فهرست مطالب فاطمه جهانی شکیب

Trend analysis of growth of cities and predicting their changes in the future are essential for spatial ‎planning. For this purpose, it is necessary to map build-up areas. In many areas, especially in arid ‎climate, it is not possible to separate the build-up areas from the surrounding land cover simply. That's ‎mean the usual methods of classifying satellite images or conventional indices can’t separate mentioned ‎classes with acceptable accuracy. Hence, many researchers have developed different spectral indices to ‎extract the build-up areas. The use of surface temperature changes to represent build-up areas using the ‎Local Climate Zones (LCZ) algorithm is less considered and is a relatively new method. Therefore, in ‎this paper, the separation of build-up areas from the other surrounding land cover was considered using ‎LCZ algorithm. There is no limit to the number of bands in this method, thus four series of Landsat ‎satellite images in the year 2020 were used and the LCZ algorithm’s accuracy was compared with the ‎latest automatic classified build-up indices including DBI, BLFEI, BAEI and BAEM. The results of this ‎study showed that the classification accuracy of the LCZ algorithm was 96%, while the BLFEI and ‎BAEM indices were not able to completely separate the build-up areas from other types of land cover. ‎The total accuracy of the BAEI index was 0.37. Therefore, the use of LCZ method has a high efficiency ‎compared to build-up indices, and it is recommended in arid and semi-arid zones.‎

Modeling habitat network connections in biodiversity conservation planning is one of the global priorities of landscape ecology and ecological security. Destruction of landscape structure by creating disjointed habitats and disconnection in landscape patches leads to disturbance in ecological functions. This research aimed to model the landscape corridors of South Khorasan Province to link habitats together to increase habitat network connections. This, in spite of avoiding island management of conserved areas, causes sustainable protection of ecological security. First, the habitat quality map of the study area was modeled, and then it was converted into a habitat resistance map. Habitat hotspots were also extracted from the habitat quality map using the Getis-Ord G approach. Finally, Habitat corridors and the most significant connecting regions were modeled using the habitat quality and resistance maps in Circuitscape software based on circuit theory. The findings indicated that several regions are capable of producing flow with intensities ranging from 0 to 114.5 Ampere. These areas include about 4,944,200 ha (33%) of the entire study area, of which 900 ha are hot corridors, which can be thought of as corridors that facilitate species movement and can mitigate the negative effects of habitat fragmentation. Therefore, for efficient protection of habitat network security, it is necessary for planners to pay attention to the important corridors for connecting the habitats. The results of this study in the South Khorasan Province can pave the way for operational measures to be taken to construct and plan the protection of corridors and improve the habitat performance of the landscape.

Habitat fragmentation, interruption of the movement of organisms, and gene flow between them are considered a threat to the supply of habitat services in the landscape. It can lead species populations to extinction. Landscape connection is defined as the ability of landscape structure and composition to facilitate the movement of people and populations among habitat patches, and it is considered an important feature of the landscape. Establishing and maintaining gene flow between habitats and populations of species to prevent the fragmentation of habitats in the medium term and to prevent the extinction of species in the long term is one of the main goals of designing ecological corridors and connections. It is considered and causes preservation and supply of habitat services. Modeling habitat network connections in biodiversity conservation planning is one of the global priorities of landscape ecology and ecological security. Destruction of landscape structure by creating disjointed habitats and disconnection in landscape patches leads to disturbance in ecologic functions. This research aimed to model the landscape corridors of South Khorasan Province to link habitats together to increase habitat network connections. In spite of avoiding island management of conserved areas, this matter causes sustainable protection of ecological security.

The province of South Khorasan is a study area that has seven protected areas, three wildlife refuges, and six no-hunting areas. The province's diverse ecosystems and habitats have resulted in an abundance of species in arid land areas. In the first step, habitat quality was modeled using InVEST software. Then, based on the modeled map of the habitat obtained in the previous step, the habitat resistance map was considered as the inverse of the habitat quality. Then, a habitat resistance map and habitat hotspots were prepared as input in Circuitscape software. Also, habitat hotspots were extracted through spatial data mining using the Getis-Ord Gi method. In the third step, by implementing Circuitscape software, habitat corridors were designed in the South Khorasan province based on the circuit theory.

Modeling the status of habitat quality has a vital impact on biodiversity conservation strategies. Threats affect landscape fragmentation and functions and processes and lead the ecosystem to decrease the supply of habitat services. Therefore, building ecological networks by identifying and facilitating the connections of habitats and planning to improve their performance is considered a solution to deal with this crisis and sustainable conservation of habitats. The research method was applied according to the mentioned framework. For this purpose, the status of threat sources, their location, and distribution were determined by reviewing extensive studies. We identified ten types of threats and modeled the habitat quality. Habitat corridors and the most important communication areas were modeled based on the circuit theory using Circuitscape software. Finally, habitat corridors and the most significant connecting regions were modeled using the habitat quality and resistance maps in Circuitscape software based on circuit theory.  Results indicated that several regions are capable of producing flow with intensities ranging from 0 to 114.5. These areas include about 4,944,200 ha (33%) of the entire study area, of which 900 ha are hot corridors, which can be thought of as corridors that facilitate species movement. Another important result of this research was the identification of important connection areas called pinch points. The ease of movement along important connection areas (subject to their protection) can partially compensate for the negative effects of habitat fragmentation by connecting isolated populations and help to identify and review gaps in conservation planning.

In this research, sustainable conservation of biodiversity was done with a method based on habitat corridor modeling and circuit theory. The importance of conducting this research to identify corridors between habitat patches is because the circuit theory provides the possibility to evaluate the strength and intensity of the connection. The application of results of this research can be used to guide the conservation planning development of the province's ecological network based on the supply of habitat services to ensure the survival of wildlife and biodiversity with great benefit and the least cost. Also, as an effective conservation strategy, it causes integration and maximum supply of this service, which enables territorial managers to achieve ecological security and ultimately sustainable development. The results of this study in the South Khorasan Province can pave the way for operational measures to be taken to construct and plan the protection of corridors and improve the habitat performance of the landscape.

Water yield is a key indicator of the performance and valuable ecosystem service that directly affects the sustainable development of the economy, human well-being, and ecosystems of the basin. Using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, were simulated water changes in 10 basins, in the eastern border basin of South Khorasan province under the influence of land use/land cover changes. The model was calibrated using the long-term data of flow at Efin, Khonik Olia, Mansourabad, Gezik, and Ahangaran stations. Also, the economic value of produced water service was calculated in each of the different land uses/land covers. The results showed the highest volume of produced water in the Esfadan basin with 8,126,129 cubic meters, and the lowest in Namakzar khaf Basin equal 185,590 cubic meters. The amount of produced water in the whole studied area was 14836168 cubic meters. The highest amount of produced water was in the land use of dense and semi-dense range with more than 12 million and 430 thousand cubic meters, followed by the land use of sparse range with more than 1 million and 990 thousand cubic meters. The total economic value of produced water in the eastern border basins was equal to 16115806.5 million Rials. The spatial indication of the distribution of economic values of the ecosystem, which was carried out in this research through quantification, mapping and valuation of ecosystem services, can be used as important and reliable tools for natural capital management and policy making.

The distinction between barren and build-up areas is one of the most important issues in land use/land cover mapping ‎in arid and semi-arid climates. In this regard, many researchers have tried to increase the accuracy of classification ‎using different methods that, some of which are complex and time-consuming. Therefore, the present study conducted ‎aimed to apply micro-climate change through the implementation of Local Climate Zoning (LCZ) algorithm in land ‎use identification with emphasis on the separation of build-up areas in one of the arid cities of Iran, and the efficiency ‎of the method by investigation the classification accuracy was compared with various supervised methods including ‎maximum likelihood, minimum distance, Fisher, KNN, fuzzy, artificial neural network and support vector machine. ‎The study area is Zahedan city, which has a very significant growth of build-up areas in recent decades. For this ‎purpose, four periods of Landsat satellite images year 2020 were used. Training samples were extracted from Google ‎Earth and the validation of the classification results was performed using 218 random points. The accuracy results ‎showed that the use of LCZ algorithm with overall accuracy and kappa coefficient of 96.33% and 0.95, respectively is ‎the highest and then the support vector machine and Fisher methods with overall accuracy of 86.61 and 83.03 and ‎kappa coefficient of 0.82 and 0.75, respectively. Therefore, for land use / land cover studies, the LCZ method that ‎considers the micro-climate, is proposed.‎

Increasing development activities have led to a reduction in habitat quality and biodiversity loss. Utilization of industrial and mining capacities and the development of infrastructure are among the most important components of habitat quality decline in Kerman province. In this study, the quality and destruction of habitats in Kerman province were modeled using Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. The habitat quality map of the ungulates was valued using the cost compensation method, and the average habitat quality value was used as an independent variable in the regression analysis to predict the economic value of the habitat. The results showed the highest degradation of the habitats in the northwest of the province, where most of the threat factors are present. The northeastern parts of the province have experienced the least degradation. The highest-quality and most valuable areas, which cover 42.8% of the province, have the highest level of habitat degradation. These habitats are mainly cover by dense forests and rangelands. The total habitat value of Kerman was estimated at 2437 billion Tomans. The final habitat valuation map can be used as a decision-making criteria in environmental management for locating development projects, estimating damages, and updating the boundaries of protected areas.

The world is warming and the world's population is moving to cities. These two truths do not seem to be related; But a phenomenon called urban heat island connects the two. UHI is one of the most common urban climate phenomena in which some urban areas, especially urban centers, become several degrees warmer than the surrounding areas. Studying this phenomenon and examining its mechanism is very important for urban planning. In the present study, in order to estimate LST, four single-channel Landsat algorithms, single window, Planck equation and radiation transfer equation in QGIS software environment between 2000 and 2019 in summer and winter seasons in Birjand city have been used. The effect of land use change on the thermal island has also been investigated. In the present study, ground surface temperature in Birjand city was first extracted using Landsat 7 ETM + satellite imagery and Landsat 8 TIRS / OLI sensors in 2000 and 2019 by four methods. In order to investigate the general ability of algorithms to calculate the surface temperature, the statistical indices of mean square error, Nash-Sutcliffe coefficient, mean absolute error and coefficient of determination were used. The results showed that the Landsat single-channel algorithm for calculating the surface temperature in Birjand is more accurate than other algorithms.

Landscape ecology has generated much excitement in the past two decades. One reason was that it brought spatial analysis and modeling to the forefront of ecological research. However, high expectations for landscape analysis to improve our understanding and prediction of ecological processes have largely been unfulfilled. We identified three kinds of critical issues: conceptual flaws in landscape pattern analysis, inherent limitations of landscape indices, and improper use of pattern indices. For example, many landscape analyses treat quantitative description of spatial pattern as an end itself and fail to explore relationships between pattern and process. Landscape indices and map data are sometimes used without testing their ecological relevance, which may not only confound interpretation of results, but also lead to meaningless results. In addition, correlation analysis with indices is impeded by the lack of data because of difficulties in large-scale experimentation and by complicated behavior of indices as a result of their varying responses to changes in scale and spatial pattern. These problems represent significant challenges to landscape pattern analysis, especially in terms of relating pattern to process. In this perspective paper, we examine the underlying problems of these challenges and offer some solutions.

Human activities have increasingly threatened biodiversity and habitat services. With the intensification of fragmented habitats has affected their quality. In this regard, it is necessary to know the spatial pattern of habitat hotspots because it, in turn, causes environmental sustainability. In present research, habitat quality modeled in arid ecosystems of South Khorasan province using InVEST software based on human threats, impact, distance, relative sensitivity to threats, and accessibility of habitat sources. Then spatial data mining of hotspots was analyzed using Gettis-Ord Gi, Moran and natural breaks methods. Also, the accuracy assessment of habitat hotspots extraction, through the ROC index, indicated accuracy more than 80% in the mentioned data mining methods, but the Gettis-Ord Gi index had the highest accuracy (94.5%). The results of the spatial statistics of habitat hotspots overlapping with the protected areas of the province showed that Kamarsorkh Protected area contains the most (91.33%) and the Estand No-hunt area has the least (0.54%) habitat hotspots. Also, some areas of habitat hotspots were identified in free lands (9.34%). Therefore, the current protected areas do not cover a significant percentage of the hotspots in the free lands, so in sustainable conservation planning, the proposed methodology in research can apply to change and revise the borders of the protected areas.

The Iranian leopard (Panthera pardus saxicolor, Pocock 1927) is one of the endangered species. For this reason, it is necessary to evaluate and protect the habitat of this species as a flag species that is placed at the top of the food pyramid. In this paper, the InVEST software is utilized to investigate the habitat quality of the Iranian leopard in Kopet Dag region in the northeast of Iran Then, 30 habitat variables are prepared using ArcGIS 10.3 software including climatic variables, topography, Landuse/Landcover, and leopard prey distribution. Then, InVEST software and Habitat Quality model are employed in Kopet Dag region to survey the habitat quality of the studied species. The input data of the InVEST software encompasses the current land use map, threat list tables, and habitat sensitivity. By employing the output of MaxEnt results, the information on the threat and habitat sensitivity tables are prepared and entered into the model. Ultimately, after running the model, the results indicate that 81.22% of the desirable habitats and 18.77% of the undesirable habitats overlap with Kopet Dag region. Moreover, the cities of Mashhad, Khaf, Neishabur, and Sabzevar, have the most desirable habitat respectively for the studied species. the results indicate that the most amount of destruction is in the west of Mashhad city and then in the center of Golbahar and Qochan citie.

The ecosystem service of water yield is affected by damaging human activities, and the estimation of its quantity ‎through modeling is the first step to sustainable management of this service. This research applied the InVEST ‎hydrological model to quantify the ecosystem service of water yield and its valuation in the northern arid and semi-arid ‎sub-basins of Kerman province. First, for modelling the water yield were entered the maps such as annual average ‎precipitation, depth of root limiting layers, plant accessible water capacity, land use/land cover (LULC), and the ‎boundaries of the basin and sub-basins, and the approximate amount of actual evapotranspiration (AET) in each pixel. ‎Then maps of estimated water yield in each pixel was obtained. The model calculated 5112.43 million cubic meters of ‎water with a value of more than 418500 billion Rails are produced annually, the highest amount of water yield is in sub-‎basin one (Abargho-Sirjan) with 2103 million cubic meters per year and the lowest amount of water yield in sub-region ‎three (north Kavir-e lut) with the amount of 741.84 MCM. The results showed that the value of supply the ‎water yield service is strongly influenced by the spatial changes of LULC. Dense range lands produce 27630.7 MCM of ‎water per hectare, and each hectare of dense forest can produce 1104.6 MCM of water. Therefore the role of vegetation ‎shows the influence of water infiltration and feeding of aquifers in high areas. The results of this study can be used in ‎spatial planning to reduce the destructive effects of floods and droughts, prevent land degradation and develop vegetation, ‎feed aquifers, and also estimate damages in green accounting.‎

South Khorasan Province has gone through rapid industrialization and urbanization processes in the last decades and is under increasing pressure from various environmental challenges such as water scarcity and intensification of pollution and ecosystem degradation. Therefore, the purpose of this study is to develop scenarios for the future state of the environment of South Khorasan province using LIPSOR, the French school of scenario building, and by the application of simple interaction matrix models and morphological analysis to systematically help the environmental management orientations. For this purpose, key variables were first introduced as the main drivers or actors shaping the future. SMIC PROB-EXPERT software package was used to explain the initial scenarios of the future environmental situation of the province. Then a set of scenarios including the most probable scenarios were identified using MORPHOL software. Also, due to a large number of scenarios, the framework of general scenarios was used to describe different axes and conditions. The results of the study of the five main drivers in the SMIC model led to the extraction of 10 initial scenarios. Then, morphological analysis with the MORPHOL model with three political, institutional-executive, and cultural domains produced 3125 possible and probable scenarios, each of which shows the probability of D5/D6/D1/D33/D29 propulsion, respectively. Finally, the analysis of 50 possible scenarios showed that scenario 11111 is the most probable scenario (276.41%), and scenarios 11112, 11113, and 21111 are with probabilities of 184.28, 122.85, and 115.17, respectively, which are five of its constituent variables mainly indicating the probability of occurrence of low (1) to moderate (2 and 3) in the scenarios. In general, the future environmental situation of South Khorasan province is in the situation of the third quarter called lack of discretion in the environment. To change the future and move towards a better future, paying attention to each of the influential variables will be the way forward and can be directed towards a quarter of the framework with at least one flourishing axis.

Accelerating urban expansion is increasingly challenging the sustainable use of land, since modeling urban growth is important in order to adapt to balanced development. Among all the models for urban simulation, dynamic models based on cellular automata have significant usage in urban modeling because of its applications in different places and times. One of the most widely used spatial models based on cellular automata is the SLEUTH model, which in recent years has improved its accuracy and efficiency for performing calculations, and today it is widely considered in predicting the development trend of different cities in the world.This study was carried out with the aim of simulating the future urban expansion of Birjand Metropolitan from 2020 to 2050 using Cellular Automata (CA) methodology in the SLEUTH modeling considering two scenarios: historical and environmental growth.

Study areaBirjand Metropolitan is the capital of South Khorasan province. The area of Birjand is 14.265 km2 and located between 53', 32° N and 59', 12° E in the northeastern margin of The Lut Desert, which is surrounded by mountains. In the last decade, and especially after the division of Khorasan province into three provinces of North Khorasan, South Khorasan and Khorasan Razavi, Birjand Metropolitan as center of South Khorasan province faced to socio-economic and political changes that led to rapid urban growth and physical and functional changes.SLEUTH modelIn this research, modeling the expansion of Birjand has been considered using cellular automata by SLEUTH method. SLEUTH name is derived from the names of input layers: Slope, Land use, Excluded areas, Urbanization, Transportation and Hillshade. The main attribute of SLEUTH is that it be calibrated on the base of the region changes in the past and therefore reasonably predicts the future. SLEUTH starts with the oldest data (first year of control) and generates growth cycles. Each growth cycle is assumed to represent one year. A run is the set of growth cycles from the first control year to the final year. Considering the comparison the simulated image with the real image in the control years, evaluation indexes are generated.SLEUTH modeling performed in four steps:1- Data gatheringAll layers (Slope, Land use, Excluded areas, Urbanization, Transportation and Hillshade) were georeferenced to the same geographical references system (UTM-40N) and pixel size 30*30. Slope and Hillshade layers extracted from DEM. Land use and Urbanization provided from classification of landsat_TM images 1990, 2000, 2001, 2020 years. These images were belonged to row and path 159 and 37, respectively and classification was performed using ‎Support Vector Machine (SVM) algorithm. In preparing the road layer for four mentioned years, in addition to using satellite images, the existing maps and Google Earth were used for updating. Two Excluded areas layer in this study were prepared according to two scenarios: historical growth and environmental growth. In the historical growth scenario, roads and cities and in the environmental growth scenario, vegetation and high slopes (slops higher than 30%) were considered as Excluded areas.2- Confirmation of the correct execution of the modelThe SLEUTH model was downloaded from the Gigalapolis project from the website: http://www.ncgia.ucsb.edu/projects, and the required simulator in the Windows (Cygwin) on the PC was installed. To ensure the correct execution of the model, SLEUTH was performed by experimental data and data from the study area. Surveying the results and outputs of these performances confirms accuracy of execution.3- The calibration stepCalibration is one of the most important steps in simulating urban growth using SLEUTH. In the calibration step, based on the historical data, the best set for the five global parameters/coefficients (Diffusion, Bread, Spread, Slope and Road Gravity) is extracted. These coefficients, which indicate the contribution of factors to the expansion of the study area, vary from zero to 100 and according to the Brute Force method in four stages, which consist of coarse, fine, final and average, are obtained based on cell size, search range and Monte Carlo execution number. In each forward stage the range of search become narrow and number of Monte Carlo execution become more. ‎Optimum Sleuth Metric (OSM) and Leesalee metrics in each stage were used to determining the calibration coefficients for the next stage. These metrics show the overall precision of the simulation too.4- Prediction the Birjand growthFour kinds of growth simulate by SLEUTH consist of spontaneous, spread, organic and road influenced. This growth rules and the coefficients obtained from previous step constitute the transfer rules in the Cellular Automata of SLEUTH model for prediction. Output image of prediction was reclassified to 1: urbanization probability> 80% and 0: urbanization probability< 80%.

In this study, using the SLEUTH model, the expansion of Birjand city was predicted according to historical and environmental growth scenarios from 2020 until 2050. During the study period, the growth of the urbanization is quite evident and it is mainly happening in the northeast and southwest of the city. One scenario of this research was based on the historical growth and the past trend, which means that all the drivers that have caused the growth of the city in the past will continue in the future. In the environmental growth scenario, urban growth will not located in vegetation cover and slopes above 30%. The largest increase will be happened around roads in the historical growth scenario and in the vicinity of urban in the environmental scenario. The Calibration results showed that there was different coefficients for scenarios. High diffusion in historical growth scenario (87) rather than environmental growth scenario (20) denoted that probability of a new urban center by 2050 is high and spontaneous growth/outlying growth will occur by 2050 but, in the environmental growth scenario the growth will has a more coherent pattern. Bread coefficients in historical growth scenario (73) show the probability of filling around the new urban points by 2050 is high in the future, but in environmental growth scenario (4) does not support new points for urban expansion. Spread coefficient in environmental growth scenario (32) was more than historical growth scenario (20) that means probability of edge (organic) growth in environmental growth scenario is more than historical growth scenario in the future. Slope Gravity in both scenarios was very low (1) so slope isn’t the control factor in this area. The main reason for low rule of slope is the uniformity of the slope and the scarcity of high slopes in the study area. Road Gravity in historical growth scenario (22) and in environmental growth scenario (37) that shows there are high eventuality of linear growth type in both scenario and road-influenced growth is significant for the future growth.The simulation results showed that urban expansion in the historical and environmental growth scenarios would be 2201.85 and 2150.91 hectares, respectively. Although the extent of the urbanization area is close to each other, the probable places for urbanization are more compact with organic pattern in the environmental scenario and more scattered in the historical scenario. Therefore urban expansion in environmental scenario has lower influence on surrounding environment rather than historical scenario and is more close to sustainable development.The results can provide useful information for the decisions of land managers and municipalities in the direction of sustainable urban development.

The new political division of Khorasan Province had significant changes on urban growth of Birjand that turn it to metropolitan. According to simulation of urban growth increasing the area of Birjand city is inevitable in both historical and environmental scenarios. A comparison of the two scenarios denoted that in the historical growth scenario, the urban growth rate is higher, the vegetation destruction and spontaneous settlements is maximal. The findings of this study can help policy makers and managers in formulating informed urban planning strategies to have the least destructive effect on the environment in the future.

Human activities are one of the factors that have a significant impact on the land use change patterns, and these changes are in most cases inconsistent with the environment. Therefore, land-use prediction models for sustainable land-use planning are a requirement. In this research, using the Cellular Automata Markov Chain model, modeling of land use change for the Gharehsou basin has been improved to predict the future. Promotion of the Markov chain model has been done by entering the population growth rate and per capita requirements of each land use in the model. Validation of the upgraded model by comparing the map of the predicted land use change for 2014 and the results of the upgraded model have been reviewed. The results of the comparison of these two maps showed that the results of the upgraded model were much more similar to the current situation since the population growth rate and, consequently, per capita needed for urban development are the most important driving force to disrupt the ratio of changes in a timely trend. Therefore, considering this factor in the Markov chain model more flexibility and great results closer to reality, which is practical in the Gharehsou basin. Finally, the upgraded CA-Markov chain model was used to predict the 2030 basin.

In recent years, there has been a growing demand for solar energy, as one of the cleanest and most innovative energy sources in the world. South Khorasan province is one of the less developed regions of Iran that the transfer of energy carriers to this province is costly. On the other hand, the development of agricultural farms in South Khorasan province is facing a serious challenge due to the lack of water resources in arid and desert climate. Therefore, the development of solar farms can be a good alternative for the development of agricultural farms, especially irrigated and non-strategic crops. The purpose of this study is to identify the optimal locations for the development of solar farms in South Khorasan province. The different stages of this research have been done in six steps. First, the criteria affecting the location of solar farms were identified by the Delphi method. In the second step, with the help of experts and environmentalists, the criteria were coded and screened. In the third step, the spatial database of effective criteria was established. In the fourth step, the weight of the effective criteria was calculated through the Analytic Hierarchy Process (AHP). In the fifth step, the layers of effective criteria were classified and coded. In the final step, the weighted fuzzy layers with gamma fuzzy operator was overlapped. The results showed that in South Khorasan province, the cities of Tabas (387.4 km2), Nehbandan (120.4 km2) and Sarayan (119.6 km2) are sites with very high optimality for the development of solar farms in the province, respectively. The optimal area by the cities of the province at the average, desirable and very desirable level for operation in different conditions was presented. The current results and even changing the existing conditions by re-implementing the proposed approach can consciously lead managers' decisions towards the wise development of the region, the use of environmental capacities and new energies.

In recent decades, the drastic ecological changes of Hamoon international wetlands placed them on the Montreal blacklist. Therefore, this study aimed to predict and validate the changes of birds and fishes indicators for the future of these wetlands. KSIM is the used method (Kane Simulation Technique to measure the impact of different variables ranged from +3 (severe and positive effect) to -3 (severe and negative effect); is evaluated by environmental experts. Due to the limitations of this method in multivariate analysis (because of the numbers and abundance of variables), the affecting factors on indicators have been grouped into four categories of economic, social, wildlife management and water resources management. To obtain probabilities of variables and predict the value of indicators in 2034, the mode of experts' ideas was used and future trends were simulated. Model validation was performed by field surveying in two consecutive years. The results of the KSIM simulation estimated that the bird and fish indicators will continue to decrease during the period 2004-2034; from 0.77 to 0.28 and 0.60 to 0.22, respectively. Based on the validation results, the validity of the model is acceptable, which can be confidently used based on the results obtained from the experts' ideas in the cross-effects matrix. This study showed that the KSIM method can properly investigates the interactions between system components and therefore is able to predict future conditions. Economic and social problems lead to the decline of fishes and birds indicators; and deterioration of the situation put relatively more pressure on resources. The downward trend in wildlife management and water resources is also a serious warning that must be considered in decision-making processes.

There is not hidden from anyone, that the effects of climate change and droughts in the Sistan region on the degradation of wildlife habitat. Meanwhile, species that live close to residential areas are under increasing pressure due to human threats. Francolinus francolinus is one of these types that in this research applied MaxEnt (Maximum Entropy) algorithm to model its possible habitat distribution. Modeling considered nine environmental variables. Before implementing the algorithm, it was ensured that there was no correlation between the variables. The results of the model evaluation based on the following level of the ROC curve showed that the model has an excellent prediction than the random state. Among the studied environmental variables, the highest percentage of share, distance from agricultural fields, and the most important is the grass cover type variable. Eastern Sistan regions were the most preferred areas for this species, where most agricultural lands are located there. There are no protected areas in these areas, and due to the widespread distribution of urban and rural uses in these areas, it is not possible to allocate land for conservation use, so only with management measures and public participation is it possible to survive.

The base of current environmental problems can be addressed in irresponsible behavior humans around nature. These behaviors appear that are influenced by different factors in the environment. The natural and humanity are bedded of tourism activities. Then maybe behaviors and unsuitable tourism activities have negative impacts and subject to vulnerable them. This research aim to modeling the environmental behaviors of tourists in Birjand city was applied. In the method of this research In order to assess the behaviors of tourists (dependent variable) evaluate the influenced factors such as cognition, satisfaction, theory, and involvement activity (independent variables) using spread the questionnaires among tourist in Birjand natural and cultural attractions. So, after the query of the tourist’s community in Birjand city during the first six months of 1398, the results were analyzed by linear regression with SPSS 13.0 software. Analyze of Spearman and Pearson were appeared the high correlation among the studied factors. In achieved behavior model from regression analysis in tourist’s community showed the cognition of tourists and their satisfaction of tourism places and natural attractions have a high impact on behavior. While the theory and involvement activity have no impact on the behavior model. In this behavior model, the value of R and R2 achieved 0.99 and 0.98 respectively that shown the high prediction power of the model. The others of the result’s research are a significant effect on behavior in gender, age and education levels in the studied tourist community. It seemed the environmental behavior was due to subjectivism factors. So, it needs to execute to improve the responsible behavior in tourists and create the theory and involvement activity, education and promotion measures of the relevant organization.

 In Iran,time is limited and it is always too late to modify management attitudes in the fields of environment. On the one hand, the relevant agencies do not even know their priorities separately or are unaware relationship of their priorities with other agencies, while at the macro level, they are unaware of the province's development plan. So, important drivers in the field of environment are the first and most important steps in guiding scenarios of proper management.

 First, a list of effective drivers of environmental management in the South Khorasan province was collected  from some specialist and experts using Delphi, followed by two-dimensional matrices containing quantitative matrices to quantify the driver’s relationships and interpretations. The axes of influence and dependence are were used. Therefore, according to the position of each driver with these two criteria in the matrix, five types of drivers are defined. Drivers screening based on the degree of influence and dependence of other drivers as effective , key and independent drivers in the field of environmental management in South Khorasan province were studied. The method used was MicMac Structural Analysis, which was used by academic experts and related executives. In so doing, the team created a common language which will served them as the process continued. In most cases, it also allowed the team to redefine certain variables and refine the analysis of the system. Lastly, experience shows that the ideal percentage of the matrix to be filled-in is around 20%.
Comparing the rankings of the variables from the various classifications (direct, indirect and potential) is a rich source of information. It allows the team to confirm the importance of certain variables as well as to reveal those variables which play a dominant role in the system, and which would have remained undetected if they had only been compared directly. The information obtained by influence and dependence of each of the variables can be displayed in two-dimensional diagrams containing the vertical (affective) and horizontal (affective) axes. This method can identify the most effective drivers in the system and study the different roles played by these drivers (Godet & Durance, 2011).

By aggregating and analyzing the views of a panel of experts in the field who know the topic in MicMac 39 software, drivers were identified as key, effective, effective and dependence drivers. The comments were considered as MicMac inputs, with a filling rate of 23.86% including 153 one (weak influence), 113 two (moderate influence), 89 three (strong influence) and 8 to P (possible influence). The sum of direct and indirect and probable influence of drivers were estimated to be 3007, 2805, 2135, 1938 and 1572, respectively. This matrix has 100% stability with two replications which shows high validity of the questionnaire and its answers. The direct influence (a) and indirect (b) influence of the drivers on each other are shown in Fig. 1.
 Driver 5 (D5: creating environmental law enforcement and warranties) and D1 (co-operation between related agencies to prevent any re-work) in four ways are among the most effective and determining factors. In the next step, the influence of the drivers of the free flow of information and sharing the results of studies of all environmental-related organizations to public or academic expertise (D33), changing the real attitude of decision-makers in embracing intellectual physical potential, and creative indigenous peoples of the region (D29) and the environmental agency's correct placement in decision making (before doing the project and any action not after it is finalized or completed!) (D6) were more influence drivers respectively.
Given that the distribution of drivers is in the axis of influence and dependency as L shape, the system under study is balanced and it is possible to make planning for such a system (Arcade et al., 1999; Erfani and Mircheraghkhani, 2018)

 Five main and key drivers of the system under study were identified, the first two of which relate to political and institutional domains that are in line with  Erfani and Mircheraghkhani’s (2018) study. In this study, monitoring of nine identified response drivers is the main indicator for revealing the province’s environmental management status, which is recommended for future studies. These indicators can explain the environmental status of the province and can be considered as a criterion for determining the actual performance and efficiency of the agencies. It is also recommended to continue the present study and to complete four more steps from the LIPSOR School to identify conflicts of interest between relevant stakeholders, scenarios building and predict the future. 
 Each year, the performance statistics of the agencies are presented based on the indicators set by the agencies themselves and the overhead agencies, and they are more likely to be defined in a way that may not adequately represent the agencies’ performance, and thus make the agencies less judgmental to fall. For example, the index of mountain tenure has clearly increased over the last few years. Combating mountain tenure alone does not indicate management efficiency, but rather the absence of mountain tenure and the return of shifting areas given to conditions close to the baseline status is effective either. Therefore, change in decision makers' attitudes (D6) and efforts in problem solving have been introduced as one of the key drivers in this study (Fig. 1).

In ecological systems, biotic and abiotic (physical and chemical) components interact with each other. It is a challenge to understand and measure these systems and their internal and external nteractions. However, to manage the ecosystems sustainably, using the integrity principle, we require information on the status and trends of ecosystems as a whole. An ecosystem has integrity when its ecological characteristics and processes occur within their natural ranges of variation, and also it can withstand perturbations and changes caused by natural environmental or human factors. In this situation, the ecosystem will not be disorganized and the process of self-regulation will continue. Useful indicators for ecological integrity assessment must be comprehensive, representative of composition, structure and function of ecosystems. The goals of this research were to explain the theoretical concept of ecological integrity and review integrity indicators as a tool for environmental planning. As such, integrity indicators were assessed in terms of comprehensiveness. The results showed that the species and ecosystem indices are more focused on the internal state of the ecosystem, while those of landscape concerned with the internal state as well as perturbations caused by human activity and natural disturbance.

Efficiency of Gravitational Search Algorithm on Land Multi-Objectives Allocation in optimal selection of Agricultural Land use in Birjand Basin The background of spatial sustainable land planning is based on the position and establishment suitability of the land use activities and the interaction of judgments should be rooted in the three main elements of sustainable development, namely economic, social, and environmental. To the best of our knowledge, over the past 20 years, many significant the developments have been invented in the field of artificial intelligence techniques and tools that can be used to solve many practical geographic problems. The present research aims to introduce a new and effective searching method in order to solve complex, multiple, and non-obvious problems existing in the evolution of land suitability using optimization algorithms. The Birjand basin with 3435km2 area located in longitude from 88º, 41´ to 59º,44´ E and attitude from 32º, 44´ to 33º, 8´ N in the northern part of Bagheran mountains. Employing GSA
This algorithm is designed to simulate the laws of gravity and Newton's motion in a discrete-time environment in search space. The positive features of GSA, including fast convergence, non-stop in local optimizations and computational volume reduction compared to Evolutionary Algorithms (EA) and no need for memory in comparison with other collective intelligence algorithms has created a new research field for researchers. Therefore, in the present study, by considering the advantages of GSA, its capability in optimizing the multi-objective land suitability problems was used.
The objective functions of optimization model
1- Maximize the environmental suitability: Compatibility of land for objective use based on physical, environmental and infrastructure factors requires the mapping of effective factors and their integration.
2- Minimize the Land-use conversion: it results in a decrease in social capital costs and increase in economic benefit of society.
3- Maximize the ecological suitability: it means as the preservation of natural features and environmental structures by maximizing the green lands, which can be evaluated using the Ecosystem Service Values (ESV).
4- Maximize the stability of landscapes: in concepts of landscape, compressed forms close to the circle have more stability than shredded structures. This goal is achieved by maximizing compression function.
5- Maximizing the compression function: In the present study, in order to create an integrated and compact surface a circle form was used around the image gravity centers. Besides, the noise and single cells were removed using the image-processing algorithm.
Optimization model constraints:Setting constraint functions were applied in optimization model by considering the flood-protected areas, areas with a slope over than 70%, amount of demand for agricultural areas, placing a user per pixel, and the total area of the region.
Measuring the efficiency of GSA
In order to evaluate the efficiency of GSA, its results were compared with those of MOLA. At the end, three following approaches were used to compare and measure the efficiency of the algorithm.
First approach: visual evaluation and studying the coherence of allocated spots
Second approach: the use of statistical parameter such as mean and standard deviation of agricultural use suitability
Third approach: Calculating and analyzing the landscape measures such as a number of plots (NP), plot density (PD), mean of shape index (SHAPE_MN), mean of plot area (PARA_MN), proximity index (PROX_MN) and cohesion of spot (COHESION) using FRAGSTATS software. All objectives and constraints of optimization model were mapped. Therefore, amount of agriculture use suitability was applied using ANP Fuzzy technique of weight, fuzzier, and constraints (Fig. 1). Fig. 1: Agriculture use suitability using ANP fuzzy and WLC
In Birjand basin, the ease of change from land covers to agricultural use was mapped (Fig. 2). Fig. 2: the ease of change from land covers to agricultural use
The results from maximizing the ecological suitability were modeled using the difference between the present and future ESV (Fig. 3).
Fig. 3: the difference between the present and future ESV
After fitting all considered objectives and constraints by GSA, the allocation of agricultural use was provided (Fig. 4).   Fig. 4: Allocated agricultural use through GSA
Relative efficiency of GSA
The results of GSA were compared with those of MOLA. The results of allocating agricultural use by MOLA were presented in Fig. 5. Fig. 5: Allocated agricultural use through MOLA
According to the comparison of statistical parameters, mean of agricultural suitability in MOLA had better performance, but in terms of SD, GSA showed better performance. Besides, analyzing all landscape measures demonstrated the efficiency and relative advantage of GSA compared to MOLA.
Discussion and In the present research, optimal allocation of agricultural use was carried out using GSA. Besides, in order to measure the efficiency, its results were compared with those of MOLA. The results showed higher allocated spot for agriculture in MOLA as a disadvantage and higher suitability average was an advantage. On the other hand, since in the GSA, the number of allocated spots was less than MOLA, their suitability was not that much high. GSA showed the maximum sum of suitability with less spot on the map, which depended on the amount of demand. Therefore, it was a great advantage for GSA. Moreover, analyzing the landscape measures demonstrated the efficiency and priority of GSA compared to MOLA. Finally, it can result that the GSA have higher capacity in solving problems with complex and large space in short time and higher objectives and constraints.  

One of the new problems is paying attention to environmental planning for sustainable exploitation of land resources and prevention of environmental issues that have been considered by researchers and managers recently. As much as this planning is based on objective facts and potentialities, achieving predetermined goals becomes more feasible. On the other hand, environmental planning tools have tended to achieve local-scale plans to reach more sustainable cities and townships. In this paper, local-scale development planning has investigated in Shandiz district located at Torghabeh-Shandiz city. The planning of the Shandiz district has carried out using the analytical process consisted of three stages of environmental planning and using the Geographic Information System (GIS). The first stage involves understanding the capabilities and potentials of the study area through the study of the current status. Issues, facilities, and constraints associating to each section are categorized and prioritized in the second stage. The third step involves drawing a vision, organizing the general goals, and defining the objectives. Regard to the priority of the studied factors, it was proposed spatial solutions in environmental units. Finally, physical-spatial development plans were developed to guide the regional changes according to the natural and man-made constraints and potentials.

The most important thing in the land use planning is conflict between opposite or rival land uses in one place that should be done by allocation of land uses according to the utility of land and taking into account economic, social and environmental impacts. For this purpose, different approaches are formed which each of them has made efforts to resolve this conflict. This study compared the two optimization approaches such as Multi Objective Land use Allocation (MOLA) and the Multidimensional Choice (MDCHOICE). The maps were prepared using two approaches for the city limits of Gorgan. Then, maps were compared using the statistical methods of land uses utility and ecological assessment by landscape metrics. Results of this comparison based on statistical and ecological parameters showed the superiority of multi-objective the allocation of land use to multidimensional choice approach. Map by the MOLA approach as a reference map and another map by MDCHOICE approach as a comparative map was used in order to validate the results of the previous stage. Finally, the similarity and agreements of maps were evaluated with various algorithms in the software IDRISI and MCK. The results obtained from the use of any of algorithms offered useful indicators like comparing the class to class, cell to cell, and other types of kappa coefficients such as Histo Kappa, place and fuzzy Kappa that additional discussion of comparison methods is raised. Finally, this study suggests that to compare maps that are modeled in different ways or to validate the maps that use different type's kappas that show the agreement on number and place instead of the usual or standard kappa coefficient.

In order to understand the condition of ecosystems it is essential to asses the threats and disturbances affecting the ecosystems and to develope suitable strategies for environmental management, monitoring and assessment. Especially, sustainable management of wetlands, in terms of their terrestrial and aquatic ecosystems composition and characteristics, requires scientific and multidisciplinary approaches. Due to the impacts of these threats, characteristics of ecosystems have become vulnerable.
This study has been done to provide a new method for vulnerability assessment of Choghakhorwetland at fine scale in order to develop management strategies. At first, by using the Driver, Pressure, State, Impact and response (DPSIR) model the threatening factors and values including ecological, hydrological, economic and social factors were investigated. Then the threats, values and links between threats and values were assessed. Vulnerability assessment is done through combination of their scores.
Results of this research indicated that main threats impact on ecological values included loss of birds and wildlife habitat. Increase of the height of constructed dam and drought have undesirable and severe impact on water supply for Gandoman wetland located in downstream lands. Finally, the strategies were presented as response to each factor of the analytical DPSIR model.

In this study, for potential survey construction of wind power plants in the provinces of Khorasan Razavi and Northern different criteria and sub-criteria have been considered. To become fuzzy criteria are based on expert opinions and investigation done researches, control point and fuzzy function for each of the layers based on their membership gradation range of zero and one was determined in the IDRISI software. Then, according to the importance of integrating information, Analytical Hierarchy Process (AHP) for layers weighting was implemented by Expert choice software. Then, the software ArcGIS, was used to spatial analysis and overlapping layers, and after the analysis of information, Razavi Khorasan and North Khorasan province, in terms of capability the wind power plants building, divided into four levels: excellent, good, fair and poor. Finally, the results indicated that excellent are as for the construction of wind power plants in the study area are located in thesoutheast ofthe study area at Torbatjam station with an area exceeding 222565 .97 hectares (0.018 percent). In addition, good areas are located around the Taybad and Khaaf, Golmakan, Sarakhs, Roshtkhar, Bardaskan, Neyshaboor, Sabzevar, Bojnurd, Ferdows and Jajarm stations with an area exceeding 1817573 .81 hectares (0.17 percent). One cans that renewable energy of wind without any pollution could be utilized by the construction of wind power plants in the replaces ultimately.

Educational organizations due to entry new competitors in this field، they are drawing a long-term vision for them. In order to achieve an acceptable point in this field، should be internal and external factors including of the challenges and potentials of the accelerator and the opportunities، and also examines the opportunities and then attempt to formulate the optimum strategies. In this paper required information investigation through filling the questionnaires، interviews with faculty and department experts and reviewing reports and documents were prepared. This research survey the internal (strengths and weaknesses) and external environment (opportunities and threats)، Department of environment of natural resources faculty of Tehran university، it has studied using SWOT analysis. Based on the results of the final score in the Internal Factor Evaluation of matrix was 0. 035 and external factors Evaluation of matrix was -0. 093 determined. In order to، the Department mentioned in the strategic position is conservative. To determine the attractiveness and relative priority strategies was formed quantitative strategic planning matrix that based on those results، as the best strategies was determined Environmental Excellence launched and set up new fields operational needs respectively.