cost-effective way. It is also suggested that with appropriate management, planning and using the ideas of academic researchers to improve the capabilities of theaverage class, we can make the most out of the potentials of this area to develop sustainable regional tourism.
Amer Nikpour; Hamid Amoniya; Sahele Shokri
Abstract
Extended Abstract
Introduction
Sprawl is the process of rapid population growth and spreading of urban developments on undeveloped land near a city with a direct impact on the spatial development which in recent years has become one of the major challenges of cities around the world. Growing population ...
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Extended Abstract
Introduction
Sprawl is the process of rapid population growth and spreading of urban developments on undeveloped land near a city with a direct impact on the spatial development which in recent years has become one of the major challenges of cities around the world. Growing population trend and substantial changes in land use have made scientific and accurate planning a vital requirement for the management of this phenomenon. Accurate planning can help managers and spatial planners achieve sustainable urban and rural development. The present study seeks to enhance understanding about spatio-temporal processes of urban growth and development in Babolsar, identify general factors affecting the formation and spatio-temporal changes of the city and also inform managers and decision makers of the trends and growth patterns to help them in accurate planning, designing and managing. In order to achieve these goals, detailed information about the physical structure of the region in different time periods are collected, changes and spatial dispersion of the study area are observed, and information about the physical growth of the city is also obtained.
Material and Methods
The present study applies descriptive-analytical method to examine population growth and physical expansion of the city. After selecting the geographical area, satellite images captured in 1990, 2000, 2010 and 2020 were obtained from the US Geological Survey (USGS) web site. To calculate Shannon's entropy, the study area was divided into 25 regions based on the distance from central core of the city. Then, total area of each region and each zone (marked in each region for each period) were calculated. Thus, the necessary information was prepared to determine the trend of physical expansion and development of Babolsar city from 1990 to 2020. Shannon's entropy model not only has no limitation regarding the number of areas, but also has a high level of flexibility regarding the types of divisions used for the study area.
Results and discussion
These maps show that Babolsar has always grown both spatially and demographically from 1990 to 2020. The relative entropy of Shannon was calculated for each period and each region, and resulting coefficients show that not only is the rate of sprawl high in Babolsar, but it has always exhibited a sharply increasing trend during the last three decades especially from 2010 to 2020. Since examining expansion and dispersion require a careful consideration of population changes and trends, population of the study area was calculated for each year and its relationship with sprawl was examined. Findings indicate that sprawl has increased along with population increase. According to Holdern model and results obtained in the present study, population is the most important factor affecting physical growth of Babolsar city. It has played an especially powerful role from 1990 to 2000. Three main patterns of spatial development and sprawl can be identified in Babolsar: 1) strip or linear growth pattern spreading the city along the main transportation artery further away from the urban core. 2) Leapfrog development pattern which occurs when developers skip over land to obtain cheaper land further away from cities and thus create separately, singularly, discontinuously developed settlements. 3) Continuous low-density pattern developed due to excessive use of land for urban purposes along the outskirts surrounding the city. Gradual development in this pattern support infrastructure such as water, and energy and road network.
Conclusion
Studies indicate that sprawl in Babolsar city has had destructive effects on the environment and high quality agricultural lands around urban and rural settlements. Especial attention of Iranian society to its northern culture and the concept of "pleasure utopia" which has been assigned to the Southern Coast of the Caspian Sea are considered to be the most important reasons for urban sprawl in this city and other similar cities. Rapid increase in the number of villas built by indigenous and non-indigenous people has resulted in the destruction of high quality agricultural land and irreparable socio-economic damages. Currently, real estate trading, even in the villages of northern region, has not only intensified the sprawl, but also has changed and dissolved the traditional land use systems turning previous land owners into janitors. Other influential factors affecting sprawl in Babolsar and similar cities in the northern region of Iran include inefficient government policies in land and housing section, failure to meet the goals of urban and rural projects, population growth, real estate trade, development and construction codes incompatible with the realities of society, ambiguity in the laws and regulations governing construction within the legal limits of cities, lack of protection for government-owned land and properties, lack of proper supervision in construction projects.
Farshad Pazhooh; Farzaneh Jafari
Abstract
Extended Abstract
Introduction
Due to its specific geographical situation,Iranhas an especial precipitation pattern. In other words,despitehaving a precipitation equal to one-third of global average,Iran experiences a strong fluctuation in its rainfall regime. According to global classifications, floods ...
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Extended Abstract
Introduction
Due to its specific geographical situation,Iranhas an especial precipitation pattern. In other words,despitehaving a precipitation equal to one-third of global average,Iran experiences a strong fluctuation in its rainfall regime. According to global classifications, floods are considered to be among the most important natural disasters. In recent decades, humaninterferencesin the environment and improper management of land usehave resulted in increasing severity and higher frequency of these natural disasters (Abbas ZadehTehrani et al., 2010: 78). Extreme floodingcaused by climate changeshave resulted in severe damages in different parts of the world during recent decades and the effects of these changes are more significant in dry environments (Negaresh et. al., 2013: 15). Increasing urbanization and constructions has naturally reduced permeable areasin different basins. The resulting impenetrable surfacesare incapable of absorbing the rainfall, and consequently, the total volume of runoff in the city has increased (TaheriBehbahani and Big Zadeh, 1996).
Materials and methods
Two typesofground level data and data collected from higher levels of the atmosphere were used in the present study:
A) Precipitation data collected during the first ten daysof April 2019 by stations in Western and South Western Iran obtained from the Iranian meteorological organization.
B) Data collected from higher levels of the atmosphere including revised geopotential heights, sea level pressure, meridian and orbital winds, omega and especial humidityobtainedfrom the National centre for environmental surveys at Colorado, USA.
For synoptic analysis, environment to circulation approach was used to detect heavy rainfall peak periods and then their synoptic dimensions were reanalysed in the spatial range of 10 to 70 degrees north latitude and 10 to 80 degrees east longitude. Based on the analysis ofprecipitation data, April5th and11th,2019 were selected as having the highest rainfall resulting in the highest level of flooding and damage in the western and southwest regions of Iran.
Results and Discussion
On April 5th,2019 most regions of Iran have receiveda rainfall of more than 20 mm. The maximum levels of rainfall wererecorded in Koohrangstation(187 mm), Izehstationin Khuzestan (155 mm) and Yasoujstation(151 mm). OnlySistan and Baluchestan, Kerman and South Khorasan Province have experienced a stable situation without any precipitation on this day. However, on April 11th,2019, the highest level of rainfall has occurred inwestern stations of the country. The maximumlevels of rainfallon this day were recorded inNahavand and Tuyserkan stations (Hamedan Province) and Noorabad(LorestanProvince) with 126 and 122 mm, respectively. Central and northwesternregions of the country have experienced the next highest level of rainfallfollowing western regions. Figures 1 to 3 show a part of precipitation values in the western and southwestern regions of Iran during rainfall peak periods. Precipitations in more than 16 provinces in the western, southwestern, and central regions of the country have damagedagricultural, economic and social sectors. More than 45 people were killed in thesedays.The highest number of deaths and injurieshas occurred in Shiraz. In the western parts of the country, Poldokhtar and Mamoualn were most severely damaged. Moreover, heavy rainfall and floodinghave damaged 700 thousand hectares of agricultural land and resulted in 4600 billion USDlosses. In the construction sector, the country has suffered from 1,600 billion USD losses (Hamshahri Newspaper, 1398).
Conclusion
The present study have focused on synoptic and thermodynamic analysis of systems causing pervasive, heavy and hazardous precipitation onApril 5th and 11th in the western and south western regions of the country. The synoptic and thermodynamic analysis of maps indicated that the contrast between the influence of southern and western low pressure fronts such as Saudi Arabia, Sudan and the Mediterranean on the southwestern areas of the country and the cold high pressure frontover the Caspian Sea have caused a strong pressure gradientand formed a strong front condition over the country and the region under study at the sea level. In the middle and upper atmosphere, deep multiple amplitudetroughsformed over the North Pole passed through Russia as bipolar and low pressureblocks, cyclonic centressettled over the eastern Mediterranean regions and the eastern half of the trough formed as a result of blocking settledover the western and southwesternregions of the country. These have resulted in severe, and widespread negative omega and divergence of warm and humid southern weather over the country and the region.
Manijeh Ghahroudi Tali; Khadijeh Alinoori; Homa Rivandi
Abstract
1. Introduction Sabzevar plain is one of the areas facing subsidence phenomenon in Iran due to a sharp decline of groundwater table, development of residential areas over aqueducts or tectonics processes. The present study investigates the impact of these cases. Sabzevar County is located in a northwestern ...
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1. Introduction Sabzevar plain is one of the areas facing subsidence phenomenon in Iran due to a sharp decline of groundwater table, development of residential areas over aqueducts or tectonics processes. The present study investigates the impact of these cases. Sabzevar County is located in a northwestern plain in Khorasan on the hillside of Jogatai Mountains. Rapid agricultural development and increased water demand in recent decades have resulted in annual groundwater harvesting of about 400 million cubic meters and an annual deficit of about 30 million cubic meters in water reservoirs. The groundwater table in this plain annually experience an average decline of one meter. Despite increased precipitation in the last two years, only a 10 mm increased precipitation was recorded in Sabzevar station and the area still faces drought according to comparative analysis of rainfall. 2. Methodology Data used in the present study include 6 C-band single-look complex (SLC) images received from the ASAR sensor of Envisat. These images were captured during June, May, October, and December 2004 – 2008. Moreover, data including the groundwater table and the depth of water in local wells of Sabzevar County were collected from Khorasan Razavi Water Management Organization for the statistical period of 2003 – 2008 and 1974 – 2014. Data collected from local water wells and aqueducts were used to investigate subsidence. Following the geometric recording of the images, related interferograms were prepared. In order to calculate ground displacement, other effects were removed from the interferograms, and the effect of topography was corrected using the STRM digital elevation model (DEM) with a spatial resolution of 90 m to further improve the results. An adaptive filter was applied on the images to reduce the level of noise. In the phase correction stage, DEM produced through interferometry was used to correct the images and separate the deformation signal resulting in a differential interferogram. In order to estimate the groundwater decrease and study the resulting subsidence, the depth and groundwater level of 88 piezometers in Sabzevar were interpolated using the IDW method. Overlap methods were also used to investigate the relationship between the spatial distribution of subsidence occurrence and the location of wells, aqueducts, and faults. 3. Results Results indicates that the deformation of the area is the consequence of the high rate of subsidence in this short period of time. The maximum level of subsidence has occurred in the northeastern parts of the study area with a southwest-northeast direction starting from the hillside of Mish Mountain and moving with an increasing trend towards the hillside of Joghatay Mountain. Sabzevar and other cities of the county face an average subsidence rate of 10 cm per year. Images of displacement in the study area were obtained through interferometry and based on their overlap with subsidence. These images were then used for spatial analysis of aqueducts, wells, faults to study their impacts on subsidence. Results indicates that the subsidence rate has changed from 1 cm/year in 2007 to 14.6 cm/year in 2008. Active faults were also located in the western part of the study area across formations such as conglomerate, sandstone, red marl, and gypsum-bearing marls. Faults were generally developed perpendicular to the direction of subsidence indicating their role in downward displacement. Interpolation was performed for the 1974 – 2014 period to study long term consequences of this finding. Findings indicates that the decline in groundwater level has deteriorated moving from Sabzevar plain toward the surrounding areas. 4. Discussion and conclusion The study area was located on the hillside of Joghatay Mountain. Agricultural activities have developed in the area resulting in increased annual demand for water. Despite recent precipitations, the area still suffers from drought, decline in groundwater level, and subsidence. Results of a three-year interferometry selected from the period for which appropriate images were available have proved the occurrence of subsidence in the study area. A comparison between this image and the piezometric level in similar statistical years indicated the significant impact of groundwater level decline on subsidence. A comparison between the distribution pattern of faults, wells, and aqueducts and the subsidence area showed that a large number of wells were associated with subsidence, and the dominant faults were perpendicular to the surface of subsidence areas (Figure 1). Therefore, groundwater decline was the most important factor contributing to subsidence in this region, and long term piezometric level also have confirmed this effect. Faults perpendicular to the surface of subsidence areas might also intensify this phenomenon. In other words, further decline of groundwater table in the region will result in a higher rate of subsidence.
Mostafa Mohamadi dehcheshme; Fereshteh Shanbehpour
Abstract
Extended Abstract Introduction 21st century is the era of cities’vulnerability, since as urban life becomes more complex, ...
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Extended Abstract Introduction 21st century is the era of cities’vulnerability, since as urban life becomes more complex, cities face natural hazards and technological crises on the one hand and social-security crises on the other.Urban safety and security have long been a focus of urban planning, and planners have always been concerned about this important issue in the process of building and designing urban areas.Improving the security of critical infrastructures can play a key role in provision of better services and reduction of vulnerabilities, especially in times of crisis,Moreover, reducing the vulnerability of urban land uses by new crisis management approaches such as passive defense, which is one of the most important goals of urban managers can play a role in creation of a safe environment in cities and mitigationof damages. Materials & Methods The present research is theoretical-practical and descriptive-analytic in nature. For data analysis, the final weights of indices were determined using FAHP-GIS and then the neighborhood of each layer was identifiedusing the Distance tool. Afterwards, maps of the interval zoneswere overlapped usingFuzzy Overlay(gamma-0.9)of the Spatial Analyst Tools. Results & Discussion The findings of the present study on spatial analysis of critical infrastructure have indicated that: (A)The 2nd district of Yasujfaces the highest risk level, while the 3rd district faces the lowest level of risks. High concentration of critical infrastructures in the 2nd district and improper distribution of these infrastructures and organizations providing emergency servicesare the most important causes of risks in the city of Yasuj. B) None of the studied critical infrastructures and organizations providing emergency services in Yasuj are located in the very low risk zone. C) Only about 31% of the studied critical land uses are located in the low Risk zone. D) Spatial analysis of critical infrastructures in Yasuj has shown the lack of a logical balance in spatial distribution of these infrastructures. Therefore, ifa possible emergency situation damages a part of the city (the 2nd district as considered in the present study), the activities of many sectors will be challengeddue to the synergy and interoperability of the infrastructure. Conclusion The results show that 11 land uses or 45.83% of infrastructures with percent value of 0.19-0.1 are located in the high risk zone; 6 land uses or 25% of infrastructures with percent value of 0.20-0.39 are located in the relatively dangerous zone; 5 land uses or 20.83% of infrastructures with percent value of 0.40-0.59 are located in the medium risk zone, and finally, 2 land uses or 8.33% of the infrastructures with percent value of 0.60-0.79 are located in the low risk zone. None of the land uses in Yasuj are located inthe very low risk zone.
Behrooz Naroei; Shahindokht Barghjelveh; Hassan Esmaeilzadeh; Lobat Zebardast
Abstract
Extended Abstract
Introduction
The rapid expansion of urbanization along with irregular changes in land use and Landscape System of Tehran has disrupted the composition and distribution pattern of urban green infrastructure. The present study seeks to analyse the spatial-temporal changes of urban green ...
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Extended Abstract
Introduction
The rapid expansion of urbanization along with irregular changes in land use and Landscape System of Tehran has disrupted the composition and distribution pattern of urban green infrastructure. The present study seeks to analyse the spatial-temporal changes of urban green infrastructure in Tehran Landscape System affected by the spatial processes of land use changes in the statistical period (4 decades of 1990 to 2030). To reach this aim, the present study has identified (1) the effect of spatial processes on the changing landscape pattern and (2) the relationship between the spatial pattern and ecological processes of landscape and its influence on the capacities and constraints of green urban infrastructure.
Materials & Methods
The present study has focused on the landscape system of Tehran and its 22 districts as the study area. The descriptive-analytical study consists of following stages: 1) Classifying urban land uses in1990-2000, 2000-2010 and 2010-2020 statistical periods using Landsat satellite images: (in Envi 5.3, Google Earth and Arc GIS 10.2 software), 2) Modelling and forecasting land use changes in 2030 using integrated model of Markov chain, automated cells (CA-MARKOV) and TerrSetsoftware), 3) Determining spatial processes of landscape changes via decision tree algorithm. 4) Quantifying landscape metrics of composition and configuration of landscape pattern (green, open & built patches) at both class and landscape levels in the mentioned periods (in Fragstate 4.2 software).
Results & Discussion
Many environmental decisions presume that some types or composition of land use are preferred to others. It is assumed that the spatial arrangement of elements in a land-space mosaic controls its ecological processes. This proposition is known as the pattern/ process paradigm, and forms the central hypothesis of landscape ecology (a branch of science developed to study ecological processes in their spatial context). Ten spatial landscape processes are considered to reflect changes in various patterns of landscapes (aggregation, attrition, creation, deformation, dissection, enlargement, fragmentation, perforation, shift, and shrinkage). These processes actually change the spatial structure of urban landscape and affect the quality of ecological processes in Tehran Landscape System. To identify the spatial processes responsible for landscape pattern changes during a defined period of time, a decision tree algorithm was developed. Decision tree required the following input: area or size (a), the perimeter or edge length (p), and number of patches (n) in each land-cover class. The decision tree algorithm applied on Tehran Landscape System has indicated that spatial processes of 'attrition' and 'fragmentation' have led to a decrease in the integration of green and open patches in this landscape system. Measuring LSI and IJI metrics in 1990-2030 statistical period at the class level has also proved the previously mentioned finding. Increased ENN-MN and decreased PLAND of open and green patches during two periods of 1990-2000 and 2010-2020 due to the spatial process of 'attrition' have also showed this decreased integrity over time. These conditions have reduced the resilience of Tehran atmosphere and its capability to absorb air pollution and also have resulted in the recent development of thermal islands in different urban areas. Moreover, the COHESION metric has reduced in green and open patches due to the spatial processes of 'attrition' and 'fragmentation' at the class level. At the landscape level, the value of SIDI metric has also decreased from 1990 to 2020 and the same trend will continue according to 2030 forecast. Spatial process of 'aggregation' in constructed patches has resulted in a decrease of NP and PD at landscape level during 1990-2000 and 2010-2020. Findings indicate the effect of spatial process of aggregation on constructed lands (high-rise buildings) in the northern (such as District 1) and western parts of the city (such as District 22) which has interrupted wind movement and air purification in Tehran. The values of LSI and ED has also decreased at the landscape level due to the 'attrition' of open and green patches leading to a reduction in the heterogeneity order of urban landscape system. On the other hand, increased IJI value in 2020 and 2030 indicates increased turbulence in distribution and also increased fineness index of open and green patches in the landscape system of Tehran.
Conclusion
Findings indicate that spatial processes of 'attrition' and 'fragmentation' have resulted in a reduction in the number and area of green and open patches in the composition pattern and also decreased coherence at class level from 1990 to 2020. This has resulted in an unbalanced distribution of the patches in the configuration pattern of green urban infrastructure in Tehran. The spatial process of 'aggregation' has been repeated during the statistical period in the constructed patches. Data forecasted for 2030 shows the impact of 'attrition' on changes occurring in both green and open land use. The landscape is also getting more simplified due to the dominance of constructed land uses. Findings can be applied to determine a roadmap and plan the spatial pattern of urban green infrastructure.
Sayyad Asghari Saraskanroud; Imanali Belvasi
Abstract
Introduction
The sun is known as the source of energy, the origin of life, and the origin of all other energies. The global solar radiation is one of the fundamental structures of any climatic range. Hence, recognition of the features and the prediction of these basic structures have a great impact ...
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Introduction
The sun is known as the source of energy, the origin of life, and the origin of all other energies. The global solar radiation is one of the fundamental structures of any climatic range. Hence, recognition of the features and the prediction of these basic structures have a great impact on energy-related planning. One way to gainaccess to the solar energy information is the direct measurements of solar energy by measuring devices such as Pyranometer and Pyrheliometer Unfortunately, the measurement of the solar radiation is not always carried out in many parts due to the high cost, maintenance and the need for the equipment calibration. Remote sensing techniques can be an appropriate alternative to the experimental and old methods in this field due to the high accuracy and speed in predicting the net radiation values. In general, remote sensing models have a better performance in estimating solar radiation, and can be used as one of the suitable and low cost tools for estimating solar radiation. Considering the importance of solar radiation as a clean, availableand free of any environmental destructive pollutants, identifying the radiation areas to be introduced to the relevant authorities is essential and the aim of the research. In this research, it was attempted to study the feasibility of utilizing solar energy in the region of Alashtar County using the SEBALalgorithm and remote sensing technology.
Materials and Methods
To investigate and study the feasibility of using solar radiation energy, the Landsat-8 satellite images over a 12-month period of the year 2017, 1: 50,000 digital topographic maps of the Armed Forces Geographic Organization and the climatic data of the study area including temperature, precipitation, wind speed and the number of sunny days were used. The ENVI software was used to perform the calculations related to SEBALmodel and the ArcGIS software was used to implement the model. In this study, the feasibility of using solar energy in Salsala city was studied using SEBALalgorithm and remote sensing technology. In this method, the instantaneous values of pure radiation are obtained by measuring the sun’s incident radiation from the cloudless images and using surface albedo, surface emission and surface temperature. In this method, instantaneous values of pure radiation are obtained by measuring the sun’s incident radiation from cloudless images using surface albedo, surface emission and surface temperature. After calculating the parameters of the SEBAL algorithm, the net surface radiation flux was calculated.
Discussion and Results
The results showed that the average maximum short-wave radiation was 996 watts per square meter in June and the minimum was 460 watts per square meter in January, while the highest amount of net radiation in September was calculated to be 602 watts per square meter and the lowest amount in January was calculated to be 261 watts per square meter. Also, the highest percentages of net radiation distribution in the ranges of 0-200, 200-400, 400-600, 600-800 and 800-1000 watts per square meter were in August, November, April, September and June. The highest percentage of net radiation distribution was in the range of 600-800 watts per square meter with 69.86% of total net radiation in September and the lowest percentage was in the range of 800-800 watts per square meter in January.
Conclusion
In order to carry out the research, the Landsat 8 ETM satellite images for the 12 month period of the year 2017 were provided. But, since the images of February, March and December were completely cloudy, they were not used. Then the preprocessing operation in ENVI software was used on all bands of images. The amount of pure radiation in the study area was calculated in watts per square meter in January to November in ENVI software environment and by the utilization of SEBAL algorithm, using the prepared images (Table 2). The results of Table (2) show that the average maximum input shortwave radiation is 996 watts per square meter in June, the lowest amount input is 460 watts per square meter in January, the highest output long wave radiation is 539 watts per square meter in July and the lowest output is 391 watts per square meter in January. Finally, the highest amount of net radiation reaching the surface of the Earth was 602 watts per square meter in September and the lowest amount was 261 watts per square meter in January. The highest percentage of net radiation in the range of 600-800 watts per square meter was 69.86% in September 2017 and the highest percentage of net radiation in the range of 600-400 watts per square meter was 60.12% in January 2017.
The difference in the amount of net radiation reaching the ground in the study area is due to the difference in the angle of the sunlight and the number of sunny hours in different months of the year.
The results obtained from of the information in Tables 2 to 11 prove this fact. Also, given the sensitivity of the photovoltaic cells that are sensitive to the solar radiation from the radiation threshold of up to 1000 watts per square meter and receive them, it can be concluded that solar radiation in the city of Alshtar has the potential to implement the solar photovoltaic plans in 9 months of January to November.
Geographic Data
Ali Akbar Sabziparvar; Alireza Seifzadeh
Abstract
Extended Abstract
Introduction
Ultraviolet radiation (UVA) is a dangerous part of solar radiation that makes a small percentage of total solar radiation energy (5 to 7 percent). Despite the beneficial role of solar energy in the production of vitamin D3, it can cause irreparable damage to human cells. ...
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Extended Abstract
Introduction
Ultraviolet radiation (UVA) is a dangerous part of solar radiation that makes a small percentage of total solar radiation energy (5 to 7 percent). Despite the beneficial role of solar energy in the production of vitamin D3, it can cause irreparable damage to human cells. The majority of previous studies on ultraviolet radiation in Iran have focused on in-vitro impacts of UV radiation on human health and plant physiology in a limited study area. The present study estimates daily cumulative UVA radiation in central regions of Iran and compare it with total column ozone (TCO), cloud optical depth (COD) and aerosol optical depth (AOD) in different seasons.
Materials and methods
The present study estimates daily cumulative UVA radiation (320-400 nm) over a 13-year reference period (2005-2017) in a large area in Central Plateau of Iran with arid and semi-arid climate using TUV5 multilayer radiative transfer model (Madronich, 1993). 22 synoptic stations in 9 provinces were investigated in this study. Daily cumulative UVA radiation under three different sky conditions (clear-sky, overcast and real-sky) was also compared with geographical distribution of total column ozone (TCO), cloud optical depth (COD), aerosol optical depth (AOD) and surface albedo (SALB). Required data were extracted from satellite images (downloaded from http://disc.gsfc.nasa.gov) and Iran Meteorological Organization data center.
Results and Discussion
In general, maximum daily UVA radiation was recorded in the southern half of the study area. During warm seasons of the year, the eastern part of the study area (Kerman and Khorasan-e-Jonubi Provinces) and during the cold seasons of the year, central and southwestern part of the study area (Yazd and Fars Provinces) experience maximum daily UVA radiation. Maximum cloudiness in spring has occurred in northeastern and western parts of the study area and a lower level of cloudiness has always been recorded in its southern parts. Thus, the highest level of UVA radiation has been recorded in southeastern parts of the study area and especially in Birjand station (1071.12 kj/m2 per day). As expected, maximum UVA radiations in all sky conditions and all stations were recorded in summer. The lowest level of cloudiness was also recorded in this season. During autumn and in overcast condition, the highest concentration of UVA was recorded in southeastern parts of the study area and Birjand station (725.85 kj/m2 per day). This is consistent with cloud optical depth and total column ozone, and so, the lowest amount of ozone in this season was recorded in Birjand station (276.57 Dobson). The highest values of atmospheric aerosol with an average of 0.59 optical depth were recorded in winter in the eastern parts of the study area. Thus unlike other seasons, maximum UVA radiation in overcast condition moves toward central stations in winter. Comparison of daily cumulative radiation maps in overcast condition shows that there is a good agreement between daily cumulative radiation and cloud optical depth (COD) and aerosol optical depth (AOD). This indicates that in overcast condition, total column ozone (TCO) have a weaker impact on UVA radiation as compared to other sky conditions. However, UVA radiation is consistent with total column ozone in clear-sky conditions.
Conclusions
Geographical distribution of UVA radiation indicates that maximum daily radiation in warm seasons has often occurred in the eastern parts of the study area. However, maximum concentration of UVA radiation moves towards southwestern parts of the region in cold seasons. Therefore, residents of the eastern and southwestern regions face a higher risk due to daily cumulative UVA radiation. Findings indicate high biological risk of solar UVA wavelengths in clear-sky condition within the study area. Overcast conditions can reduce daily UVA radiation up to 52% in winter and 21% in summer as compared to clear sky conditions. In real-sky conditions, daily UVA radiation decreases up to 19% in summers and up to 32% in winters as compared to clear-sky conditions. As a result of lower solar zenith angle, the impact of cloudiness on surface UVA radiation in summer is relatively less than cold seasons.
Elham Forootan
Abstract
Extended AbstractIntroduction. Floods are natural disasters which occurrence causes annual great damage to people and environment around the world. So, specifying flood susceptible land is a necessity to reduce and control destructive impacts. Watershed management implementations could affect runoff ...
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Extended AbstractIntroduction. Floods are natural disasters which occurrence causes annual great damage to people and environment around the world. So, specifying flood susceptible land is a necessity to reduce and control destructive impacts. Watershed management implementations could affect runoff volume and flood occurrence. The goal of this study is to apply the combination of Curve Number method and AHP in Arc-GIS to prepare flood susceptibility map and to investigate the role of biological measures in flood susceptibility of the region through this method and statistical tests.Materials & Methods .For this purpose, Pardisan watershed located in the southern part of Qom city was selected. Ten factors layers viz. drainage density, slope, annual rainfall, distance from river, elevation, flow accumulation, SCS Curve Number, geo infiltration, geomorphology and previous floods were prepared and classified based on flood susceptibility in different scales. Then future Curve Number was determine with assuming the implementation of biological watershed management in different land uses such as rangeland, agriculture, garden and badland. In this study, AHP method in Arc-GIS was used to calculate pairwise comparison and determine the weight of each factor. Overlaying current and future Curve Number layers with nine layers using the weights obtained from the hierarchical analysis method led to the preparation of flood susceptibility maps for pre and post watershed management implementation. Results & DiscussionGeo infiltration map showed the proportion area of “low”, “and “very low” infiltration classes were 4.46% and 16.87%, respectively while moderate and high infiltration classes were 39.75% and 38.92%. Slope map indicates that 0-2%, 2-5%, 5-15%, 15-35% and 35-60% classes comprise 29.87%, 35%, 30.11%, 4.88% and 0.14% of the studied area, respectively. In this region, South parts were steep whereas; north parts were mild. Distance to river is another factor classified in to four groups of 0-500, 500-1000, 1000-3000 and 3000-6500 meter with 38.86%, 24.32%, 29.63% and 7.19% of the region, respectively. Elevation classified map revealed 45.1% of the region were in 900-1200 meter range whereas; 36.4%, 14.8%, 3.6% and 0.1% were in 1200-1500,1500-1800,1800-2100 and 2100-2400 meter classes, respectively. As can be seen in rainfall map, 25.57% of the region was categorized in 140-160 mm rainfall class while 35.41%, 20.59% and 18.43% of the whole area were classified in 160-180,180-200 and 200-250mm groups. In the region, South parts have more rainfall volume than north. Also, flow accumulation map indicated that 96.5%, 1.97%, 1.07%, 0.24% and 0.22% were classified as 0-1500, 1500-5000, 5000-15000, 15000-25000, 25000-100000 values which high flow accumulation pixel range show high flood susceptibility. Drainage density map represents 10.38%, 14.36%, 56.88% and 18.38% of the studied area were grouped in 0-0.05, 0.05-0.07, 0.07-0.09 and 0.09-0.12 classes. Also, Curve Number (SCS) map for garden, cultivated lands, rangelands and badlands shows that 25.54% of the study area was classified as 15-35 CN value while 36.14%, 0.9% and 37.42% were categorized in 35-50, 50-65 and 65-80 classes before performing biological measures. After biological measures in different uses, 15-35 Curve Number values are observed in 36.6% of the area and 35-50, 50-65, 65-80 classes comprise 32.05%, 29% and 2.35% of the study area, respectively. The geomorphological map shows that the class with the highest score is visible in 68.96% of the area, while the classes with the lower scores are observed in 3.07, 18.34, 9.37, and 0.26% of the region, respectively. The past flood zoning map of the region also shows that 22.41% of the region exist in low susceptibility class, 36.15% of the region locates in the medium susceptibility class and 41.44% is in the high sensitivity class. For AHP approach, the calculated consistency ratio of this study was less than 0.1. Therefore; the compatibility between ten selected factors was acceptable. AHP results showed that the Curve Number factor has the highest weight percentage (27.44) whereas; the geo-infiltration has the lowest weight percentage (3.20). Comparison of flooding classes for pre and post water management implementation shows that high and medium flooding classes will decrease by 7.3 and 39.7% and low and very low susceptibility classes will increase by 22.18 and 24.82 %, respectively due to the implementation of biological watershed management measures. Also, Sign and Wilcoxon statistical tests indicated the existence of significance difference in flood classes’ for pre and after implementing biological watershed management. ConclusionFlood susceptibility map provision is a necessity in arid and semi-arid regions due to insufficient vegetation cover. The results of this study indicate positive effects of biological watershed management in decreasing flood vulnerability. These findings can be considered for future planning of the region and help watershed managers for optimal utilization of water and soil resources and reduction of flood damage.
Mohammad Ghasem Torkashvand; Mostafa Mousapour
Abstract
Extended Abstract
Introduction
The snow cover is one of the quickest changing phenomena on the earth that considerably affects the climate, amount of radiation, the balance of energy between atmosphere and earth, hydrology cycle and biogeochemical as well as human activities. Precise estimate ...
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Extended Abstract
Introduction
The snow cover is one of the quickest changing phenomena on the earth that considerably affects the climate, amount of radiation, the balance of energy between atmosphere and earth, hydrology cycle and biogeochemical as well as human activities. Precise estimate of snow cover is regarded as one of the fundamental operations in precipitation. Thus, monitoring the snow-covered surfaces hasspecial importancefor the perspective of climatic, ecologic and hydrologic studies. The researchers believe that remote sensing data can lead to better assess from the snow-covered areas than traditional topography methods. Therefore, nowadays, in efficient management of water resources, remote sensing data aims to achieve exact information on snow-covered areasis applying operationally. Satellites are suitable tools to measure the mentioned areas since high snow reflection creates a good contrast with other natural surfaces except clouds. This research is conducted to compare the performance of Cornell functions of support vector and object-oriented Fuzzy operators in estimating the desired areas in Almabolaq Mountain, Asadabad.
Material & Methods
The data used in this research are the bands with 10 m spatial segregation of 2B Sentinel satellite including bands 2, 3, 4 and 8 on 6th March 2020. To classify Cornell functions of support vector machine and compute their accuracy, ENVI software was implemented. The eCognation software was used to partition and categorize those with the same object-oriented Fuzzy operators. Separating similar spectral sets and classifying those with the same spectral behaviour are regarded as satellite information classification. In other words, categorizing the photo pixels, and allocating one pixel to one class or phenomenon are the mentioned classification. Support vector machinethat is one of the most common classifiers in learning machine, which divides data using an optimum separation super plate. One of the important advantages of support vector machine is the ability to deal with high dimensional data using almost less training samples for remote sensing applications. Objective analysis is an advanced technique of image processing which is used to assess the digital images and typical conflicts of basic pixel classification based on different methods. Traditionally, pixel-based analysis can be done by available data of each pixel whereas object-based analysis considers a set of similar pixels called objects or image objects. It regards adjacent pixels with the same information value as one distinct unit called piece or segment. In fact, pieces are the areas produced by one or few homogeneous criteria in one or few dimensions of a specific space, so that the pieces have extra spectral information in each band, mean, maximum and minimum amounts, variance, etc. as compared to single pixels. Combining the object-oriented and Fuzzy methods provides the classification of image pieces with a specific membership degree. In this process, image pieces with different membership degrees are classified in more than one class, so according to the membership degree, image piece classification is done leading to the increased final precision.
Results & Discussion
In this research, after preparing satellite images in SNAP software using Sen2Cor, radiometric correction was conducted on the images. To prepare the classification map of Cornell functions of support vector machine, TIFF satellite images were called by ENVI software. Using the shape file of the case study, the area cutting operation was done. Afterwards, two classes of snow and non-snow regions were created to pick up the training points, so based on imagery processing, training points were specified for each class. To classify support vector machine algorithm, linear, polynomial, radialand sigmoid Cornell functions were applied,soclassification maps were separately produced. To draw the classification map of object-oriented Fuzzy operators, satellite images pre-processed in previous stages were called by eCognation software, then they were defined as a project. Afterwards, two mentioned classes were defined to do the classification process, for each class, the desired Fuzzy operator was determined. For suitable classification, it was done in various scales and weight coefficients of shape and compactness. Scale 75, shape 6.0 and compactness 8.0 presented suitable classification. The training samples, parameters of lighting, mean and standard deviations were chosen as distinct features of classes for object-oriented classification. Using the nearest adjacent neighbor algorithm, object-oriented classification was done for each of the Fuzzy operators. After drawing the snow-covered areas through Cornell functions of support vector machine and object-oriented fuzzy operators, the accuracy of classification was computed.
Conclusion
The results indicate that AND algorithm showing the logic share and minimum return value out of Fuzzy values is the highest accuracy (98%) and to classify digital images,the object-oriented processing methods of satellite imagery enable more precision due to the data related to texture, shape, position, content and geometrical features as compared to Cornell functions of support vector machine.
Hasan Sinaei; Mohammad Saliqe; Mehri Akbari
Abstract
Extended AbstractIntroductionPrecipitation is considered to be one of the most important elements of climate. It affects the distribution of other climate elements and thus, has played a prominent and significant role in recent studies especially those focusing on global climate change. Due to ...
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Extended AbstractIntroductionPrecipitation is considered to be one of the most important elements of climate. It affects the distribution of other climate elements and thus, has played a prominent and significant role in recent studies especially those focusing on global climate change. Due to its geographical location, Iran climate is affected by various climate elements. As one of the most important components of general atmospheric circulation, jet streams affect the quality of precipitation (amount, intensity, temporal and spatial distribution, etc.). Jet streams are relatively narrow bands of strong wind traveling across very long distances at high altitudes of the troposphere (tropopause) forming a hypothetical wind tunnel. Materials & MethodsThe study area surrounds southwestern Iran including provinces of Khuzestan, Ilam, Chaharmahal and Bakhtiari, Kohkiluyeh and Boyer Ahmad, Bushehr and Fars. The present study applies statistical methods and synoptic climatology. Based on the library research, representative days were selected in accordance with the following conditions: 1. Precipitation must have occurred in cold season, since cold season events generally show various patterns due to multiple weather systems affecting precipitation in Iran. 2. A significant percentage of the total annual precipitation must have occurred on the specified day (for example, a precipitation in the 90th percentile in each station). 3. Precipitation must be pervasive (i.e. recorded in more than 70% of the stations in the study area). Three representative days, December 17th 2006, November 25th 2014, and January 17th 1996 were thus selected with the highest precipitation volume over a 30-year statistical period (1989-2018). Two climate databases (precipitation data collected from meteorological stations in the capital city of the previously mentioned provinces and NCEP/NCAR climate data separated based on a 2.5 degree pattern) were used for synoptic analysis of these precipitation events. First, daily precipitation recorded by synoptic stations of southwestern Iran on each of these days was obtained. Then, climatic parameters such as geopotential altitudes of 500 and 850 hPa, jet streams occurring at an altitude of 300 hPa, specific humidity at the 1000 hPa level and values of omega component (measuring upward and downward movement of air flow) at the 500 and 850 hPa levels have been used to explore the relationship between these precipitations and jet streams in troposphere. Finally, GrADS was used to map the previously mentioned parameters. The relationship between precipitation occurrences across different stations of southwestern Iran and troposphere jet streams was exhibited based on an analysis of jet stream maps, moisture flows and other climatic parameters at various atmospheric levels. Results & DiscussionThe relationship found between previously mentioned precipitation events and tropospheric jet streams shows that in each of these events, the jet stream is a westerly wind meandering toward southwest or northeast in the study area and extending throughout North Africa and the Middle East. Central core of the jet stream was traveling above the study area with a speed of 35 to 60 meters per second. The present study indicates that in these three days of heavy precipitation, the jet stream axis has affected the study area in a southwest-northeast direction. Moreover, a cyclone is located at the 850 and 500 hPa levels approximately over eastern Mediterranean whose eastern side extends across southwestern Iran. Southwest-northeast direction of jet stream axis and eastern side of the Mediterranean Sea cyclone being extended toward the study area intensified instability in the lower atmospheric levels of the study area. Negative omega values at the 850 and 500 hPa levels (from -0.15 to -0.8 Pascal-second) indicates severe atmospheric instability in the study area. ConclusionEvery year, southwestern regions of Iran face intensive, and pervasive rainfalls resulting in severe floods and damaging agricultural products, gardens, roads, facilities, industries, etc. The present study indicates that Mediterranean cyclones, westerly winds across the lower atmospheric levels, and the subtropical jet stream meandering in the southwest-northeast (in the meridian direction) direction across the upper atmospheric levels affects the study area. Precipitation in this region is mainly supplied by the moisture coming from warm southern seas (Red Sea, Arabian Sea, Sea of Oman, Persian Gulf, etc).
Seyed Ali Ebadinejad; Mohammad Reza Pourgholami-Sarvandani; Ali Asghar Mohammadpour; Ali Osanlu
Abstract
Extended Abstract Introduction Along with other environmental factors, climatic conditions are among the most important factors affecting social, moral and cultural problems. People behave differently in different climates. Quetelet and Gurreydeveloped crime statistics in Franceandinvestigatedits relationship ...
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Extended Abstract Introduction Along with other environmental factors, climatic conditions are among the most important factors affecting social, moral and cultural problems. People behave differently in different climates. Quetelet and Gurreydeveloped crime statistics in Franceandinvestigatedits relationship with physical environment.Thus, they studied the effects of geography and climatic conditions on human behavior, including criminal behavior. In Climate and Crime, Ellen J. Cohen argues that situational approaches, selected rationaltheories and routine activity theory all suggest that climate has a major impact on the rate of crimes and criminal behaviors. Based on their observations, Quetelet and Gurreyformulatedthethermic law of delinquencyin criminology. Based on statistical studies, they concluded that violent crimes are more frequent in hot seasons and hot regions, while in cold regions and cold seasons, more deceptive crimes such as crimes against property requiring thinking and imaginationoccurmore often. It should be noted that crime is a social phenomenon affected by various factors. Environmental conditions can also intensify the threat of human behaviors. The present study seeks to investigate the relationship between the climatic element of temperature and the occurrence of crime in Shiraz, Abadeh and Larestancounties of Fars province? Materials & Methods The present study is applied in nature and purpose, while taking advantage of an analytical-descriptive method. 3 meteorological stations of Shiraz, Abadeh and Larestan were studied here. Investigated data included the seasonal average temperature and seasonal rate of crimes for the2008-2013 period. Seasonal rate of crimes including social corruption, theft, forgery, strife, mischief, intimidation and coercion, smuggling, drug-related crimes, murder, and suspicious death were investigated in Shiraz, Abadeh and Larestan, which have a meteorological station. Crime statistics were collected from the Prevention Police Department of Fars province Law Enforcement Force and statistics related to the climatic elements of temperature were obtained from Fars Meteorological Department. Different descriptive and inferential statistical methods were used to analyze the data and Pearson correlation coefficient test was used in inferential statistics. Data analysis in the present study included two stages. First, the seasonal and annual percentage of various crimes were studied in each of the mentioned cities. In the second stage, the correlation coefficient between the average temperature and the total (seasonal) number of crime occurrence were investigated. Discussion Investigation of various crime occurrence in Shiraz, Abadeh and Larestancounties of Fars province revealed that in spring, strife and affray (47.11), theft (23.16) and social corruption (19.16) were the most frequently committed crimes in Shiraz. However, intimidation and coercion (0.32), smuggling (0.24), forgery (0.20) and murder (0.05) had the lowest frequency in Shiraz during spring. In summer, strife and affray (47.71), theft (24.64) and social corruption (20.95)are considered to be the most frequent crimes, while intimidation and reluctance (0.33), smuggling (0.23), forgery (0.20) and murder (0.03) arethe least frequent crimes, respectively. In autumn, strife and affray (44.36), theft (27.71) and social corruption (18.24) were more common, whileintimidation and coercion (0.33), smuggling (0.27), forgery (0.26) and murder (0.04) had the lowest frequency. In winter, strife and affray (43.92), theft (29.99) and social corruption (16.84) were the most frequently reported crimes,whileintimidation and coercion (0.35), smuggling (1.4), forgery (0.24) and murder (0.02) were the least frequently reported crimes. Findings indicate that during the 2008-2013 period, strife and affray (45.86), theft (28/28) and social corruption (18.84) were the most common crimesin Shiraz city, while smuggling (0.43), intimidation and coercion (0.33), forgery (0.22) and murder (0.03) were the least common crimes. Generally in the three counties, crimes against the person such as strife and affray, murder, mischief, intimidation and coercion were more frequently reported in warm seasons (spring and summer). However, crimes against property, such as theft, were more frequent in cold seasons (autumn and winter). Strife and affray(0.95) in Shiraz have the highest correlation with the seasonal average temperature. There is a negative correlation between the crime of strife and affray and the seasonal average precipitation in Shiraz. The same relationship existsbetweenstrife and affray and the seasonal average relative humidity in Shiraz. In Larestan, drug-related crimes (-0.97) have the highest negative correlation with the seasonal average temperature. In Abadeh city, social corruptions (0.99) have the highest correlation with the seasonal average temperature. Conclusion: In total, crimes against the person, such as strife, murder, mischief, intimidation and coercion were more commonly reported in the warm seasons of the year (spring and summer) in the three counties on the whole and separately. However, crimes against property such as theft had a higher rate of occurrencein the cold seasons (autumn and winter). Therefore, as crimes against the personare more common in warm seasons and crimes against property are more frequent in cold seasons, it can be concluded that QueteletandGurrey’s thermic law of delinquencyis in force in all the three specified counties. However, this law is not generalizable and it cannot be concluded that crimes against property occur more in cold regions and crimes against the person occurs more in warm regions of Fars province. In this respect, this law only applies to Larestan which is located in the warm region of the province.
Shahriar Khaledi; Ghasem Keikhosravi; Farzaneh Ahmadibarati
Abstract
Extended AbstractIntroductionAmong the climatic elements, the effect of temperature in an area and its changes is the perception of land reclamation and can be maintained and land use of a place. Mean while, surface temperature is an important factor in global warming studies and as a representative ...
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Extended AbstractIntroductionAmong the climatic elements, the effect of temperature in an area and its changes is the perception of land reclamation and can be maintained and land use of a place. Mean while, surface temperature is an important factor in global warming studies and as a representative for climate change and radiation balance estimation in energy balance studies. Due to the special heat that each cover has on the ground. Vegetation land uses, barren lands, water resources, residential areas, absorb some of the sun's radiant energy and increase the temperature of the earth's surface. Finally, this heat is emitted from the surface of various coatings to the environment in the form of long wavelength radiation. If the surface temperature is calculated in different periods, the process of increasing or decreasing the surface temperature of different types of surface coverings can be modeled. MethodologyIn this study, to study the changes in land cover, MODIS images related to land cover from 2001 to 2019 were received. Surface cover product (MCD12Q1) Surface temperature product (MOD11) was prepared on a daily scale for both Terra and Aqua satellites to provide a variety of surface temperature indicators in the Google Earth engine system. In environmental studies, we often deal with observations that are not independent of each other and their interdependence with each other is due to the location and location of the observations in the study space. For this purpose, to reveal the effect of land cover on surface temperature components, global Moran correlation analysis tool was used and to analyze clusters and non-clusters, local Moran insulin index was used. In the last step, to evaluate the relationship between circadian surface temperature, daily temperature and night temperature After converting NDVI and LST raster maps to vector maps, Pearson correlation coefficient, regression relationship and significant value between variables in R programming environment were calculated.DiscussionBased on the land cover product of Modis 5 sensor, the predominant cover including shrubs, grasslands, agricultural lands, scattered vegetation and residential areas were identified between 2001 and 2019. The largest area of the region is scattered vegetation (50%) and secondarily grasslands (20%). During these 19 years, the cover of shrublands and the cover layer of scattered plants has an increasing trend and the cover of grasslands and arable lands has a decreasing trend. The surface temperature of this region has a spatial structure and is distributed in the form of clusters, so it has a spatial relationship with the natural features of the region. Spatial patterns of spatial data on surface temperature are divided into three categories: hot spots, cold spots, and clusters. Low-lying areas of the south and part of the east and west of the area, hot spots, high-altitude areas that include parts of the central areas in the south and north of the area, cold spots and cold spots margin, clusters (foothills) they give. On the 24-hour surface temperature scale, the land use layer of settlements and agricultural lands shows the most significant relationship between the types of land surface cover. In the daily temperature scale, the land use layers, grasslands and scattered vegetation have a decreasing trend and the use layer of shrubs and settlements has an increasing temperature. At night surface temperature scale, the trend of significant surface coatings in relation to the microclimatic element of surface temperature intensifies so that field cover, scattered vegetation and habitat layer have the highest correlation with increasing night surface temperature Show them selves. Therefore, in the study of spatial pattern of surface temperature, latitude and altitude are the most influential factors and in the study of the effects of land cover, the layer of settlements in three surface temperature parameters (minimum, maximum, average) of the highest temperature increase compared to others. Uses have been enjoyed. ConclusionLand use type and land use changes and vegetation have a significant effect on land surface temperature changes. In the northeastern region of the country, shrub cover, grasslands, arable lands, scattered vegetation cover and residential areas are the dominant cover of the region. During 19 years, the increase in the area of scattered vegetation and barren shrubs indicates negative changes in the ecosystem of the region. In such a way that the area of other classes such as arable lands and grasslands has been reduced and the area of these classes has been increased. The surface temperature of this region has a spatial structure and is distributed in the form of clusters in 3 clusters. Hot clusters, low-lying areas, cold clusters, high-altitude areas and inconveniences covered the foothills. Elevation factor, latitude are influential in the distribution of clusters. In studying the effects of land cover on the surface temperature of the land, during 19 years, the circadian temperature of the settlement layer has increased by about 1.12 degrees and the arable land layer by 0.41 degrees Celsius. On the daily temperature scale, the settlement layer has a temperature increase of about 1 degree. At night surface temperature scale, arable land cover, scattered vegetation cover and habitat layer recorded 6.2, 0.8 and 0.6 ° C temperature increase, respectively.
Mohammad Rahim Rahnama; Mehdi Bazargan
Abstract
ExtendedAbstract
Introduction
Walking is one of the most basic methods of transportation in cities. Before the Industrial Revolution, pattern of movements within cities was based on a human scale. But with the onset of Industrial Revolution and the subsequent dominance of modernist thought, the role ...
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ExtendedAbstract
Introduction
Walking is one of the most basic methods of transportation in cities. Before the Industrial Revolution, pattern of movements within cities was based on a human scale. But with the onset of Industrial Revolution and the subsequent dominance of modernist thought, the role and importance of pedestrian zones diminished. Due to the unsatisfactory situation of modern urban planning and its failure, the increased importance given to human development and environmental issues resulted in the introduction of New Urbanism approach. New Urbanism is a response to modernism and the negative effects of suburban expansionin Europe and North America after World War II. In recent years, there have been widespread reactions against the use of motorized vehiclesseeking to revive the issue of increasing walkabilityof cities. With a population of 3057679,Mashhad annually receives 30 million pilgrims and tourists due to the presence of holy shrine of Imam Reza (Peace be Upon Him), which sometimes makes the movement of pedestrians especially around the holy Razavishrine difficult. Furthermore, the holy Razavishrine is located in the central part of the city (Central Business District-CBD) surrounded by a worn-out urban texture and a network of organic passages and thus needs paths with walkability capability. Therefore, the present study intends to identify walkable and human-centered routesin Mashhad using the New Urbanism approach.
Materials and Methods
The present study takes advantage of a descriptive-analytic survey methodology. 32 quantitative and qualitative pedestrian related indices are investigated and 400 questionnairesaredistributedin Mashhad. ArcGIS software is used to analyze the collected data. The study area is Mashhad with an area of around 35187 hectares, a population of 3057679, and a population density of 87 per hectare.
ResultsandDiscussion
Investigating respondents’ age group indicates that 5% of respondents are in the 15-24 year age group, 17% in the age group of 25-34 years, 9% in the age group of 35-44 years, 15.75% in the age group of 45-54 years, 22% in the age group of 55-64 years and 31.25% in the age group of 65 years and more. 32% of the respondents are men and 68% are women.
Surveys show that pedestrians in the western half of Mashhad are more energetic. Public participation is higher in informal settlements of Mashhad. Police records show that crime rates are higher in the suburbs of Mashhad. Regarding hiking culture, the findings show that districts number 1, 8, 9 and 11 ranked highest in the studied indices. The patterns and spatial trends of activities and population attraction centers establishmentin Mashhad show that due to the presence of holy Razavi shrine, most of these activities are located in the central part of the city (CBD), which has the highest potential to attract the population. In fact, the CBD and western areas of Mashhad have the highest economic potential to attract popular activities in Mashhad and thus, the highest number of air pollution sources. The central part of the city (CBD) and west of Mashhad have the highest sources of air pollution. Moreover, the central part of the city (CBD) and the western parts of Mashhad show the highest degree of interconnection in their urban pathways and thus, are more capable of facilitating movement within the city. Per capita green space of Mashhad is 14.26 m2.District number 7 with an area of 2736894 m2 (22.4%) have the mostand Samendistrict with an area of 44736 m2 (0.36%) have the least green space.
Conclusion
Based on 10 principles of New Urbanism, 32 quantitative and qualitative pedestrian related indices were extracted, identifying the paths that canbe used as routesfor pedestrians. For this purpose, 400 questionnaires were distributedin districts of Mashhad. Quantitative and qualitative data were then converted to location-based data and used for spatial analysis (SDA). Finally, combining location-based data, pedestrian routes were identified in Mashhad. Results indicate that based on the New Urbanism indices,district number 8 and Thamenare the first priority, district number11 is the second priority and district number2 is the third priority for pedestrian routes. Kohsangi, Imam Reza (AS) and Moallem-Imamatstreets were also identified as the best pedestrian routes in Mashhad.
