Ramin Kiamehr
Volume 5, Issue 20 , February 1996, , Pages 57-61
Abstract
In recent decade, great progress has been made in diversification and completion of surveying software, and utilization of these software programs has become common as a major tool. The aim of this paper is to review the gamut of available software programs in the field of surveying that can be run on ...
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In recent decade, great progress has been made in diversification and completion of surveying software, and utilization of these software programs has become common as a major tool. The aim of this paper is to review the gamut of available software programs in the field of surveying that can be run on personal computers, determine major parameters such as necessary computer hardware and operating system, and compare the cost of the minimum and maximum of structure required for implementation of such software. In short, this paper can act as a suitable guide for surveying organizations in selection of new software programs.
Eghbal Mohammadi; Mamand Salari; Hiva Shirzadi
Volume 20, Issue 79 , November 2011, , Pages 58-60
Abstract
The major part of Iran's land is mountainous. One of the dangers that always threatens these areas is hillside instability. The occurrence of this phenomenon entails a great deal of damage to the hillside lands exploited by human beings every year. In this context, one of the most dangerous instabilities ...
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The major part of Iran's land is mountainous. One of the dangers that always threatens these areas is hillside instability. The occurrence of this phenomenon entails a great deal of damage to the hillside lands exploited by human beings every year. In this context, one of the most dangerous instabilities is the landslide phenomenon. Kurdistan province and specially the studied area (Baneh) as a part of the province, is one of the areas susceptible to landslide due to certain geological, topographic and climatic conditions along with human factors in some places. Gardaneh Khan, Savan, Sabadlu and finally Alut can be referred to as being amongst the most important of these landslides. Therefore, identifying the landslide process along with identifying, investigating and determining the causes of landslides in the regions of the country seems to be necessary. In this study, firstly, the nature of landslide phenomenon and their occurrence factors and then the introduction of landslides in Baneh city are discussed. At the surface of the study area, the role of lithologic factor such as sensitivity of loose formations, degradation of vegetation, fall of snow and rain, permeability, lateral digging of rivers with high flow rate, road construction, and proximity to the main faults (young Zagros fault and Piranshahr fault) are among the factors causing landslides.
Akram Rabi'ee
Volume 7, Issue 27 , November 1998, , Pages 58-64
Abstract
One of the concerns in the second half of the twentieth century is the issue of increase of using abbreviations and acronyms. From the natural geographic point of view, the main reason of this increase is related to international organizations such as the UN as well as inclination toward conducting multi-discipline ...
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One of the concerns in the second half of the twentieth century is the issue of increase of using abbreviations and acronyms. From the natural geographic point of view, the main reason of this increase is related to international organizations such as the UN as well as inclination toward conducting multi-discipline and multi-organizational research in the framework of research groups. Unfortunately, in many books and papers the main meanings of abbreviations do not exist. Therefore, a list of abbreviations we deal with in many natural geographic sources has been presented here. Abbreviations of journals can be found in the World List of Scientific Periodicals, and a list of abbreviations of organizations is available in Buttress’s World Guide to Abbreviation of Organizations (London, Leonard Hill, fifth edition, 1975).
Mohammad Akbari; Khodayar Sepahvand; Mahdi Karimi
Volume 23, Issue 89 , May 2014, , Pages 61-66
Abstract
The present article evaluates condition of currents, sedimentation and erosion regime in Kuh-Mobarak coasts. Modelling was performed using MIKE-21 software and the hydrological information received from Geographic Organization of Armed Forces. Moreover, last year’s satellite and aerial imagery ...
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The present article evaluates condition of currents, sedimentation and erosion regime in Kuh-Mobarak coasts. Modelling was performed using MIKE-21 software and the hydrological information received from Geographic Organization of Armed Forces. Moreover, last year’s satellite and aerial imagery of Kuh-Mobarak are used to evaluate changes in the coastline. In sediment transport studies, changes in depth of some northern and southern profiles of Kuh-Mobarak port are evaluated using information related to hydrographical periods. Modelling was performed to understand the hydrodynamic situation and current in the area. Afterwards, the model was validated and calibrated in accordance with field measurements. In the proposed model, dominant current at the beginning of the coastline has a South East- North West direction, while there is a south to north direction at the end of the coatline. Comparing aerial and satellite imageries of different time periods, we can distinguish coastline changes, erosion points, coast sedimentation. Therefore, 1968 and 1995 aerial imagery and 2010 Geoeye satellite images were applied.
Azadeh Zaeri Amirani; Alireza Sofyanian
Volume 21, Issue 83 , November 2012, , Pages 65-69
Abstract
Accessing correct and timely information about urban land use and coverage is especially important for urban planning and management, achieving sustainable development in urban areas and optimal application of land.Impenetrable surfaces are a part of urban coverage with an effective role in changing ...
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Accessing correct and timely information about urban land use and coverage is especially important for urban planning and management, achieving sustainable development in urban areas and optimal application of land.Impenetrable surfaces are a part of urban coverage with an effective role in changing landform and the quality of urban environment. Regarding the importance of such surfaces, different methods of mapping impenetrable surfaces and investigating its changes with satellite imagery exist. These methods can be classified into five general groups: subpixel classification, neural network, classification with VIS model, regression tree model, and spectral composition analysis. Generally, each of these methods have their own advantages and disadvantages, but they are mostly used to detect and classify impenetrable surfaces. The present article investigate impenetrable surfaces and their importance, along with different methods of mapping these surfaces.
Hasan Lashkari; Mahdi Khazaie
Volume 23, SEPEHR , July 2014, , Pages 70-79
Abstract
In order to investigate synoptic patterns of heavy precipitations in Sistan va Baluchestan province, 24 year (1987-2010) daily data of 6 synoptic stations was retrieved from meteorology organization. Moreover, data like sea level pressure, geo-potential elevation of 500 and 850 milibars were exploited ...
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In order to investigate synoptic patterns of heavy precipitations in Sistan va Baluchestan province, 24 year (1987-2010) daily data of 6 synoptic stations was retrieved from meteorology organization. Moreover, data like sea level pressure, geo-potential elevation of 500 and 850 milibars were exploited from NCAR/NCEP database and then required maps were prepared in Grads software. Generally, two patters have resulted in the heavy precipitations in this province.
In the first pattern which resulted in precipitations of December12, 1995, a cyclone with contour plot of 1017.5 and 1020 milibars crossed the Arabian Sea, 24 hours before the precipitation and caused humidity spreading toward the area. In 850 milibars, a cyclone above the country results in cold weather flow and a low pressure system with a 1500 geopotenial meter contour plot passed the Bangla Gulf and the Arabian Sea and supply the necessary humidity conditions for rising in this equilibrium level.
In the second pattern which resulted in precipitations of June 5, 2010, a large low pressure system is formed 24 hours before the precipitation over southern part of Asia, which also influence south eastern and southern parts of Iran. 24 hours before the precipitation, a low altitude center covers the area under study and supply humidity and instability. On the day of precipitations, study area in 850 and 500 milibars are affected by a trough of 1475 and 5850 geopotenial meter contour plot and results in precipitation of this pattern.
Seyyed Hossein Mir Musavi
Volume 19, Issue 73 , May 2010, , Pages 74-77
Abstract
One of the most important problems in the field of agricultural activities is water scarcity or water resources issues. In this context, only those countries that utilize scientific methods in supplying the water needed for crops have been able to overcome these problems. In this study, we tried to evaluate ...
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One of the most important problems in the field of agricultural activities is water scarcity or water resources issues. In this context, only those countries that utilize scientific methods in supplying the water needed for crops have been able to overcome these problems. In this study, we tried to evaluate the application of meteorological studies in estimating the water requirements of the desired crops (wheat and potato) in Tabriz region during different stages of growth. For this purpose, the ETP (plant evapotranspiration potential) was first determined using long-term statistics, and then, using the FAO organization tables, the plant coefficients for each of the crops were extracted. Finally, in order to plan for the supply of water resources, the effective rainfall in the region has been studied, and by subtracting the amount of water required from effective rain, the amount of water deficiency in the region has been identified.
Mahmood Davoodi; Naser Bay; Omid Ebrahimi
Volume 22, Issue 88 , January 2014, , Pages 100-105
Abstract
Traditional methods of climatic classification are very diverse. Despite traditional and comparative importance, these methods have weaknesses which impair their comprehensive performance. Natural potentials as the background of human activities form the basis and foundation of many environmental programs ...
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Traditional methods of climatic classification are very diverse. Despite traditional and comparative importance, these methods have weaknesses which impair their comprehensive performance. Natural potentials as the background of human activities form the basis and foundation of many environmental programs and land use plans. Sustainable development needs careful planning based on resource constraints and abundances, and local development potentials are determined by its climate. Due to the significant topographic diversity and geographic expansion of Iran, providing a logical classification based on this country's natural realities is quite difficult. Due to topographic diversity of Mazandaran province, its climatic classification is not easily executable. The present article seeks to determine the climate of Mazandaran province according to Litinsky model. We tried to use different methods for climatic classification of the province, yet finally we focused on Litinsky model and explained it. Litinsky model use three fundamental elements of temperature, precipitation and Berry coefficient. Then, it takes advantage of auxiliary indicators including adaptation, continuity of dry season and solar radiation condition to provide a comprehensive classification. To do so, data obtained from 10 synoptic and climatologic stations in Mazandaran during 1984-2005 statistical period was used in SPSS environment. Finally, climate of Mazandaran province stations were determined and proposed in table 4.
Rozina Hanifi
Abstract
Increasing the use of fishery resources and increasing global demand for food has created the need for a new look at the nature and the potential of the aquaculture sector andthis question is raised that how far aquaculture can increase protein production and human food security in the long run. The ...
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Increasing the use of fishery resources and increasing global demand for food has created the need for a new look at the nature and the potential of the aquaculture sector andthis question is raised that how far aquaculture can increase protein production and human food security in the long run. The present study is an attempt to provide a part of the information requirements regarding the potential of aquaculture and the estimation of ecological and socioeconomic power of SARDASHT city in west Azerbaijan province for breeding cold water fish and mainly rainbow trout. This study has been conducted with the aim of locating and prioritizing SARDASHT’s underground water resources in West Azerbaijan province for the construction of rainbow trout breeding pools using geographic information system (GIS). For this purpose, after reviewing the sources and previous studies done in this field, effective measures in locating trout breeding pools were classified as: (1) ecologic- water (water’s rate of flow, type of water source, water temperature, PH), Shape of the land (slope, altitude), land use, distance from accidental areas (distance from flood areas, distance from earthquake areas); (2) economic - market proximity, profitability, and access to labor force; (3) social- employment, type of Exploitation ownership, population density; and (4) Infrastructure - proximity to the road, proximity to electricity, or proximity to telephone lines, and the like. Finally, it has been carried out using collected data and providing information layers in the GIS environment. The results revealed that out of a total of 208 sources of water being exploited, 141 sources of water had the ability for breeding trout.
Mohsen Ahmadkhani; Mohammad Reza Malek
Abstract
Extended Abstract
Despite of widespread usage of Global Positioning System (GPS), this system is considered inefficient for indoor areas. Although the most prominent positioning system is Global Positioning System, this system uses some electromagnetic waves which are unable to pass thick obstacles ...
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Extended Abstract
Despite of widespread usage of Global Positioning System (GPS), this system is considered inefficient for indoor areas. Although the most prominent positioning system is Global Positioning System, this system uses some electromagnetic waves which are unable to pass thick obstacles such as concrete roofs and trees [1]. Thus, it cannot be considered as a robust infra-structure for indoor positioning purposes. Since, other signal networks like Wireless Local Area Network (WLAN) can be an appropriate alternative for indoor spaces. In addition, widespread usage of mobile smart instruments has provided the possibility of ubiquitous system’s development.
Several methods have been proposed to obtain indoor positions which are generally based on received radio waves from fixed points. Time of Arrival (TOA), Time Difference of Arrival (TDOA), Angle of Arrival (AOA) and Location fingerprinting can be used in this case. It is noteworthy that some of these methods are not really appropriate for indoor areas which maybe contain complex structure [2]. Time of Arrival, Time Difference of Arrival and Angle of Arrival methods use triangulation techniques so direct lines of sight are desired for them. And also acquisition of accurate time and angle of received signal without professional instruments, which are usually expensive, sounds almost impossible. Furthermore, for most of indoor areas such as commercial centers and museums direct line of sight is rarely available and signals are likely to be affected by multipath phenomena [3].
In recent years methods based on Inertial Measurement Units (IMU) have been proposed and programmed [4], [5]. These methods which are usually called Pedestrian Dead Reckoning (PDR) often employ sensors such as Gyroscope, Accelerometer and Magnetic sensors to obtain the position of the client [6]. It can be regarded as an important limitation along the objectives of the Ubiquitous systems. Such systems are restricted to clients equipped by platforms having these expensive modern sensors. Therefore, the methods using WLAN signals are usually preferred for location based services.
WLAN Fingerprinting can be regarded as a most appropriate technique that uses signal strength as an identification parameter, which can be simply obtained. Furthermore, fingerprinting does not have any special infrastructure to establish and it can be conveniently laid out. In order to apply this method there are several ways to recognize the pattern of signals received from active transmitters. Stochastic method, Artificial Neural Network and K-Nearest Neighbor methods are some of classic pattern recognition techniques [7] that were investigated in this study. In this article these three methods were scrutinized and relatively compared, eventually an enhanced method has been offered. After using several data sets in order to assess the pattern recognition techniques, the proposed method got the first rank of the accuracy and also other techniques were ranked based on the accuracy.
One of the most important differences between indoor positioning systems might be utilizing of various algorithms to recognize the spatial pattern. In this study, three popular classic methods including Probabilistic algorithm, Nearest Neighbor and Artificial Neural Network were investigated. The flowchart presented in Figure 1 has depicted the major steps of the study.
Figure 1. The flowchart of the study.
This study focuses on Nearest Neighbor in Signal Space method as the most accurate method among all and tries to enhance the output accuracy of the method. NNSS Method computes the difference between received signal strength in a point from each transmitter and the received strength of that signal in the rest of the sample points (Equation 1).
(1)
Where Sij be jth sample point of the database from ith transmitter and Si received signal strength from ith hotspot in online phase and also for m hotspots and n sample points, i= 1,2,…,m and j=1,2,…,n [8].
By applying this formula, the most likely sample point as the location of the observer can be obtained. Since the number of sample points in the design of the model in offline phase is limited and the distance between two adjacent sample points is constant in the whole model, the accuracy might be affected. Regarding these limitations, in order to increase the output accuracy of the system, the medium of first and second candidate location points was proposed as the position of the user. After applying this change, the highest accuracy was acquired (Figure 4). The study area was the third floor of the building of Geomatics faculty of K.N.Toosi university of Technology (Figure 2). For this building with dimensions of 70×14 meters, totally 6 hostspots with reasonable distribution, covering the whole area, were taken into account. The best distance between each adjacent pair was 0.9 m and for each sample point four directions were observed and recorded in to the database and also JAVA programming language was chosen to develop the user friend software. Figure 3 depicts an instance of the database.
Figure 2. Plan of the study area.
Figure 3. A part of the produced database.
In order to evaluate the accuracy of each method, observations in the online phase were categorized in 6 separate classes containing 10, 20, to 60 obser-vation in each class. Based on the output results of the system, although the accuracy of Artificial Neural Network raised up to 2.7 m by increase in the number of observations, it showed the worse accuracy among all methods. Probabilistic and KNN methods with final accuracy of 1.8 and 0.9 meters respectively were more accurate than ANN. Our extended Nearest Neighbor method was the most accurate method almost in all sets of observations. In the first observation class, ANN with 3.6 m, KNN and Probabilistic methods with 2.7 m were not really reliable to locate the position of the user, however, extended KNN with 1.5 m seemed more acceptable than the rest of methods (See Figure 4).
Figure 4. The behavior of accuracy trend in all methods in the considered sets of observation.
Mohammad Baaghideh; Gholamabbas Fallah Ghalhari; Hasan Hajimohammadi; hasan rezaei
Abstract
Extended Abstract Introduction The climatic conditions of each site play an important role in the dispersion of humans, animals and plants. Therefore, any activity or planning in different economic, agricultural and industrial fields at the ground level is not feasible without the knowledge of ...
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Extended Abstract Introduction The climatic conditions of each site play an important role in the dispersion of humans, animals and plants. Therefore, any activity or planning in different economic, agricultural and industrial fields at the ground level is not feasible without the knowledge of the climate. For this reason, climatic zoning and recognition of the most important factors and factors affecting each area is one of the ways of recognizing the climatic identity of the area. Lack of knowledge of the sub-regions of the country fails to meet the economic and agricultural plans of mankind. In general, the climate of a region is the average of the weather conditions in the region. Access to the average weather conditions in a specific location requires long-term weather information. Data and Methods In order to obtain the correct and comprehensive knowledge of the climate of Hamedan province, climatic zoning was performed with new statistical methods such as factor analysis and cluster analysis during the 20 years period (1993-2013). For this purpose, 23 variables were selected from 8 meteorological stations. Then, using a digital elevation model, a multivariable regression was applied between the meteorological parameters and the digital elevation model. Finally, a zonal matrix with a dimension of 23 × 88 was obtained. Since the aim of this research was the climate zone of Hamadan province based on altitude, a digital elevation layer (DEM) was used with a resolution of 90 meters. In the following, for climatic zoning, a regression relationship was made between climate parameters and length, width and height of the area. To identify the climatic sub-regions of Hamedan province, the raster data obtained from the zoning were converted to point data. Then, based on the analysis of the main components, the points were analyzed by clustering method and the dominant factors were identified. In this research, the resolution of each of the pixel was 15 × 15 km and a matrix with dimensions of 23 × 88 was developed. Finally, this matrix was clustered into the MATLAB software using the Wardclustering method. Results and discussion By studying 23 climatic elements, 5 climatic factors were identified and their maps were drawn. These factors include temperature, visibility, rainfall, thunder storm and radiation. Among these factors, the first factor with 37% of the variance of the total data has the most important role in determining the climate diversity of the province. This factor is most commonly observed in the South and Southwest of the province and with moving to the North and Northeast of the province, this factor is severely reduced. Conclusion According to the dendrogram, 6 climatic regions were identified and the characteristics of each separate area were investigated.
Saeed Balyani; mohamad salighe
Abstract
Abstract
The aim of Exploratory SpatialData Analysis (ESDA) is, distinguishing the difference between random andnon-random patterns. In this study, 37 meteorological and synopticstations in the northern region of the Persian Gulf (Mondand helle basin) were used to analyze the spatial changes of precipitation ...
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Abstract
The aim of Exploratory SpatialData Analysis (ESDA) is, distinguishing the difference between random andnon-random patterns. In this study, 37 meteorological and synopticstations in the northern region of the Persian Gulf (Mondand helle basin) were used to analyze the spatial changes of precipitation regime, monthly and quarterly. According to the drawnprofiles on monthly rainfall in different seasons along the meridiansand orbits, the precipitation raised from the west to the east of the basin. Also, along the meridians, monthly precipitation had a decreasingtrend from the north to the south of the study area. The ESDAof precipitation data in the study area showed that meancenters and standard deviational ellipse are located in the center and nearthe high rainy areas in winter and spring. But, thisbehavior was very different in summer, because mean centers andstandard deviational ellipse of precipitation tended towards the south and the southeast of the study area. The analysis of spatial autocorrelation showedthat high-high clusters of monthly precipitation in most months of the year except for two months of summer (July and August) are located inthe east and the northeast and low-low clusters are locatedin the west, south and south West of the basins.
Ali Akbar Damavandi; Mohammad Rahimi; Mohammad Reza Yazdani; Ali Akbar Noroozi
Abstract
Abstract
Drought is a natural phenomenon that occurs in almost all climates of the world. The effects of this creeping and gentle phenomenon are higher in arid and semi-arid regions due to their less annual rainfall. In the present research, in order to monitor the location of drought, time series NDVI ...
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Abstract
Drought is a natural phenomenon that occurs in almost all climates of the world. The effects of this creeping and gentle phenomenon are higher in arid and semi-arid regions due to their less annual rainfall. In the present research, in order to monitor the location of drought, time series NDVI ((Normalized Difference Vegetation Index)) and LST (land surface temperature) of the Terra satellite’s MODIS (Moderate Resolution Imaging Spectroradiometer) sensor were used during the growing seasons (March, 21 to September, 21) of the years 2000 to 2014 in Markazi province. For this purpose, the VCI (Vegetation Condition Index) and TCI (Temperature Condition Index) indices were created on a monthly basis based on the NDVI and LST 15-year time series, and the VHI (Vegetation Health Index) index was extracted based on the combination of the two indices. As a result, drought severity maps based on the VHI index were extracted in five categories: 1- Very severe 2- Severe 3- Moderate 4- Mild 5- no drought, and variations of these classes were investigated in VHI time series. A review of time series resulted from VCI and TCI showed that there was a meaningful relationship between NDVI and LST variations. According to the results of drought severity classification maps, VHI index had the highest drought intensity in the years of 2000 and 2001 and the years of 2004 and 2007 had the lowest drought severity. Also, the highest and the lowest drought severity were observed in May and September, respectively. The highest percentage of the areas of drought classes belonged to drought-free (56%), mild (19%), moderate (15%), severe (8%) and very severe (2%). Comparing the results of this research and the report of the Meteorological Organization shows the high precision of the method of using the VHI remote sensing index in agricultural drought monitoring. The result is that, remote sensing indicators of drought monitoring (such as VCI, TCI and VHI) can greatly help decision-makers and planners in monitoring agricultural drought by eliminating the weaknesses of point-based approaches.
arash zandkarimi; Davood Mokhtari; Shaida Zandkarimi
Abstract
Extended Abstract Introduction The prediction of the occurrence of floods and the reduction of damages caused by it is strongly influenced by the modeling of physical phenomena and the spatial-temporal distribution of precipitation. The purpose of the research was to optimize the rainfall gauging network ...
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Extended Abstract Introduction The prediction of the occurrence of floods and the reduction of damages caused by it is strongly influenced by the modeling of physical phenomena and the spatial-temporal distribution of precipitation. The purpose of the research was to optimize the rainfall gauging network in Kurdistan province using Kriging estimation variance and taking into account the topography of the area. In this study, to optimize the rain gauging network in Kurdistan province, rainfall data of the rain gauging, synoptic, and climatology stations were used. In order to reduce the costs, stations close to each other that are located in the same height range and also have the same error variance, were removed from the existing network. In order to reduce the maintenance cost of the stations, after clustering of the area, 8 stations whose removal had little impact on the accuracy of the data, were identified in the province. Then. In order to strengthen the network, the optimization of new stations was put on the agenda and 28 points were set as the proposed stations. Materials and methods After reviewing the existing stations’ data, 145 stations were selected for the analysis and optimization of the existing network. After selecting the normal data and spatializing them, due to the large extent of the area and the variability of the average annual precipitation, Kurdistan province is divided into smaller regions with less variations in the average rainfall. The regional division or clustering of stations is carried out using the functions available in the ArcGIS 10.2.2 software and based on the main catchment basins. In the next step, the spatial distribution of rainfall and the variance of the errors in all clusters are calculated separately. Given the importance of highlands in receiving rainfall and supplying water, the distribution of rain gauges on elevation layers has been studied. At this stage, redundant stations were eliminated, and stations which are located in close proximity of each other, and are located in the same elevation range and also have the same error variance, can be eliminated too. At the final stage, adding new stations and strengthening the network took place. At this stage, the priority is to build the station for areas where the variance of the errors is high. After adding each station, the error variance of the whole system is calculated again. Adding a new station to the network will continue as long as the network error reaches its minimum. Discussion 1-Normality test of data After spatializing the rainfall data, their normal distribution was investigated using the Kolmogorov – Smirnov test. The results show that the distribution of data at 95% level does not have a significant difference with a normal distribution. 2- Division of the region and clustering of stations In this study, using the region’s digital elevation map, and based on the analyses made in the software ArcGIS 10.2.2, clustering of stations and division of the region was carried out. The entire area of interest is divided into 8 clusters. 3- Calculating the Kriging error of the existing network The amounts of the rainfall data error can be obtained by calculating the Kriging error of the existing network. As mentioned in the previous sections, the calculation of the error in the Kriging method is a function of semi-variogram (spatial structure) of the variable and this feature increases the estimation accuracy of the variable error. 4- Distribution of the stations on elevation layers and determination of the redundant stations By studying the distribution of the stations on altitudes, stations which had no impact on the accuracy of data extraction were removed. The candidate stations for removal were located in a same range of elevation, and showed similar error values. In order to be sure of the decision taken, by eliminating each station, the overall error of the network in each cluster is calculated, and an increase in the error values represents the wrong station is being removed. 5- Adding the proposed stations and calculating the variance of the new network error Adding new stations to the network is done based on the Kriging variance. The priority of the station construction is for areas that display a high error. In the Kriging error variance method, adding a new station to the network is done based on Eó2 (error variance), in a way that points with equal error variance or greater than the value of data variance is considered as the first priority for the construction of the station. The points whose error variances are between the variance of data and ½ of the variance of data, is the second priority and finally, the third priority belongs to the points whose variances are between ½ and ¼ of the variance. In this research, based on Kriging variance, 28 stations have been proposed to strengthen the rain gauging network in Kurdistan Province. Conclusion Given that precipitation is considered as the main entrance to the planning of sustainable water resources development, in this study, the optimization of rain gauging station network in Kurdistan province was investigated using the Kriging error variance. In previous studies, generally, entropy has been considered as the main model for network modification, therefore, due to the limitations of these methods in not using the semi-variogram features, in this research, the geo-statistic method based on kriging error variance was used due to its high accuracy. The amount accuracy increase in this method depends to a large extent on the semi-variogram features (spatial structure) of the precipitation, which can be used to calculate the error variance rate for the new station before the construction and inventory of the station. In order to strengthen the network, the optimization of new stations was put on the agenda and 28 points were set as the location of the proposed stations. For practical comparison of the results, the error variance values were calculated before and after the addition of the proposed stations, the average error variance of the annual precipitation in the province decreased by 11%, with the largest decrease belonging to the central part of the province with 24.03%.
Masoud Torabi Azad; Abbas Ali Aliakbari Bidokhti; Hossein Salehianfar
Abstract
Many hydrological conditions in the seas depend on temperature variation, and the rate of this parameter is an important determinant in the environmental conditions of each area. The variations in temperature and surface wind causes changes in the density of the sea water, and the change in density affects ...
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Many hydrological conditions in the seas depend on temperature variation, and the rate of this parameter is an important determinant in the environmental conditions of each area. The variations in temperature and surface wind causes changes in the density of the sea water, and the change in density affects the stability rate and mixing of the sea water column. In this research, the mutual effect of sea surface temperature (SST) on surface wind speed in the southern Caspian region (Mazandaran province) has been investigated. First, the sea surface temperature data was collected by the AVHRR sensor of NOAA satellite and surface wind speed data was collected by QuikSCAT satellite for an area of 340 × 220 square kilometers in the southern Caspian Sea. After analyzing the satellite data for sea surface temperaturel, its monthly and seasonal variations were drawn by Tecplot software for this area. It was found that the average seasonal temperature (spring and summer) of the eastern coast of southern Caspian Sea is 0.87 degrees centigrade more than that of the eastern coast. In order to investigate the mutual effect of the sea surface temperature on surface wind speed, four stations, A and D (in the western region), B and C (in the eastern region) were selected on the southern Caspian Sea. Then, the graph of temperature time series, temperature difference between the four stations, time series of wind speed and time series of wind speed difference between the four stations from 2000 to 2005 were plotted and compared for the spring and summer seasons. The results indicate that, with increasing temperature difference between the four stations, the difference in speed also increases in 80% of the cases for the summer and in 66% of the cases in the spring season.In these two seasons, because of the decrease in the activity of atmospheric systems, the temperature difference between the two stations has a significant effect on improving the wind speed difference.Average wind speed difference in the statistical period of 2000-2005 at the stations is 0.7 m/s for the spring and 1.37 m/s for the summer season.
Saeed Ojaghi; safa khazai
Abstract
Extended Abstract
Land use/cover (LULC) change detection is one of the most important applications in the remote sensing field, providing insights that inform management, policy, and science. In the recent decade, development of remote sensing systems and accessibility to high spatial resolution images ...
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Extended Abstract
Land use/cover (LULC) change detection is one of the most important applications in the remote sensing field, providing insights that inform management, policy, and science. In the recent decade, development of remote sensing systems and accessibility to high spatial resolution images has associated with the improvement of digital image processing. The advantage of high spatial resolution remote sensing imagery further supports opportunities to apply change detection with object-based image analysis, i.e. object-based change detection – OBCD.
OBCD analysis in comparison with pixel-based techniques provides a more effective way, especially in high spatial resolution imagery to incorporate spatial, spectral, textural and geometry feature that can identify the LULC change in comparison with pixel-based technique. OBCD approach is classified into for categories: (i) image-object, (ii) class-object, (iii) multi- temporal object, and (iv) hybrid change detection. Different algorithms and features can be employed in the process of image classification for OBCD. Therefore, the choice of algorithm and optimization features are major challenges in OBCD. This paper has introduced an object- based change detection method based on the machine learning algorithm, which can overcome the traditional change detection method limitation and find the interested changed objects. In this paper, multi-temporal object approach is utilized and high spatial resolution imagery, GeoEye-1 and Quick Bird-1 satellite images were acquired during 2002 and 2015, covering a region of the Geshm Island which were used to detect the meaningful detailed change in the study area. As an essential preprocessing for change detection, multi-temporal image registration with the accuracy of less than one second of a pixel is applied. Also, radiometric correction is performed using histogram matching algorithm in ENVI Software. In the Next step, a number of texture features of images such as mean, variance, entropy, homogeneity, momentum and such are extracted from two images. To reduce the input features space, PCA algorithm is employed and the result of this process is used in the segmentation process. The two images are incorporated with PCA output and are used as inputs feature to segmentation. Segmentation is the first step in OBCD. It divides the image into larger numbers of small image objects by grouping pixels. The segmentation algorithm is a region-merging technique. It begins by considering each pixel as a separate object. Subsequently, adjacent pairs of image objects are merged to form bigger segments. The merging decision is based on local homogeneity criterion, describing the similarity between adjacent image objects. Correct image segmentation is a prerequisite to successful image classification. At the same time, this task requires explicit knowledge representation. Furthermore, optimal segmentation results are depended on not only the choice of segmentation algorithm or procedure, but are also often influenced by the choice of user-defined parameter combinations which are required inputs for many segmentation programs. The segmentation has been done using multi resolution segmentation algorithm which involves knowledge-free extraction of image objects. Multi-resolution segmentation begins with single pixel objects and employs a region-growing algorithm to merge pixels into larger objects; pixels are merged based on whether they meet user-defined homogeneity criteria. Each multi-resolution segmentation task must be parameterized by the user and involves settings of three parameters: Scale, Color-versus-Shape, and Compactness-versus-Smoothness. In this paper the process of segmentation is performed in four different levels using Ecognition software and finally, the level with better output with scale of 100 is selected to provide the change map. The scale values were determined through an iterative method. The color/shape was set to 0.6/0.4 and compactness/sharpness was set to 0.5/0.5 for the selected level. Color and shape weightage are inter-connected to each other. If color has a high value, which means it has a high influence on segmentation; Shape must have a low value with less influence. If both parameters are equal, then each will have roughly equal amount of influence on segmentation outcome. In addition, texture, spatial and geometrical features from the segmented image are extracted. Feature space Optimization (FSO) tool available in Ecognition software have been used to calculate optimum feature combination based on class samples in four classes including: ”barren to road”, ”barren to building”, barren to vegetation” and “barren with no change. It evaluates the Euclidean distance in feature space between the samples of all classes and selects a feature combination resulting in best class separation distance. In this study, the performance of the proposed RF-based OBCD method is compared with the conventional methods such as support vector machine (SVM) and KNN. The commonly used accuracy assessment elements include overall accuracy, producer’s accuracy, user’s accuracy and the Kappa coefficient. The overall accuracy of the change map produced by the RF method was 86.57%, with Kappa statistic of 0.79, whereas the overall accuracy and Kappa coefficient of that by the SVM and NN methods were 83.76%, 0.75 and 75%, 0.63, respectively. Experimental results show that overall accuracy and kappa coefficient obtained from the proposed RF-based OBCD method improve 3% and 18%, 2% and 10% respectively compared with SVM and KNN improved. The results indicated that object base change detection method can be performed more accurately and reliably in the high-density region if it uses image with high spatial resolution. Also, selection of classification algorithm has very impressive effect on the providing change map.
seyyede samira jafari pour; Nazila Mohammadi
Abstract
Extended Abstract
Introduction
Ionosphere is a region of ionized plasma that extends at an altitude of 80 to 1,200 km above the earth's surface. The ionosphere consists of free electrons and ions formed during the ionization process. Total electron content (TEC) in the ionosphere is reported in TECU ...
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Extended Abstract
Introduction
Ionosphere is a region of ionized plasma that extends at an altitude of 80 to 1,200 km above the earth's surface. The ionosphere consists of free electrons and ions formed during the ionization process. Total electron content (TEC) in the ionosphere is reported in TECU units. Each TECU is equivalent to 1016 electron units per square meter. Ionosphere is highly sensitive to any atmospheric turbulence, and thus is considered to be an atmospheric event sensor. The present study seeks to investigate the effect of space and temperature on the amount of total ionospheric electron content in order to accurately estimate TEC value. To reach this aim, variations in latitude and longitude are decomposed for a given period of time using the process of transforming wavelet to frequency component and modeled using a variety of artificial neural networks.
Materials and Methods
Here, after separating the location and temperature parameters in each region, ionospheric electron density is estimated for each spatial and temperature parameter separately and also as a combination using the capabilities of artificial neural networks and wavelet transform. TEC value for each location and temperature parameter is extracted from the ionospheric maps and then used as input data in the suggested method. These maps show ionospheric electron content. The standard format of ionospheric maps, which contains TEC values is called IONEX. These files are received from the website of Iranian National Mapping Agency.
Results and discussion
In general, IONEX is divided into three different parts: description, TEC maps, and standard deviations of maps. TEC values are presented in a regular network. Each IONEX file includes 25 maps, the last of which is the first map of the next day. As mentioned before, TEC value gives us a better understanding of ionospheric behavior. Availability of enough data and time coverage are two important factors in understanding a phenomenon and proper evaluation of its behavior.
Conclusion
As results of artificial neural networks indicate, MLP generally has lower RMSE values. Therefore, it gives a more accurate estimation of TEC, compared to other artificial neural networks. Also compared to artificial neural networks, a combination of artificial neural networks and wavelet shows better results. The best condition of all three methods shows that compared to other methods, temperature variations give us a better estimation of TEC in ionosphere.
Saeed Amanpour; Souran Manoochehri; Mahnaz Akbari; Zahra Abbassi
Abstract
Smuggling goods as an unofficial activity has a special place in the quality of life of the country’s border villages which are under stress and suffering from the marginalization of the planning system. Considering the necessity of eliminating goods smuggling for the economic dynamism of the country, ...
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Smuggling goods as an unofficial activity has a special place in the quality of life of the country’s border villages which are under stress and suffering from the marginalization of the planning system. Considering the necessity of eliminating goods smuggling for the economic dynamism of the country, it is undoubtedly necessary to reduce and eliminate this unofficial profitable economic activity at once and without any planning to prepare alternatives from border villages which are highly dependent on smuggling goods due to the weakness of economic structures, and brings major changes In the quality of the lives of the border villagers. Therefore, following the significant reduction in smuggling of goods and its elimination, the changes in the life quality of the villagers of Marivan city’s border villages have been studied, in order for the approach of this issue to be a comprehensive understanding of the status quo to provide practical solutions to improve the quality of the lives of the villagers in the area following the elimination of goods smuggling. This is an applied research, and in terms of method is a descriptive-analytical study in which, two library and field methods have been used for collecting information based on the distribution of questionnaires and interviews. The statistical population of this study is households residing in two border villages of Khav and Mirabad, and Zaryvar where 360 households were selected from among 5223 households as sample size using Cochran formula, and the questionnaires were distributedby stratified and then simple random methodamong selected villages and their villagers. To analyze the data, descriptive statistics indices (mean) and inferential statistics tests (paired, Friedman rankings, fit-square, Kruskal-Wallis and binomial tests) have been used. The results show that smuggling of goods has been eliminated as an unacceptable phenomenon, but instead, the quality of the lives of the villagers has decreased in social and economic aspects and we are only witnessing a rise in the quality of the lives of the villagers in the physical aspect. Also, there is a significant relationship between the level of satisfaction of people with their quality of life and distance from the border and occupational dependence on smuggling, and ultimately, the established border markets as the alternative solutions have not been able to raise the life quality of the villagers asmuch as smuggling goods.
Meysam Argany; Amir Ramezani; Sadegh Elyasi
Abstract
Extended Abstract
Introduction
Remote sensing science is one of the most powerful tools for the mineral explorations and mineral resource estimation. With regard to this science, any type of rocks with structural characteristics and mineral constituents has a special spectral signature, thus, using ...
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Extended Abstract
Introduction
Remote sensing science is one of the most powerful tools for the mineral explorations and mineral resource estimation. With regard to this science, any type of rocks with structural characteristics and mineral constituents has a special spectral signature, thus, using remote sensing techniques, different types of rocks in a particular area can be recognizable based on their reflective characteristics. Remote sensing techniques are considered as one of the standard methods in geological studies due to the identification of spatial patterns of rocks as well as their speed and economic price. Pervious geological studies indicate that the study area mostly contains basalt, limestone and marble, which has resulted in physical and chemical degradation of basalt stones under the influence of some geological events. Some parts containing basalt have lost their qualities due to these degradations. Therefore, the classification and separation of high-quality basalt zones from low-quality zones is the main objective of this paper.
Materials and method
The main objective of this study is to identify high-quality basalt zones in the Dir-o-Morreh mine located 50 kilometers from Tehran city near the lake of Hoz-e-Soltan. Basalt is a dark-colored and fine-grained igneous rock composed mainly of plagioclase and pyroxene minerals. Typically, this type of rock is formed externally or in the presence of air, such as the flow of lava, and these rocks can also take form intrusively like igneous dikes or narrow pillars. The basalt in the Dir-o-morreh mine is of igneous dike basalt type. In this study, the ASTER satellite multi-spectral images were used. These images allow us to have a good spatial and spectral resolution with regard to the objectives. However, reflectance conversion and atmospheric corrections were carried out on these images before using them, in order to enhance the accuracy of the project. Aerosols contained in the atmosphere are liquid or solid particles suspended in the air, which are very important in the evaluation of satellite imagery for remote sensing. After applying pre-processing, Basalt Exploration Index (BEI) was introduced and used to identify the basalt. The BEI index has been extracted using various sources, including the basalt spectral signature provided by the department of applied mathematics and statistics of Johns Hopkins University, ASTER satellite behavior (defined by the space team of NASA and Japan) and the Earth’s data which were collected to validate the results. This index has been able to identify different basalt zones, including major extraction zones and other potentially possible zones. Moreover, this index is able to completely separate the basalt zones from the surrounding areas (mainly limestone, marble and clay rocks). At the next step, convolution and morphology filters have been applied to separate high-quality Basalt zones from the low-quality. The amount of the brightness of an output pixel from the Convolution filters is a function of weighted average of the brightness of its surrounding pixels. Using convolution with the selected kernel in satellite imagery returns a new filtered spatial image. High-pass Standard convolution filter was used in this study, which eliminates low frequencies of an image by retaining the high frequencies. The morphological nuclei used in this study are only the structural elements of this project and should not be confused with convolution kernels. In order to control the obtained results, the classified zones were double-checked on the field.
Results
The results obtained from the field studies and the identified zones are appropriately consistent with each other using the proposed index. Supervised classification was applied to improve the level of assurance and accuracy. Supervised classification is based on the idea that the user can select sample pixels in an image representing certain classes and then use image processing software using these educational samples as the referral for the classification of all other pixels in the image. This classification algorithm can be very effective and accurate and classifies satellite images in pixel-based or object-oriented form. Supervised classification can result in the preparation of two maps in two different classifications, which is has been done by using the Maximum Likelihood Algorithm. MaxVer or Maximum Likelihood is a statistical classification method that takes the weight of average value of the distance between the classes into consideration, using statistical parameters. To achieve sufficient accuracy, this algorithm requires a number of educational samples or pixels (more than 30). The primary classification includes 5 types of rocks or classes: high-quality basalt, low-quality basalt, limestone, marble stone, and clay which are designated on the map. In order to increase accuracy of the proposed method, the second map was prepared with 3 different classes (low-quality basalt, High-quality basalt, and surrounding rocks) in the second stage.
Conclusion
These maps help us in preparing a new BEI which is more accurate and more capable. It was also able to prove its capability in the latest ground operations and determining the most zones with high-quality basalt.
Ali Ahmadabadi; Amanollah Fathnia; Saeed Rajaei
Abstract
Abstract[1]
Vegetation cover has a high relationship with climatic conditions. Identification of the seasonal variation of plant growth to determine the response of ecosystems to climate change in seasonal and inter-annual time scales is decisive.To present a prediction model, 7 climatic elements including ...
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Abstract[1]
Vegetation cover has a high relationship with climatic conditions. Identification of the seasonal variation of plant growth to determine the response of ecosystems to climate change in seasonal and inter-annual time scales is decisive.To present a prediction model, 7 climatic elements including precipitation, temperature and relative humidity (maximum, average and minimum) for a 20 year period (1987-2006) were converted into spatial data in 141 synoptic and climatological stations. The combination of maximum monthly NDVI values from NOAA-AVHRR images was extracted in the same period. Then climatic elements and NDVI entered the multivariate linear regression as independent variable and dependent variable respectively. The results showed that the highest correlation coefficient between climatic elements and the amount of NDVI was 0.82 and happens in May that is the peak of greenery. The least correlation in winter is due to the lack of sufficient tree growth. Taking into account the random error, the annual correlation coefficient of the model amount with computational mode is more than 93/0. In total, the computational value of May and June for 2004 and 2005 is close to the correlation coefficient of the model, but in the winter months, the correlation coefficient decreases due to lack of greenness.In 2006, there was less prediction due to more severe dryness in the late spring (June). In winter, the role of temperature control is more than rainfall and relative humidity, but with increasing temperature and decreasing precipitation and relative humidity, the role of precipitation and relative humidity becomes positive and temperature becomes negative from the beginning of May. In the autumn, the role of precipitation decreases and the temperature is increased.
[1] - به دلیل کیفیت نامناسب متن چکیده مبسوط انگلیسیِ ارائه شده توسط نویسنده مسئول مقاله، نشریه به ناچار اقدام به ترجمه مجدد متن چکیده فارسی و انتشار آن به جای چکیده مبسوط انگلیسی نموده است.
Mojtaba Behzad Fallahpour; Hamid Dehghani; Ali Jabbar Rashidi; Abbas Sheikhi
Abstract
Abstract
Effective factors in SAR images can be divided into five general categories of radar, radar-carrying platform, channel, imaging domain and raw data processing section. In each of these factors, various physical, structural, hardware and software parameters are influential, in such a way that ...
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Abstract
Effective factors in SAR images can be divided into five general categories of radar, radar-carrying platform, channel, imaging domain and raw data processing section. In each of these factors, various physical, structural, hardware and software parameters are influential, in such a way that one can see the role of each of them in the final formed image.
Modeling, Analyzing and, in general, knowing the effect of each of these parameters, will provide a better understanding of how SAR imaging systems operate, and from this point of view, it will not only be an important step in designing and manufacturing these types of systems, but also it will provide the possibility of interpreting and analyzing these types of images. For this purpose, in the present paper, the effect of the angle of incidence and the shape of the targets which are parts of the radar and the imaging domain parameters, are simulated in SAR images. The shapes used in this simulation are cylinders, cones and cubes, which represent buildings, silos, tree trunks, etc., in the real world, so they are very abundant in SAR images. Also, for more comprehensive results, different angles of incidence of 30, 40, 45, 50 and 60 degrees have been selected for simulation. With this simulation and analysis of the results, the behavioral pattern of the above geometric shapes is extracted at different angles of incidence from the perspective of SAR imaging systems. Thus, an important step in identifying and recognizing various shapes, which is one of the most important issues in the interpretation of SAR images will be taken.
Kamran Karimi; Gholamreza Zehtabian; Marzban Faramarzi; Hassan Khosravi
Abstract
Extended Abstract Introduction Land use changes is a widespread and accelerating process, mainly driven by natural phenomena and anthropogenic activities, which in turn drive changes that would impact natural ecosystem. Because of the human population growth and its impacts, land-use patterns are changing ...
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Extended Abstract Introduction Land use changes is a widespread and accelerating process, mainly driven by natural phenomena and anthropogenic activities, which in turn drive changes that would impact natural ecosystem. Because of the human population growth and its impacts, land-use patterns are changing very fast. Most of the population in Iran depends on agriculture, so the land use changes are mostly linked to agricultural developments. In recent decades, rapid land use changes have been associated with the degradation of natural resources, especially in sensitive ecosystems. On the other hand, like many other developing countries in the world, significant land-cover changes have been occurred in Iran within two last centuries. These changes were primarily due to human activities in connection with the population increase, which forced people to clear forest for cultivation and other activities. This study tries to present the effect of irrigation systems on land use changes since over three decades. Methodology Abbas plain with a surface area of 34104 ha, is located in Ilam province near the Iran’s western border. The average of annual precipitation and temperature are 207mm and 26.1o respectively. Karkheh dam, one of the largest soil dams in the world and the largest soil dam in Iran and the Middle East, located 15 km east of Abbas plain. The Karkheh Dam is designed to irrigate 320,000 hectares of downstream land including Abbas plain. The water transfer project to the Abbas plain was launched in May 2005. In the present study area, changes in land cover were evaluated in the pre and after- exploitation period of irrigation networks of Karkheh dam to the Abbas plain in Ilam province, Iran. To obtain more accurate results, Landsat sensors imagery of TM, ETM + and OLI were used for the years of 1989, 2003 and 2013, as well as topographic maps, Google Earth images and area coverage. To classify the land use changes, supervised classification method with maximum likelihood algorithm was applied in the ENVI4.8 software. Images of all three periods were classified into five classes: rangelands, agricultural land, residential land, river bed and barren lands and hill moor. In order to determine more precisely changes, areas were obtained for two other periods. Results The classification accuracy results showed that the Kappa line was more than 87% for every three years and the overall accuracy obtained were 90.43%, 92.28% and 94.76% respectively for these years. The results also showed that barren lands and hill moor class has covered the largest area of this study place during the two periods (pre and after- exploitation), so that, it was 12344.1 hectares in the first period and 17370.5 hectares in the second one. In both study periods, the rangeland class has been destroyed, but in the second period 13.8% was destroyed more than the first one. Due to the exploitation of irrigation systems by farmers in the second period, more changes in land use have been converted to agricultural use, so that, 3671.8 hectares (55%) have been added to these lands during 10 years. The growth of residential areas was 0.27% of the study area after channelling, which was estimated 1.6 times higher than the first one. The area increase average in this class is 10.2 hectares per year. The most frequent conversion to farm use was barren lands and hill moor class. These lands have undergone a change by residents of the region due to their location between agricultural lands and a short distance from irrigation systems. A large number of land use changes can be prevented by defining the scope for agricultural land. Conclusion and Discussion In the present study area, irrigation has been in practice since over 25 years ago. Significant land-use changes have occurred in the study area in response to the Karkheh Dam from time to time affecting agricultural productivity leading to land-use changes. Unfortunately, some parts of these changes are out of schedule and unskillful and, that is significant for planners to know about these. All in all, for providing management activities and environmental programmes, accurate data on land use changes are essential. Satellite images and maximum likelihood algorithm provide the baseline data essential for proper understanding on the land-use patterns in the past and its impacts. It is also proper to understand the past land use changes ratio, and the physical and socio-economic factors behind.
Saman Nadizadeh Shorabeh; Najmeh Neisany Samany; Yaghob Abdali
Abstract
Extended Abstract Introduction There is a huge potential in the usage of renewable energy sources because these natural resources are inexpensive and harmless to the environment. Solar, wind, and geothermal energies are among the renewable energies. Solar photovoltaic (PV) technology is one of the fastest ...
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Extended Abstract Introduction There is a huge potential in the usage of renewable energy sources because these natural resources are inexpensive and harmless to the environment. Solar, wind, and geothermal energies are among the renewable energies. Solar photovoltaic (PV) technology is one of the fastest growing renewable energy technologies across the world. Solar energy is a practical and suitable technology, especially in arid areas with high solar energy potential. The first step in using renewable energy in Iran was in 1994, and since then, much attention has been paid to this type of energy in the society and the government. In Iran, 850 million tons of greenhouse gases are produced annually. Consequently, renewable energy sources such as solar energy can have a significant impact on reducing the greenhouse gas emissions. The integration of GIS and MCDA helps the decision maker to perform decision analysis functions such as ranking the options to select a suitable location so that the GIS is used as a powerful and integrated tool for storing, manipulating and analyzing the solar energy criteria. The use of the MCDA method can facilitate the evaluation and selection of the most appropriate location (s), taking into account the key criteria in the decision-making process. In this study, the optimal areas for the construction of the solar power plants have been identified in five highly optimistic, optimistic, moderate, pessimistic, and highly pessimistic levels using the spatial criteria and the OWA model. One of the most prominent features of this research in relation to the other articles is the inclusion of the concept of risk into the solar power plant site selection process to determine the optimum areas for the construction of solar power plants using the OWA model. Materials and methods The primary data used in this study include the Digital Elevation Model (DEM) derived from the Aster satellite data for the extraction of solar radiation and the region slope, the extraction of the mean land surface temperature for 2017 using the Terra Sensor MOD11A1, the preparation of the average map of the vegetation for 2017 using MODRA13A2 Terra sensor, the 1.250000 fault map prepared by the geological organization, the statistics and data of the rainfall prepared by the Meteorological Organization of Chahar mahal-o-Bakhtiari province, shapefile of road network prepared by the Organization of Roads and Urban Development, the climaticshapefile of the country prepared by the Iran Meteorological Organization, the shapefile of urban areas generated by the National Cartographic Center (NCC).The proposed methodology works by employing AHP to obtain the appropriate weights for each criterion, and utilizing OWA to extract suitable locations to varying degrees of risk. Sensitivity analysis for the criteria weights were conducted by virtue of the OAT method. Results and discussion The northern sectors of Razavi Khorasan province are endowed with cold temperatures and cold mountainous climate, which has had a substantial contribution to the increased cloudy and rainy days as well as the relatively extensive vegetation cover in this area. In this light, with respect to all ‘ORness’s, the target areas fall within the ‘very unsuitable’ and ‘unsuitable’ classes for construction of solar power plants. Moreover, the high slope factor in these areas has contributed to high levels of surface radiation, albeit, as the slope criterion is considered a constraint, the target areas are, in fact, not suitable for the construction of solar power plants. Moving southwards, the suitability of the regions, in terms of construction of solar power plants, tends to shift in the positive direction (very suitable class), which is most likely the result of the low rainfall and vegetation cover in conjunction with high surface temperatures in these areas, as opposed to their counterparts in the north. Areas falling within the very suitable class for construction of solar power plants in Razavi Khorasan can be realized by dint of calculating the percentage of area attributed to each class at ORness = 0.5 per city. The findings show that cities located towards the south and southwest of the province contribute to the highest area in the suitable class, while counties in the northern regions have the lowest share of area in the very suitable class. The highest sensitivity in locating suitable areas in Razavi Khorasan province were observed among the factors of slope, road, and urban criteria. Alterations in the weights assigned to these criteria would entail a significantly strong impact on the extent of the very suitable class. This highlights the significance of accurately determining the weights for these three criteria in Razavi Khorasan Province. Based on the findings, the rate of change in weight assigned to the of fault criteria ranges from 0 to 0.2, which in turn causes substantial change in the area of regions in the very suitable class extent. However, setting the criteria weight at between 0.2 and 1 appears to have no significant effects in the area of this class. Conclusion The results of this research indicate that the northern parts of Razavi Khorasan province are highly unsuitable and unsuitable for all of ‘ORness’ values, while a significant extent of the highly suitable class for the construction of solar power plants is comprised of sectors of the southern regions. Areas within the very suitable class corresponding to an ORness=1 comprise 5% of the class, whereas those with an ORness=0 have a 74% share. The three cities of Ferdows, Bardaskan, and Gonabad, had the highest share of the area attributed to the very suitable class (0.8-1), as maintained by a per city analysis of the area for each class. However, the cities of Dergas, Quchan, Mashhad, and Kalat had no share of the areas within the very suitable class. This most probably stems from the high geographic latitudes of said regions, which has engendered unsuitable climatic conditions in these areas. Finally, results from sensitivity analysis of the criteria showed that increases in the weights assigned to the factors of slope, road, and urban criteria, would cause a further increase in the area of the very suitable class. Stated differently, the selection of suitable locations for the establishment of solar power plants is highly sensitive to these criteria. Changes in the weight of the surface temperature criterion had no considerable effect on the area of the very suitable class. Moreover, shifts in the weight allotted to solar radiation and precipitation in the province, ranging from 0 and 0.6, brought about substantial changes in the area of the very suitable class. Whereas, shifts within the 0.6–1 range had no significant effects on the area of the very suitable class.
Rasool Afzali; Zahra Kateb Azgomi
Volume 21, Issue 84 , February 2013, , Pages 133-144
Abstract
In every society, having leisure time is considered one of the most important rights of people. Apart from suitable job and reasonable income, every single person of the society must have the opportunity to enjoy leisure time. The necessary legal conditions must be created for every one so that they ...
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In every society, having leisure time is considered one of the most important rights of people. Apart from suitable job and reasonable income, every single person of the society must have the opportunity to enjoy leisure time. The necessary legal conditions must be created for every one so that they can access their rights in a proper atmosphere. Therefore, to investigate the condition of leisure time considering the right of citizens and how much people know about the rights and rules about their leisure time, the role of government and organizations which deal with leisture time and enactment of leisure laws, 210 questionnaires were distributed among people in Laleh Park in Tehran. SPSS and Likert systematic fivefold spectrum were used to process the data. The result indicates that most people enjoy the necessary safety security, and freedom in their leisurely places, but they know nothing much about their legal rights concerning leisure times. Also, it was found that the role of government in organizing and controlling the places for leisure time is important to them. Also it was found that the role of government in organizing and controlling the places for leisure time is important to them.
Mehran Maghsoudi; Hamid Ganjaeian; Lila Garosi; Anvar Moradi
Abstract
Extended abstract
Introduction
Geomorphology tourism or geotourismis one of the areas ofmodern studies in geoscience and tourism studies based on the identification of geomorphosites or special geomorphological sites. Geomorphosites are of new concepts that have entered the tourism literature with ...
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Extended abstract
Introduction
Geomorphology tourism or geotourismis one of the areas ofmodern studies in geoscience and tourism studies based on the identification of geomorphosites or special geomorphological sites. Geomorphosites are of new concepts that have entered the tourism literature with an emphasis on the location of special sites, therefore, it emphasizes on a set of geographical, geological andgeoarchaeology features. They also havescientific, ecological, cultural and economic values simultaneously and are utilized to understand and exploit human tourism. Geosites, which are a branch of geotourismgive rise to sustainable development in that region, due to their unique attractions. This new economy is completed in a network of cultural heritage and natural resources managements. Geosites of the region must be identified and introduced prior to any planning. Geosites in east Kurdistan province are very less known and only some of them have superficially drawn attentions,therefore, it has been tried to evaluate the capabilities of these geosites in this research while introducing them. This area, along with the attractions of geotourism has also sensitivities and limitations that can be severely damaged, if the red lines are violated. In fact, the purpose of this is to introduce Kurdistan geositeswith the aim of becoming more familiar with the capabilities of this geosite, as well as investigating the geotourist problems of the region in order to pay attention to the planning related to the tourism industry that can be economically effective on areas with geosites.
Materials and methods
This is an applied research, and descriptive-analytical method was used to analyze information and data. The final analysis has been carried out based on the results obtained from the evaluation of the values and criteria of geotourism. Survey procedure, field visits and field studiesas well as library and documentary studies have been used to collect information. The combination of library and field information will determine the overall value of the region’s geotourism. Two methods of Comanescu and Fassoulaswere used to evaluate the geosites in this research. In addition to evaluating geosites, the areas susceptible to geotourism development in the study area were zoned, and two Fuzzy and ANP models were used for this purpose. The methodology is in a way that the data layers first became fuzzy and comparable, using fuzzy model. Then, the obtained weight was multiplied by each one of the data layers, and thefinal map was obtained by integrating the data layers in Arc GIS. Finally, geosites which are susceptible to geotourism development were selected using the final results obtained from the zoning as well as the results obtained from the geosites evaluation by the use of two Comanescu and Fassoulasmodels.
Discussion and results
After identifying the geosites, Comanescu and Fassoulas methods were used to evaluate them. For this purpose, library methods and experts’ opinionshavebeenused. First, the geosites were evaluated according to the criteria of Comanescu method, and based on the final results obtained from the evaluations, the GhalehQomchoqayhas the highestvaluewith a totalof 84 scores. After the GharQomchoqay, SarabQorveh and CheshmehTangzhave the highest valueswith 76 and 69 scores, respectively. Then the geosites were evaluated using the Fassoulas method, and according to the final results, GhalehQomchoqay and SarabQorveh with a total of 17.5 and 13 scores have the highest values, respectively. The results obtained from the evaluation by both Comanescu and Fassoulasmethods indicate the high value of GharQomchoqay and SarabQorveh for geotourism purposes. In the present research, in addition to the geosites evaluation, areas susceptible to development have been identified using the intended criteria and two Fuzzy and ANP models have been used for this purpose.
Conclusion
After the evaluation done by the methods of Comanescu and Fassoulas,zoning of the areas susceptible to geotourism development was carried out,using the intended criteria. The results indicate that among the geosites of the study area, 8 geosites including GhalehQomchoqay,SarabQorveh, CheshmehTangz and Baba GoorGoor’sEzhdaha Mount, Badr and Parishan mountains, GharGolestaneh, KoohNesar and SarabBijar have a high Potential for the purposes of geotourism development. In most important of researches done in the country, the evaluation methods have only been used. However, the most important advantage of this research is that all the necessary criteria have been evaluated and the final result has been the outcome of the multi-criteria evaluation. In fact, in addition to the evaluation methods, the zoning methods have also been used. The use of zoning methods has led to taking the environmental factors into consideration in the selection of top sites and the sites selected as sexemplary sites need to meet all the necessary requirements for the development of geotourism infrastructure.
