Saeed Farzaneh; Reza Shahhoseini; Iman Kordpour
Abstract
Introduction Drought is considered to be one of the most widespread natural disasters, ranking second in terms of damages. Due to the complex relationship between hydrological cycle parameters and atmospheric observations, predicting or modeling drought lacks the necessary precision. One of the most ...
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Introduction Drought is considered to be one of the most widespread natural disasters, ranking second in terms of damages. Due to the complex relationship between hydrological cycle parameters and atmospheric observations, predicting or modeling drought lacks the necessary precision. One of the most significant problems in drought monitoring is lack of proper spatial coverage for the collected data (due to unavailibility of field data in some regions) and also lack of a suitable time scale (observations and thus drought estimation is not always possible). Since satellite observations do not face challenges like lack of spatial scale which is quite common in field observations, remote sensing satellites can provide a better estimate of droughts. However, satellite observations alone are not capable of accurately estimating the occurrence of droughts. Therefore, a combination of field and satellite observations has been used recentely to reach a better estimate of hydrological problems. Materials & Methods Temporal and spatial complexity of droughts have made a new global index combining ground-based and satellite-based observations quite necessary. Given the kind of data used in MDI index, we cannot expect it to be global. However, its performance is still acceptable in similar environments and climates, and thus it has been used in the United States (Texas). Datasets selected for the present study have different temporal and spatial scales and thus, a common scale must be found before calculating the index. Data received from GRACE satellite and MODIS sensor were downloaded monthly, but precipitation data were collected on a daily basis. Thus, aritmatic mean of precipitation data was calculated to reach a monthly avarage. Regarding the spatial scale, one-degree precipitation data were received from GRACE and MODIS while precipitation data extracted from synoptic stations had a point-based nature. Therefore, Inverse Distance Weighting (IDW) method was used to produce a one-degree network. Three types of observations were used in the present study including data received from synoptic stations of Iran meteorological organization, GRACE mission satellite-based gravity data and MODIS remote sensing satellite-based data. These were selected to identify droughts over a 14-year time series. Results & Discussion The present study has calculated MDI drought index on a one-degree spatial scale and monthly temporal scale for 168 months using Precipitation, NDVI, and TWS data. Severe droughts in northwestern and central areas of Iran from 2004 to 2014 have led to a shortage of water in reservoirs. In addition to drought, too much water harvesting in northwestern Iran has resulted in a decrease in groundwater level and thus, increased water harvesting from rivers and canals leading to the Urmia Lake and reduced water level in this lake. The results of MDI drought index calculated for Iran over the period of 2000 to 2014 show a high correlation with the results of standardized precipitation-evapotranspiration drought index. According to the type of data used to calculate MDI index, it is expected to have a strong correlation with PDSI index due to its sensitivity to precipitation, area temperature and soil moisture content. Since GRACE and MODIS satellite-based data, and data received from synoptic stations were used, a strong correlation with MDI is also expected. It should be noted that PDSI index is higher than MDI index in Iran, although both show the drought trends accurately. For example according to PDSI index, the worst drought of the last two decades in Iran has occurred in 2008, and MDI index shows the same year. Conclusion The present study has introduced a new drought index using a combination of precipitation data, GRACE_TWS and NDVI. These data were selected because of their high sensitivity to drought. GRACE_TWS observations monitor hydrological drought and include surface and subsurface water sources. NDVI observations are mostly used to identify photosynthetic activities of vegetation cover and are therefore very useful for detecting agricultural drought. Precipitation value shows the amount of surface water in the study area. Precipitation can have relatively rapid effects and is therefore useful for monitoring meteorological drought. MDI index has identified several droughts in each region of the country in the period of 2003 to 2016. These identified droughts have generally covered the country over time. However, each drought has had a different impact on ecosystem. In Iran, the most severe droughts have occurred during 2008 to 2009 and 2011 to 2012. Since MDI correlates well with PDSI, both show a drought in these years. In order to develop the proposed algorithm, the effect of different zoning of the study area on MDI index can be studied.
Farzad Moradi; Ali Reza Azmoudeh Ardalan; Parham Pahlavani
Abstract
Introduction Recently, National Cartographic Center, the Organizationfor Registrationof Deeds and Properties, and alsoon a limited scale some municipalities have developed systems to provide real-time differential positioning services. Although these systems have proved to be efficient for quick mapping ...
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Introduction Recently, National Cartographic Center, the Organizationfor Registrationof Deeds and Properties, and alsoon a limited scale some municipalities have developed systems to provide real-time differential positioning services. Although these systems have proved to be efficient for quick mapping purposes in this country, they do not provide accurate differential positioning in coastal and offshore areas and thus cannot meet the needs of navigation and exploration and extraction of marine resources in oil fields. However, Iran has long maritime boundary in its south and north, and maritime economy is considered to be a priorityin its development planning. Since site selection for permanent positioning stationsis considered to be the main step of creating a real-time differential positioning system, finding the most suitable location for permanent positioning stations in the south of the country was selected as the purpose of the present study. To reach this aim, pairwise comparison matrix of the required information layers was first constructed using Delphi methodbased on the opinion of 5 experts, and in the next step, computer coding was performedin MATLAB using Fuzzy Analytic Hierarchy Process to compute the weight of each layer and sublayer.Then, layers were classified in GIS environment based on the weights obtained from the analysis of pairwise comparison matrices for each sublayer. Finally, layers were integrated usingweighted index overlay analysis methodto select optimal sites for permanent stations based on the weights obtained for each layer. Details of the calculations and the results are presented in the article. Materials and Methods High efficiency of analytichierarchyprocess and spatial information systems in management and analysis of spatial data have led to the creation of a highly efficient environment in which various stages of different analysis such as site selection for permanent GNSS stations can be performed. One of the advantages of this procedure is that the analysis can beupdated in the shortest possible time and the result can be depicted visuallyat any stage of decision makingwith a simple changing of the values (weights) of each input data based on the expert opinion. Thisgreatly impacts experts' understanding of changes in the studyarea. Accordingly,fuzzy analytichierarchyprocess method is used within the GIS environment in the present study. Results and Discussion The present study addresses the issue of site selection for permanent GNSS stations. In the first step,pairwise comparison matrix was created for the criteria and sub-criteria and filled in by 5 experts. Then, layers were classified in GIS environment based on the weights obtained for each sub-layers of pairwise comparison matricesand the codes written in MATLAB. Finally, suitable locations for permanent GNSS stations were obtainedby integrating the layers usingweighted index overlay. Conclusion The present study has provided the results of optimal site selection for GNSS permanent stations. These selected sites meet the needsofprecise positioning in the coastal areas of the country and can be used in navigation and exploration and extraction of marine resources and oil fields. Afterthe selection of southern coasts as the study area, 7 criteria (proximity to urban areas and facilities, slope, distance from faults, distance from access roads, soil type, distance from rivers and distance from railways) were selected based on the expert opinion. A pairwise comparison matrix was createdfor these criteria and sub-criteria and 5 expert experts were consulted in this regard. Expert opinions were analyzed using codes written in MATLAB software andFuzzy Analytic Hierarchy Process method and thus, the weight of each criterion and sub-criterion was obtained. These weights were then integrated using the geometric mean method and the final weight of each layer and sublayer was determined. Using Arc map software, these weights were applied to different layers and sublayers, and finally, optimal locations for permanent GNSS stations were divided into 5 classesof very good, good, medium, bad, and very bad stations. Good and very good classes can be considered as optimal places forcontinuously operating reference stations.
Kobra Bozorgniya; Hani Rezayan; Javad Sadidi
Abstract
Introduction The accuracy of positioning depends on the quality of the technology used. Various technologies and techniques are used for positioning which are classified as absolute and dead-reckoning groups. Classified as absolute positioning technologies,GPS receiversface a variety of different errors ...
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Introduction The accuracy of positioning depends on the quality of the technology used. Various technologies and techniques are used for positioning which are classified as absolute and dead-reckoning groups. Classified as absolute positioning technologies,GPS receiversface a variety of different errors in the real-time positioning of a moving object, which reduces the accuracy and precision of the position received from these receivers. On the other hand, dead-reckoning sensors such as gyroscopes and magnetometers which measure real-time state of a moving object also have cumulative errors.Therefore, observations made by all of these sensors are not free from the noise generated during the measurement process.The amount of this noise may vary depending on various factors, including the precision of the sensor and features of the measuring environment. Thus,due to thecorrelation between observations made by these two categories of sensors and the difference between their precision and the nature of their errors,ifnoise is reduced inobservations made by them, their complementary features can be used to reduce errors made by each of them.High-quality positioning technologies are expensive and require high expertise.As a result,lower quality and cheaper global navigation satellite systems (like GPS) widelyavailable in smartphones are more commonly used. One of the most important features of these inexpensive technologies is that they are highly susceptible to factors producing noise. Methodology The present studyinvestigates the effect of gradual reduction of noise from data collected by sensors, accelerometers, magnetometers, gyroscopes, and GPS technology in smartphones on improvement of vehicle positioning. The proposed method is based on using acceleration, azimuth, latitude, longitude and roll angle parameters as an input for the Kalman algorithm and investigates the effect of reducing noise produced by these parameters using the least-squares method onimprovement of the resulting position calculated by the Kalman algorithm. To reach this aim, the roll angle parameter is extracted from the angular Velocity() in y-direction and the azimuth parameter is extracted from the magnetic field() in both x and y directions. These parameters along with the acceleration(a) parameter in x and y directions and the geographic coordinates are selected for the Kalman filtering algorithm. In the proposed method, data received from sensors share common sources of noise produceddue to drift, random movements and bias errors.To reduce this noise independently and systematically, method of averaging with the least-squares is usedfor data produced by each sensor. Thus, noise in the received data is considered as a random parameter and noise reduction is performed based on the percentage of changes in the corrected and observed data in the range of 1 to 10%. Kalman algorithm is implemented for 10 levels of noise reduction and the results areinvestigated and compared.The filter calculates and improves an estimate of position vector x, denoted by with minimum mean square error using a recursive model. The main objective is to derive an accurate estimate of for the state of the observed system at time of k. Implementing Kalman filter consists of a prediction step and an updating step. The result is compared todata received from a more accurate reference using RMSE. Results and Discussions The study area consists of lane no. 2 of the South-North (East-West) Azadegan Highway, Tehran, Iran with a total area of about 26km. Results show that compared to the reference data, using Kalman filter has decreased errorsin positioning the car from 0.8274 m to 0.6763 m with a 2%noise reduction. With a 10% noise reduction, the accuracy of this method has increases to 0.6771 m. This improved accuracy is due to noise reduction and consequently an increase in the correlation between the parameters. Accordingly, the threshold limit for noise reduction and improved positioning using Kalman filter is low and can be recognized by an investigation of a few lowlimits. According to the findings, although reducing the effect of noise can improve positioning with Kalman filter and smart phone sensors, irregular changes in the accuracy of noise reduction methods require determining an optimal percentage for noise reduction.
Mohammad Kazemi Garaje; Khalil Valizadeh Kamran
Abstract
1- Introduction Direct measurement of physical parameters of water, such as sea surface temperature and water depth through traditional methods is very time-consuming and costly. Thus, new cost-effective methods, such as remote sensing technology, have always been of interest to experts, managers and ...
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1- Introduction Direct measurement of physical parameters of water, such as sea surface temperature and water depth through traditional methods is very time-consuming and costly. Thus, new cost-effective methods, such as remote sensing technology, have always been of interest to experts, managers and decision-makers. Satellite imagery is used to estimate sea surface temperature and water depth. Therefore, the present study seeks to calculate sea surface temperature and water depth and investigate their relation using satellite imagery. 2- Materials and Methods In the present study, Landsat 8 satellite images of Urmia and Van Lake were retrieved from USGS website for August 16th, and August 23rd, 2018. Information about water temperature and water depth of 3 meteorological stations in the study area were also obtained from the Artemia Research Center and the Meteorological Organization of West Azerbaijan Province for a period of three months. In the next step, geometric and atmospheric corrections were performed on the images using ENVI5.3 software. In thermal remote sensing, thermal bandwidth of satellite imagery cannot reflect black-body radiation. Moreover, electromagnetic spectrum of radiation used in the Boltzmann relationship covers a range of 3 to 300 micrometers. This is while the thermal spectrum range of thermal sensors is generally between 10.5 to 12.5 micrometers.Thus, the split-window algorithm was used to calculate the land surface temperature. Water emission coefficient equals 0.98. Multiplying the amount of water emission by the amount of land surface temperature (LST) and subtracting the results from zero Kelvins (-273), we can obtain sea surface temperature in Celsius degrees. 2-1- Calculating relative depth of water As one of the dynamic characteristics of water, water depth has an important role in the management and optimal use of marine resources. Water depth measurement refers to the underwater study of oceans, lakes and rivers. Therefore, Stump Method was used to calculate water depthin the present study. 2-2- Accuracy assessment In order to estimate the accuracy, information about water surface temperature and relative water depth in three stations in Lake Urmia, namely Qalqachi, MalekAshtar and Ashk stations, were collected from the Artemia Research Center and the Meteorological Organization of West Azerbaijan Province. 3- Results Results indicate high accuracy of remote sensing methods in sea surface temperature and water depth measurements. The lowest RMSE of sea surface temperature measurement is related to MalekAshtar station (1/1). This station also has the lowest amount of RMSE (1/5) obtained in water depthmeasurement. According to the results, a negative correlation coefficient is observed between the values of sea surface temperature and water depthvariables. The correlation between sea surface temperature and water depth in Lake Van equals -0.52, while this correlation equals -0.24in Lake Urmia. 4- Discussion Despite their relatively high accuracy, usinginformation collected from meteorological stations to calculate physical parameters of water,such as water surface temperature and water depth, has some limitations. However, new technologies such as remote sensing can overcome the limitations of traditional methods. Remote sensing technology has made estimating the physical parameters of water on a regional to a global scale possible. Results of the present study indicate high accuracy of remote sensing technology in measuring physical parameters of water such as surface temperature and depth. In this regard, shallow water bodies have the highest surface temperature and deeper water show lower temperatures. The results also indicate that fluctuations in the water surface temperature and water depth can increase or decrease the correlation coefficient between these two variables. Thus, higher correlation coefficient between water surface temperature and water depth in Lake Van compared to Lake Urmia is due to its greater depth of water. 5- Conclusion Results indicate that the upstream of Lake Urmia is deeper than itsdownstream and also has a higher level of salinity which reduce evapotranspiration in the upstream of the lake. Thus, theupstreamof Lake Urmia has not been as severely affected by the drought. The correlation coefficient between water surface temperature and water depth of Lake Van also shows that this lake has a relatively lower water surface temperature compared to Lake Urmia due to its greater depth. Therefore, the rate of evapotranspiration in this lake is less than Lake Urmia and the drying process is negligible. Due to the fact that Lake Urmia and Van are in the same climate, the high temperature of the water level of Lake Urmia due to its shallower depth can be one of the causes of Lake Urmiadrying. The amount of water in the lake can be increased by increasing the volume of water entering the lake.This can be achieved by destroying a number of dams built on the rivers flowing into the lake or by water transfer from adjacent water bodies. Therefore, increasingwater depth and reducingwater surface temperature can be considered as one of the main solutions to prevent the drying of Lake Urmia.
Amir Hosein Shokri; Saied Sadeghian
Abstract
Introduction Recently, cadastre has become a suitable platform for global partnership in management of land and its assets. Due to ever- increasing population, spatial organization of citiesis considered to be one of the most important issues in national development planning. This indicates the necessity ...
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Introduction Recently, cadastre has become a suitable platform for global partnership in management of land and its assets. Due to ever- increasing population, spatial organization of citiesis considered to be one of the most important issues in national development planning. This indicates the necessity of using 3D land information systems since theenvironment, quality, ownership and other benefits of lands do not only change horizontallyany moreand height is also a decisive and vital factor.Therefore, 3D cadastreis used as abasis for integrating information into a complete and efficient information storage system. This system is usedtomanage scarce land resources and plays a key role in achieving future legal and managerial success in the field ofreal-estate. Designing and implementing a system capable of displaying the third dimension (height) is very complex. Common methods of producing 3D cadastral models include land surveying, classical aerial photogrammetry, high-resolution satellite imagery, and so on. Recently, the advent of drones has provided a suitable platform for large-scale cadastral mapping. Collecting high resolution images, processing withstructure from motion(SFM) method, multi-stereo vision (MSV), and dense 3D point cloud with a high resolution of about a few centimeters are the main advantages of these tools. Recentstudies in this field indicate high capabilities of UAV-based photogrammetry method for the production and updating of cadastral maps. Materials and Methods Due to the applied nature of the present study, guideline for the spatial information production using photogrammetric method published by Tehran Municipality and other Surveying and Mapping guidelines published by the National Cartographic Center of Iran have been used to produce 3D cadastral modeland reach relatively real results. The study area is Khosban village in MiyanTaleqan rural district, in the central district of Taleqan County, Alborz Province, Iran. Necessary information was collected using an eBee Plus survey drone with a SODA camera (designed for professional photogrammetric applications). Besides, exterior orientation parameters were measured using the preciseinertial measurement unit (IMU), global navigation satellite system (GNSS) Antenna withreal-time kinematic (RTK) and post-processing kinematic (PPK) techniques and triangulation was performed using these parameters. To increase the accuracy, reduce hidden areas and achieve more accurate 3D models, 75%longitudinal and transverse overlappingwere considered for the images. Image processing was performed using Pix4dmapper and Metashape software and products such as orthomosaic, dense 3D point cloud, and digital surface model were produced. To prove thegeometric accuracy of triangulation, 8 ground control points were used, and32 checkpoints were also used for the final evaluation of 3D models. Results and Discussion 3D cadastre implementation was performedin the present paperusing UAV based photogrammetry without any ground control points. According to the results of triangulation, the maximum root mean square error in the X-component was reported 3.21 cm, the Y-componentwas reported2.86 cm, and the Z-component was reported 3.96 cm using Pix4dmapper and Metashape software. Moreover, 32 sample checkpoints were used for the final evaluation of the 3D models and data collected from these points were compared with the reference data. Results indicated the occurrence of maximum root mean square error in the horizontal components (X, Y) of 0.2 and 0.21 meter respectively, and 0.27 meter in the height component (Z). A correlation coefficient of about 1 represents high geometric accuracy of the 3D models produced using UAV based photogrammetry. Conclusion 3D cadastre can be used as a tool for improving land management and related issues. Due to structural complexity and ownership issues,most developed countrieshave not yet fully implemented 3D cadastre. However, these countries are always looking for ways to achieve such a system. So far in our country, the issue of 3D cadaster has only been pursued in academic studies and no practical stephas been taken to implement this system. Unfortunately, technical dimension and preparation of 3D models are only a part of 3d cadastre and legal issues occurring due to insufficient understanding of the third dimensionand its complexity alsolead to failure in the implementation of 3D cadaster.
Yousef Ebadi; Akram Eftekhary; Hekmatollah Mohammad Khanlu; Majid Fakhri
Abstract
Introduction As an important type of precipitation, snow is especially important in the hydrological cycle. This importance can be examined and analyzed from several aspects such as water supply in other seasons. The most important aspect is the possibility of creating hazards for human beings and human ...
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Introduction As an important type of precipitation, snow is especially important in the hydrological cycle. This importance can be examined and analyzed from several aspects such as water supply in other seasons. The most important aspect is the possibility of creating hazards for human beings and human infrastructure (snow avalanches, floods during seasonsof snowmelt). Therefore, it is necessary to study the snow phenomenon and its covered surfaces in winter. Monitoring the changes in this important climatic phenomenon has always been considered important by researchers and planners. Remote sensing methods have revolutionized the field of natural environment monitoring since their inception. Snow depth is an example of what can be monitored and evaluated by remotely sensed data and techniques. Materials & Methods The present study seeks to evaluate the efficiency of several important remote sensing indices in monitoring snow depth, andalso to introduce and evaluate a proposed spectral index. To reach this aim, satellite images of Landsat 8 and Sentinel 2 have been used. These images were received from the relevant portal and used to calculate snow indicesafterinitial corrections. Four spectral indices were usedto extract snow covered surfaces. These indices include: NDSI - S3 - NDSII - SWI. These indices are based on reflection from snow covered surfaces in light reflection and absorption spectra of snow covered surfaces.Light reflection from snow covered surfaces in the visible spectra and absorption in the short infrared spectrum allow automatic detection and extraction of snow covered surfacesin remote sensing multispectral images. The above mentioned indices have the ability to extract snow, but they fail to differentiatebetween snow and other related phenomena such as water (in the absorption band) and light-color salt marshes (in the reflection band) and thus, similarity of the spectra occurs. This spectral mixing which occurs due to the similarity of the reflections, cannot be eliminated even when threshold limits are defined. Thus, the extracted snow cover includes not only snow, but also other similar zones. To solve this problem and extract snow covered surfaces correctly,a new index is presented in this paper based on principal component analysis (PCA) and the first component of the set, and short wave infrared (SWIR) spectrum reflection.Using the first component of the set with the highest variance makes the difference between reflectance of snow and similar phenomena visible and thus, solves the issue of spectral mixing to a very large extent. The proposed new index called PCSWIRI is also evaluated and validated along with 4 other indices in the present paper. Results & Discussion Spectral indices introduced in the previous section were examined and evaluatedusing 7 sets of images (4 Landsat images and 3 sentinel 2images) captured in different days of winter from the main study area (Lake Urmia in the northwest) and two other study areas. The results indicate efficiency of the proposed index in the extractionof snow covered surfaces. The proposed index has improved the accuracy of snow cover extractionin the whole collection of images. This increased accuracy has been confirmed withstatistical evaluation criteria, such as kappa coefficient, overall accuracy and in the visual review of indices(comparing to the composition of the original image). The main study area includes Lake Urmia, an important geographic feature containing water and salt and a mixture of the two, which makes its spectrum similar to snow. This lake is incorrectly identified by other indices as a snow covered surface. Like the main study area, the first study and assessment area contains salt covered zones (salt lake). Despite the spectral similarity between snow and salt,the proposed index has been able to distinguish between this phenomena (in both regions) and snow and to extract only realsnow covered surfaces. In addition, visual review of existing water bodies (Dam Lake) and 5 evaluated indicesindicates higher accuracy of the proposed index. In order to automate the process of calculation in the proposed spectral indices, a software was also providedbased on MatLAB. Conclusion The findings of the present study indicates higher accuracy and efficiency of the proposed index (PCSWIRI) for snow cover extraction. Snow cover maps are very useful in various hydrological, climatic, precipitation-runoff modeling studies, and etc. Therefore, increasing the accuracy of snow cover maps is of great importance and results inimprovedaccuracy and reliability of modeling processes.
Morteza Heidarimozaffar; Morteza Shahavand
Abstract
Introduction Iran is mostly located in arid and semi-arid regions, and groundwater is its only water resource. The present study introduces a method based on spatial zoning evaluation which takes advantage ofFuzzy Logic and Geospatial Information System to design possible sites for an underground dam, ...
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Introduction Iran is mostly located in arid and semi-arid regions, and groundwater is its only water resource. The present study introduces a method based on spatial zoning evaluation which takes advantage ofFuzzy Logic and Geospatial Information System to design possible sites for an underground dam, and ranks them according to their suitability. The usability of this method for the construction of an underground dam in Kabodarahang Plain in the north of Hamedan Provincewas evaluated in the present study. Materials & Methods Groundwater use is considered to be a solution of water scarcity in arid and semi-arid regions. Lack of sufficient financial resources and adequate technology as well as specific physical conditions make it difficult to provide clean water in arid areas of most developing countries. Over the past few years, underground dams has been considered as a way to overcome water scarcity in arid and semi-arid regions. The present study seeks to identify suitable locations for the construction of an underground dam in Kabodarahangplain in north of Hamadan province using fuzzy logic in GIS environment. As one of the case study areas of Qareh Chai River,KabodarahangPlain isthe largest plain of Hamedan province with an area of 3448 square kilometers and an average height of about 1789 meters above the sea level.It is located between 48°14ˊ 51 ̋ to 49° 5ˊ 11 ̋ eastern longitude and 34° 50ˊ 6 ̋ to36°14ˊ 31 ̋ Northern latitude. To reach the goal of the present study, effective parameters in the constructionof underground dam, such as land slope, positionof wells, springs and aqueducts, rivers channels, positionof faults, location of villages and cities, position of paths and the thickness of alluvium were collected from the study area. Based onthe possibility of performing different spatial analyses in geographic information system environment, zoning ofKaboodarahang plain was evaluated from the point of view of an underground dam construction usingfuzzy logic and GIS tools in the present study. Results & Discussion Similar to membership in classical series,“And” operatorin Fuzzy Logic is used when two or more different criteria can help in solving an issue. This operator extracts the minimum membership level of pixel units in a specified positionand use it in the final map.Fuzzy multiplication operator multiplies membership level of pixel units in specified positionsof different factors and use the result in the final map. This operator is used when mapsof different criteria have a subtractive effect on each other.Fuzzy gamma operator is the general form of algebraic multiplication of fuzzy multiplication and addition operators to the power of gamma. It is used when increasing and decreasing effects are present in the relations between different criteria. Following the preparation of layers in Arc Map software, Euclidean distance operator and interpolation based on triangulation method were used to convert parameters to raster layers. Based on the background research and standards used, the criteria maps were combined using fuzzy operators. Using Fuzzy membership operator, an area of 3342 hectares, using fuzzy multiplier operator an area of2393 hectare (around one percent of the study area) and using the fuzzy gamma operator, an area of 35574 hectares (10.32% of the study area) was selected as having a very good potential for underground dam construction.Slope Map is also one of the most important criteria in determining areas appropriate for underground dam construction. It is suggested to use a larger-scale topographic map to improve the accuracy and increase the possibility of errors. Intelligent algorithms can also be used to determine the threshold level for standardization of the criteria. Since different organizationswork in the field of data collection, it is also suggested to providea suitable mechanism to assess the potential of other plains through consultation and coordination with other relevant organizations. It is recommended to use other parameters and factors affecting the selection of suitable areas for the construction of underground dams, such as soil type or physical and chemical properties of soil in future studies. Conclusion Zoning maps prepared by fuzzy logic in GIS environment can be used to determine the appropriate location forthe constructionof underground dams. Fuzzy operators provide special conditions which make them more reliablecompared to traditional methods.Appropriate areas for construction of underground dam were identified in GIS environment. A decision making model can also be produced based on the input parameters.It is suggested to enter general information of the area to perform the initial investigation of potential areas and then add field study information to complete the model.
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.
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.
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
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.
Ayyob Ebrahimi; Mohammad H. Vahidnia
Abstract
Introduction
One of the most important components of disease prevention has always been having access to information on distribution of patients, their gender and age. With this information, we find the areas in which further prevention or care programs need to be implemented. In addition, this information ...
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Introduction
One of the most important components of disease prevention has always been having access to information on distribution of patients, their gender and age. With this information, we find the areas in which further prevention or care programs need to be implemented. In addition, this information helps in determining the effects of factors contributing to the spread of a disease in different areas. Thus, using new technologies such as GIS in such a field can be quite advantageous. Methods of spatial-statistical analysis can help us in mapping disease diffusion, its predicted future trend, and factors affecting that disease. Therefore, public health organizations have recently used such technologies to develop more appropriate health, prevention, and treatment plans.
As a major health problem, gastric cancer is reported to be the most common type of cancer and the second leading cause of cancer-related deaths in the world. Following cardiovascular disease, cancer is the second leading cause of death in Iran. GIS capabilities have made it possible to use a variety of spatial-statistical models for gastric cancer. The present study seeks to analyze the spatial distribution of gastric cancer in Hamedan province, identify the incidence and prevalence of this disease based on gender and age of patients, and map the geographical factors affecting this disease. In this regard, methods of interpolation, classification, and clustering of highly affected points are used. Spatial correlation is also calculated using regression methods.
Materials and Methods
In order to prepare spatial distribution maps of gastric cancer in Hamadan province, related data on all gastric cancer patients between 2011 and 2015 were collected from the Population-Based Cancer Registry of Hamadan Medical Sciences University. Collected data included age, gender, and address of patients. Data were first classified based on the address registered for each patient in each year. Then, geocoding process was used to convert addresses into positions using Google Maps and create related layers in GIS software. Descriptions were then assigned to the layer of cities and 1157 points were produced for these 5 years and added to the maps. According to the obtained points, spatial distribution maps were prepared based on age and gender of patients. Age distribution of gastric cancer patients was also calculated using interpolation analysis and the IDW method. In the next step, maps of provinces in critical situation were prepared according to the Hotspot method using the Getis index. In cooperation with Water and Sewage Authority, data were also collected on water pollution (including nitrate, and lead in water and water hardness) to determine the relationship between the severity of the disease and environmental variables (water pollution). Ecological analysis was then performed based on regression analysis using ordinary least squares (OLS) method.
Result and Discussion
Results of the study and age distribution maps indicated lack of any significant clustering in the studied cities. Moreover, the age groups were sparsely distributed in each year. However, statistical analysis of patients’ age and gender showed a higher incidence of gastric cancer in men and in over 70-year age group during the reference period. Cluster analysis of areas with higher incidence of gastric cancer based on Hotspot method identified Qahavand as one of the cities having a critical situation regarding gastric cancer during the reference period with 99% confidence interval. Hamadan City was ranked second with 95% confidence interval. Laljin was ranked third with 90% confidence during the reference period. Regression analysis performed to determine the relationship between disease severity and environmental variables (water pollution) indicated the presence of a positive relationship between the level of lead and nitrate in drinking water and cancer incidences. However, an ideal fit was not reached for the regression model due to unavailability of recently collected data, small sample size, and inadequate data distribution.
Conclusion
Since a different life style is considered to be the most crucial basis of combating a disease, education, empowerment, policymaking and enactment of laws and regulations can create an appropriate environment to promote healthy lifestyle and behaviors. In fact, a useful intervention in society can eliminate or reduce the impact of many risk factors. Cooperation between the fields of geography and medical sciences can result in designing and implementing an acceptable system in the society. GIS is one of the technologies used in this regard to provide health warnings for people at risk based on proper analysis. The present study showed the efficiency of techniques such as classifications, interpolation, hotspot, and regression analysis in assessing disease severity, and factors affecting its incidence.
Morteza Najafi; Mojtaba Rafieian; Rama Ghalambor Dezfuli
Abstract
Introduction Nowadays, spatial models and techniques are widely used to analyze challenges at urban and regional levels. These models and techniques can identify the relations between different variables, evaluate their impact on spatial spheres, and thus aid urban planners and managers. Recently, solid ...
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Introduction Nowadays, spatial models and techniques are widely used to analyze challenges at urban and regional levels. These models and techniques can identify the relations between different variables, evaluate their impact on spatial spheres, and thus aid urban planners and managers. Recently, solid waste and the amount of waste generated in urban areas have gained attention as a major global challenge and the World Bank has highlighted the importance of an acceptable global approach to the issue of urban waste in 2016 (World Bank, 2016). Urban waste impacts the city and its urban management system in different ways such as urban environment degradation, economic impacts and the challenges of urban landscape. Different factors impact urban solid waste generation and investigating the relation between these variables can help urban planners and managers formulate general plans and policies to reduce urban waste. But a mere examination of the relationship between factors affecting urban waste generation and the variables proposed by the World Bank cannot provide a good estimate of the future status, since spatial factors always impact the quantity of urban waste generated. Therefore, spatial models and artificial neural networks were proposed and discussed. Geographically Weighted Regression is one of these methods used to investigate the relationship between different factors affecting urban waste generation. Geographically Weighted Regression can investigate the relationship between different variables, examine their impact on the city and predict the relationship between different variable of urban waste generation and their impact on the city in the future. The artificial neural network was also used to assess the nature of data and predict the future status of urban waste. Materials & Methods The study area consists of 22 districts, 123 zones (116 zone due to the availability of supplementary information of 2011-2012 regarding the districts of Tehran), 40323 statistical areas and 895247 land uses of Tehran. Data were classified in three stages. The first phase includes the information collected from Tehran waste management organization regarding urban waste in 1996 to 2016. In the second phase, information was collected from statistical center of Iran regarding demographic segments and social components. Finally, data were collected from Tehran municipality in the third phase providing useful information about urban performance (Land use). Results & Discussion Physical-environmental components and especially land use directly impact urban waste generation. However, results indicate that some land uses such as institutional and publicbuildings gradually stop the increasing process of urban waste generation due to a decrease in their population as compared to residential land use. Population density and income ratio are investigated as the first and second rank variables. These two variables have directly impacted the amount of urban waste generation in most districts of Tehran. From central areas of the 6th district to the southern areas of the 20th district, southeastern areas of the 18th district and eastern areas of the 4th district of Tehran were influenced by population variables. In other words, the amount of urban waste generation is increased with increased population density in these district. However, the amount of urban waste generation in the 22nd and 21st districts do not change with the above mentioned variables. Results indicate that different urban development plans and policies increase population and area dedicated to different land uses and thus, play an important role in urban waste generation. The 22nd and 21st districts are in a desirable status regarding variables such as area, population, and urban waste generation, but predictions indicate that they will reach a similar status and face challenges related to urban waste generation in 10 years. Spatial distribution pattern of urban waste generation in Tehran indicates that the eastern and southern districts produce the highest amount of urban wastes. This pattern is gradually moving from central to western and central districts, and without a plan to control the situation, the pattern will move from east to west and south to north of Tehran in the next 10 years. Based on the results of spatial autocorrelation and a comparison with the results of the least squares method, Geographically Weighted Regression was considered as a suitable method of predicting urban waste variables in Tehran. This indicates that spatial variables affect urban waste generation in Tehran. Moreover, artificial neural network is capable of predicting non-spatial nature of relations among different variables of urban waste generation and thus can predict the amount of urban waste generation in Tehran. Conclusion Results not only identify (physical-environmental, economic and social) variables affecting urban waste generation, but also indicate superiority of Geographically Weighted Regression technique at spatial and non-spatial levels as compared to the least-squares regression and artificial neural network.
Esmaeil Aliakbari; Mostafa Taleshi; Mohammadreza Karami; Kioumars Maleki
Abstract
Introduction
On average, an earthquake with the force of 6 magnitude of the Richter scale hits Iran every year and a 7.0 earthquake strikes the country every ten years. The fact that urban areas face serious damages due to these natural disasters makes it clear ...
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Introduction
On average, an earthquake with the force of 6 magnitude of the Richter scale hits Iran every year and a 7.0 earthquake strikes the country every ten years. The fact that urban areas face serious damages due to these natural disasters makes it clear that a crisis plan is quite necessary. City is a multi-layered structure consisting of closely related physical and non-physical components (functional, spatial, and social) with two levels of interaction among them. Providing a clear understanding of the consequences of hazards and evaluating vulnerable urban areas seem to be a necessary step toward decreased vulnerability to natural hazards. This will be definitely reached through policy making, making the right decisions and taking the right actions. The present study seeks to analyze zoning and vulnerability of Kermanshah metropolis in regard to possible earthquakes. Findings of the present study can be used to prepare an appropriate plan for the future of this city. The present study also explains physical, social and natural components, and uses a combination of these components to prepare different quantitative models and the necessary indicators (basic studies). It also attempts to provide methods of implementing these models and indicators (operational methods). And finally it seeks to prepare a hazard map to facilitate the identification of critical areas and impenetrable residential zones in Kermanshah metropolis, while determining optimal directions for future physical-spatial development of Kermanshah based on seismic risk zone. This is achieved through a new approach using Analytic hierarchy process.
Methodology
GIS and multi-criteria decision making methods are used in the present study for seismic zoning of natural, physical, social, and economic dimensions of Kermanshah. To reach this end, statistical, non-statistical and online sources were used and necessary maps were collected from relevant organizations and departments. In general, 1, 25000 topographic maps (AutoCAD Versions), Parcel maps of the 2016 census, land use maps showing the present situation (AutoCAD Versions), and etc. were used in the present study. Except for parcel map which was prepared in Shapefile (a well-known format prepared in ARCGIS software) and thus ready for GIS analysis, other layers were prepared in CAD format and had to be edited, revised, and then converted to Coverage format and Shapefile for final editing in GIS models. It is noteworthy that many of these maps were completed and edited by the authors. Then, maps required for each cluster were standardized using the classification method. Related weights and pairwise comparison matrix were defined for each cluster using scientific resources.
Results and Discussion
Due to the large number of sub-indicators used in the present study, each indicator was rated and graded separately. Results indicate that Kermanshah metropolitan area enjoys a desirable status regarding the economic indicator since69.6% of the city lies in the low vulnerability range of this indicator. Regarding the social indicator, the city is in an unfavorable status since56.6% of its area lies in a very high vulnerability range and only a small percentage of the city area (1.5%) lies in the low vulnerability range. Regarding the physical indicator, 57% of the city lies in the medium vulnerability range and 33.2% in the low vulnerability range. Regarding the natural indicator, 55.4% of the city lies in the medium vulnerability range, 36.5% in the high vulnerability range, 1.8% in the very high vulnerability range, and 6.3% in the low vulnerability range. The unfavorable status of the social indicator is due to the presence of areas facing high or very high levels of vulnerability. Findings of the economic indicator imply the distribution of an economic class with an average income in the city. Regarding the physical indicator, about 30% of the city area is covered by old vulnerable settlements constructed with unsustainable materials in direct contrast with urban planning rules. These areas require improvement, reconstruction, and renovation. Regarding the natural indicator, Kermanshah and its neighboring cities are built on earthquake fault lines. Dealing with this situation requires strengthening and modernization of old urban contexts, increasing permeability of arterial roads, development of non-physical spaces, making a greater use of empty spaces, and building new residential spaces (brownfield lands). Findings indicate the significant role of natural factors (including proximity to earthquake fault lines), physical factors (old contexts, inefficient materials, and etc.), and above all, lack of engineering supervision in the present constructions of the city. Land uses facing earthquake hazards in Kermanshah include residential (about 16% located in the very high vulnerability range), road network (about 15% located in the very high vulnerability), and emergency operation, military and medical centers. This will definitely jeopardize any rescue operation in possible future earthquakes.
Conclusion
Earthquake and its related devastating mechanism constitute a very complex process in which various factors play a role. These factors can reduce destructive effects of earthquakes on urban settlements. High population density, patterns of spatial distribution, vast man-made environment and different characteristics and conditions of its constructions have made analyzing the situation if not impossible (without computer and advanced software), quite difficult. The present study has analyzed different indicators and sub-indicators, and introduced inappropriate status of physical elements, inefficient road network, overcrowded and worn-out urban fabric in the city center, high density, and inappropriate distribution of open and green spaces in the city as the key factors resulting in increased vulnerability of land uses in the current zoning of the city. Due to the close relationship between damages of an earthquake and proximity to earthquake fault lines, development of a physical-spatial model in Kermanshah metropolis before the occurrence of future earthquakes seems necessary. Results indicate that in case rules and principles of urban planning are followed, endogenous and horizontal development of the city toward southern and northwestern direction seem to be logical. Furthermore, considering factors such as slope, slope direction and the east-west direction of faults, development of the city toward west or east is not recommended unless principles of urban planning and reinforcing is completely followed. Rough and rugged topography of the northern and northeastern parts of the city is also another obstacle to the physical development of the city in these directions. Therefore, physical-spatial development in the southern and southwestern direction, along with infill and endogenous development according to the potential of the city are recommended
Zahra Servati; Gholamreza Latifi
Abstract
Introduction
Development of cities and vehicles used in urban areas have resulted inenvironmentalcrisisin most metropolises all over the world and caused physical and psychological damages to the residents of those areas. Comfort, especially thermal comfort, is one of the main factorsaffectingquality ...
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Introduction
Development of cities and vehicles used in urban areas have resulted inenvironmentalcrisisin most metropolises all over the world and caused physical and psychological damages to the residents of those areas. Comfort, especially thermal comfort, is one of the main factorsaffectingquality of space and people’s satisfaction in using that space. Thus, it is necessary to create a suitable environment for human beings through protection against adverse climatic conditions. Providing thermal comfort in open urban spaces is an important principle of urban planning, which affects physical and mental health of human beings and consequently, improves their performance. Compared toindoor and private spaces, fewer researches have focused on thermal conditions of public space, which is most possibly due tospatial diversity, wide range of activities performed in open spacesin urban areas, andthe complexity of parameters affecting outdoor comfort.Urban spaces are the scene in which the story of collective life unfolds. Thermal comfort in these areas is considered to be one of the most important and influential issues in various aspects of life. Natural ventilation in public urban spaces and squares is one of the best and cheapest methods of ventilation in which wind enters the urban square and its surrounding space resulting in thermal comfort of people in that area .
Materials & Methods
The present study evaluates and compares the impacts of two effective criteria of quality and direction of prevailing wind on thermal comfort in urban public spaces. These criteria are usedin a structural and physical model ofNabovat Square in east of Tehran with the aim of determining the most important and effective criterion in geographical modeling of urban squares.Therefore, different scenarios are defined changing several factors of direction, speed and wind quality in urban space in ENVI-met 4 basic environment.Through a three-dimensional simulation and measurement of urban microclimatic conditions,the level of thermal comfort in the study area is measured based on the PMV criterion (average temperature predicted in the modeling space).
Results & Discussion
Results indicate that identifying optimal geographical and geometric orientation of a building can play an effective role in getting the maximum benefits of prevailing wind while minimizing possible hazards of high winds, and thus creating thermal comfort for citizens. Another important issue is the effect of wind direction on urban public spaces. This is one of the main factors preventing an increase in the temperature range for comfort, and thus a proper direction of the prevailing wind will lead to thermal comfort in the study area.
Conclusion
Results of quantitative analysis inENVI-met 4 basic environment indicate that the most appropriate orientation of public urban spacesin Tehran is southwestwith a rotation of about 10 degrees. Assuming that several factors such as vegetation and physical properties of the surrounding buildings are constant, the present study has evaluated the impact of factors related to the direction, quality and wind speed. The impact of other factors should be considered in future studies. Finally, it is suggested that planting trees in a suitable place can decrease direct radiation and along with thespecific properties of buildings surrounding the square provide thermal comfort for citizens.In other words, surrounding buildings and the vegetation create an independent microclimate affecting thermal comfort.
Heidar Lotfi
Abstract
Introduction In the present century, the world has been divided into six regions, and other regions falling outside this division are considered to be of little importance. Each of these regions -North America, Western Europe,Middle East (Persian Gulf), Southeastern Asia, Moscow-Leningrad axis, and India-is ...
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Introduction In the present century, the world has been divided into six regions, and other regions falling outside this division are considered to be of little importance. Each of these regions -North America, Western Europe,Middle East (Persian Gulf), Southeastern Asia, Moscow-Leningrad axis, and India-is considered to be a geo-economic power (Barzgar, 2009). Most of these regions are large manufacturers with a large export value, while only one is used for the export of raw materials. The Persian Gulfis the most important corridor used for the transportation of raw materials (oil and gas) from the region to the Strait of Hormuz and from there to the Makran (Oman) Sea and Indian Ocean. In fact, Sea of Makran and its coastline play the most important role in improving the economic position of the region (Turkan and Shahbazi, 1394: 41). The Persian Gulf connects coastal countries to open waters, which apart from the military aspects, provides them with several economic benefits including: transport of their export by water which is considered to be the cheapest type of transportation, the richest human food resource and an important mineral resource, beautiful beaches attracting many tourists and many trade opportunities in the ports and free-trade zones (Salehi, 2009). Human geography and population distribution are the first group of geographical and geopolitical variables affecting the role of Makran coast in the regional security ofthe Persian Gulf. Concentration of population in certain areas may result in vulnerability to anti-urban practices of possible enemies. However, the Makran region is considered to have some advantageswith which it can face these practices and related defense strategies. Accordingly, examining issues such as population distribution in the region and determining concentration or decentralization of population in specific areas are very important. Economic geography, indicating the concentration of economic activities in the region, is the second variable affecting the role of Makran coast in the regional security of the Persian Gulf. The spatial distribution of industrial hubs throughout the region and provinces of neighboringcountriessignificantlyimpactsselected strategies andtheir roles in the regional security. Concentration of industrial hubs in a single region makes the country more vulnerable and necessities more conservative roles. Similarly, concentration of mineral resources (such as oil and gas resources) in a singleregion and the presence of strategic competitors in neighboring countries raises the issue of defense capabilities nations need. On the other hand, the more a region is geographically difficult to occupy, the more that region is important in terms of security. The presence of mountains, forests, deserts and communication networks in an area greatly reduces its permeability. Examining components of physical geography inMakranCoast can result in greater understanding ofits important role in security of the region. It should also be noted that the principle of decentralization can be implemented in this region which once more indicate the importance of the area in the security of the Persian Gulf. Extensive lands,and the presence of vast deserts and plains makes decentralization possible. Moreover, sparse population in many areas of the region significantly impacts the process of designing defense or offensive security strategies. Results and discussion According to the SWOT analysis diagram, the most important roles of Makran Coast in Regional Security of the Persian Gulf includes: 1- Defensive Role (WT)which pays attention to security capabilities of Makran Region in regard to threats in the Persian Gulf and seeks to improve domestic capabilities and deterrence against external threats. 2- Competitive Role (ST) which is related to the status of Iran outside its territory and evaluates negative points (threats) related to this status. This role aims to increase deterrence against external threats as much as possible. 3- Conservative Role (WO) which seeks to take advantage of opportunities in Makran Region and compensate for security weaknesses inthe Persian Gulf. Conservative Role is related to the internal situation of Makran region. 4- Offensive Role (SO) can rely on internal strengths and create a kind of synergy in Makran Region. To play such a role, the region must take full advantage of external opportunities using its capabilities. Conclusion The following variables affect the role of Makran region in the security of the Persian Gulf: - Human geography and a sparse population affecting the selection of defensive or offensive strategies. - Economic geography and concentration of economic activities in the region which require a conservative role and defensive strategies. - Physical geography (a combination of mountains, forests and deserts) creating a permeablecommunication network and anespecially important position in the security of the region. - Regional geography which affects national security strategies. The offensive dimension of regional geography increases the expenses related to the security role.
