فهرست مطالب saeid pourmanafi

Residential land encroachment on agricultural areas presents a global challenge regarding land use management. Such a challenge needs crucial attention in Iran where agricultural activities suffer from resource shortage and land use management practices are ineffectively planned and enforced.

An attempt was first made to delineate agricultural land use suitability. Two scenarios namely Current Development (CD) and Environmental Development (ED) were mapped and transplanted to CA-Markov model to simulate urban growth up to 2030, 2040 and 2050. Finally, severity of conflicts was analyzed based on loss of the extent and the corresponding suitability of agricultural lands.   

The results showed that ED scenario is more successful in protecting suitable agricultural lands than CD scenario (nearly one thousand ha). Moreover, CD scenario is projected to occur in areas with relatively higher agricultural suitability values. The difference between the scenarios is not significant for near future (2030), but significant for the ending simulation period (2050).

ED scenario is more succeeded in protecting quantitative and qualitative agricultural lands. By implementing this scenario from now, it takes 35 years to significantly mitigate the conflict between the two land uses. However, the effectiveness of such scenarios requires simultaneous attention to socio-economic parameters.

Chl a is the main pigment of phytoplankton, which is an indicator of phytoplankton biomass and reflects the primary production in the marine environment. In this study, level 3 (4 km) data of Chl a concentration of Persian Gulf and Oman Sea for the period of 2003- 2018 were used. The data was converted to raster format in ArcGIS10.5 environment and then the numerical values of each pixel were extracted in R (version 4.0.2). Missing data were observed in Chl a data, to solve this problem, DINEOF algorithm was applied and non-parametric Mann-Kendall and Sen’s Stimulator tests were used to analyze Chl a concentration trends. The results showed that the maximum concentration of Chl a is in September (0.09 to 18.75 mg / m3) and October (0.23 to 18.03 mg / m3) and the minimum concentration of Chl a in May (0.22 to 5.74 mg / m3) and June (0.20 to 5.12 mg / m3). The trend of Chl a concentration variability over the study period was negative in most areas and not significant. These analyses provide an overall description of Chl a concentration variability in the Persian Gulf and Oman Sea based on satellite observations; however, further investigations based on in situ observations are needed to achieve better understanding of the patterns of of Chl a concentration alterations.

Ecotourism is a financial resource and is a way to sustainable development by considering land capabilities. Without considering land capabilities for this land use, not only the desired goals will not be achieved, but also the land will be degraded. The aim of this study is to determine land capability map for ecotourism in Plasjan sub-basin in Isfahan and Chaharmahal and Bakhtiari provinces by applying multi-criteria evaluation method.  study data were first determined, standardized and weighted by considering expert’s knowledge and literature reviewing. Criteria and constraints respectively were standardized by fuzzy and Boolean methods. The weight of the criteria was determined by AHP method using the experts and professors of university knowledge. Data layers from different sources were prepared, their accuracy was checked and combined with the weighted linear combination method. Ecotourism capability model and a map of the region's ecotourism capability in six classes were prepared. The results have shown that area with very high and high ecotourism capability, with an area of ​​2701 and 7101 hectares, are located near water sources, other beautiful natural landscapes and roads. Examination of the nature tourism map of the region have shown that some areas with medium and low ecotourism capability with an area of 17187 and 176539 hectares, in some areas, are adjacent to water sources but farther away from the road. In addition, the review of questionnaires completed by tourists have shown that despite the great importance of natural beauty, as well as the development of infrastructure, is of particular importance

Increasing consumption of fossil fuels in urban areas emits enormous amounts of greenhouse gases into the atmosphere. Therefore, the study of carbon dioxide (CO2) emissions from urban areas has become an important research topic. The main purpose of this study is space-based quantification of carbon dioxide emissions driving from fossil fuel combustion in different source sectors in Isfahan. To achieve it, in the present study, the "bottom-up" method was used to quantify the carbon dioxide gas emission based on its production sources sectors. In this method, the amount of emission was measured distinctly for different sources of energy consumption and consequently the spatial distribution map the CO2 emission was generated. The results of this study revealed that the total amount of carbon dioxide emissions driving from fossil fuels is 13855525 tons per year in Isfahan. Separately stationary sectors of power plant, housing and commercial and mobile sources including road and railroad and existing agricultural machinery were responsible for emitting 50.61, 21.78, 17.18, 4.92, 4.37, and 1.14% of CO2, respectively. In conclusion, through applying the bottom-up method and CO2 emission distribution mapping based on different source sectors, mitigation measures can be applied more efficiently in urban planning.

The DINEOF algorithm is a parameter free technique based on iterative EOF analysis that is used to calculate the missing data in a given satellite data set (without requiring any prior information). In this study, the DINEOF technique has been used to fill the gaps in chlorophyll-a data series in the Persian Gulf and Oman Sea. Level 3 data (4 km spatial resolution) of chlorophyll-a concentration obtained from MODIS sensor (2003- 2020) for the study area were used. In some of the images several gaps were found in different months of the year. Images with gap in the Persian Gulf and Oman Sea were reconstructed by rtsa.gapfill R-package and DINEOF algorithm in R software. The linear regression analysis was performed between the missing and reconstructed data, and also parameters such as RMSE, MSE, MAD and SNR were calculated to evaluate the validity and performance of the DINEOF algorithm. The maximum number of the gaps in data series were found in July. Hence, the images of July have been examined and reconstructed as the case study. The original maps of chlorophyll-a concentration showed that the maximum number of the gaps were in July 2009 and 2015. Evaluation of the results showed a high accuracy of DINEOF-reconstruction method (e.g. in July 2014, R2 = 0.83, RSME = 0.34, MAD = 0.14, MSE = 0.10). The results showed that the implementation of the DINEOF algorithm (in R) to reconstruct the gaps in chlorophyll-a concentration images could serve as a rapid and efficient technique.

The purpose of this study was to model and predict temporal and spatial patterns of land-use change in the Zayandehrud basin. In this research, the CA-Markov prediction model was used to simulate and predict land-use change. First, the land-use changes from 1996 to 2018 were studied and then the future changes for 2030 and 2050 were simulated. Afterward, the future land-use scenarios were designed. The model was validated by comparing the simulated map of 2018 with the real map, and the kappa coefficient of 94 % was utilized to evaluate the model. Based on the results, the Built-up land-use was altered from 13016 hectares in 1996 to 154194 hectares in 2050. This outcome necessitates the management of the future development of the city. Furthermore, the amount of agricultural land was varied from 177067 hectares in 1996 to 40,000 hectares in 2050. Among all the changes, agricultural lands attracted the most attention and concerns. The results indicated the land-use changes in the form of urban areas and reducing area of agricultural lands. Such alterations were taken place in two distinct stages: urban lands have been developing since 2013, with a direct impact on the reduction of vegetation due to the conversion of agricultural lands into other land-uses. The dynamic trend of changes has also been confirmed and intensified since 1996. In 2018, a significant area of agricultural lands was converted into urban and industrial areas. In addition, the agricultural and orchard lands were 74057 hectares in 2018 and can be reduced to 40,000 hectares by 2050. It revealed 34057 hectares lost as compared to the agricultural and orchard lands in 2018. The present study depicts that the expansion of urban and industrial activities and reducing the level of agricultural land in the region requires more attention and care in land management.

There are several methods of measuring desert pavement roughness. Among these methods, one can name laser and sonic rangefinder, 3D photography, and close-range photogrammetry. Remote sensing techniques need less and cheaper equipment than laser and sonic methods. In short-range photogrammetry, the quantitative amount of terrains can be obtained by processing the images of a digital camera using special methods of photography and camera calibration.

  This method can be introduced as an accurate and cost-effective measuring method to provide a digital model of complications and a three-dimensional model of objects. The present study aimed to evaluate the possibility of using close-range photogrammetry in measuring desert pavement roughness. In this research, first, the calibration parameter of the camera was calculated by taking photos of standard patterns. Then, the meshed samples of desert pavement were photographed and the photos were three-dimensionally simulated.

 The results showed that since in this method the selected points have more effective height and uniform dispersion, the measurement of the average height of roughness is more accurate. It means that measuring the roughness of the soil surface is done with high accuracy in a short time.

Unplanned urban expansion related to population growth, economic development, and rural migration to urban areas has led to unsustainable urban, industrial, and agricultural development. One reason is that spatial planning faces various social, economic, and political challenges that hinder proper structural development. Air pollution has emerged as a prominent threat to human health especially in developing countries; therefore, in several studies, unsuitable land use planning was determined as the main factor of air pollution. However, sometimes a new development takes place in an area affected by air pollution. In this case, even if the land use assessment process is accurately implemented with traditional criteria and without considering air pollution, there would be no rational arrangement for sustainable development. Despite these issues, the air pollution criteria have been mostly ignored in land use assessment studies. The west of the Isfahan region, especially Mobarakeh County, is one of the major spots for agricultural and industrial activities in Iran due to the favorable climatic conditions and the presence of the Zayandehrood River as a water source. This area is also the location of mega industries that include Mobarakeh Steel and Isfahan Steel factories. Accordingly, Mobarakeh County has been constantly affected by various air pollutant factors such as PM10 and NOX caused by these large industrial factories. The existence of agricultural and industrial land uses caused various contradictions between them and urban land use. The criterion of air quality should be considered in urban planning because the residents’ health is one of the most important priorities of any region. Therefore, this study aimed to provide a methodology to include the air pollution criteria in the process of land use planning for agricultural, urban, and industrial land uses. Accordingly, the authors conducted the land use planning in two scenarios ‘with’ and ‘without’ considering the air pollution. Finally, we prioritized the optimal areas for the sustainable development of the region.

In this study, to evaluate the suitable area for zoning activity (including the agricultural, industrial, and urban), we considered the physical and the ecological criteria with the air pollution ones (including the distribution of PM10 and NOX). Two scenarios were developed as with/without consideration of air pollution criterion. The optimal land use planning was applied for agricultural, urban, and industrial land uses. PM10 and NOX annual dispersion maps were used as air pollution criteria which were simulated by the AERMOD model. Standardization and weighting of the physical, ecological, and socio-economic criteria of the land uses were implemented using the AHP model. Then, to combine the factors, a weighted linear combination technique was applied. The values of this technique ranged from 0 to 1. In this map, higher values represent more desirable areas. After producing six maps from WLC, the suitable areas for each of the zones were combined separately with and without considering the air pollution using the Multi-Objective Land Allocation (MOLA) method. The MOLA method is a multi-purpose method that tries to allocate each land unit to the most appropriate land use. Finally, the optimal land use was selected using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach. Its primary theory is that the preferred option should have the lowest distance from the ideal solution and the farthest from the unpropitious ideal solution.

The findings of the study confirmed that considering air pollution criteria is helping the zoning of the suitable areas and can change the planning strategies for the development of land use. However, the comparison of the two scenarios showed that nearly 73% of agricultural, 85% of industrial, and 64% of urban areas have remained unchanged in both scenarios. Therefore, 27% of the agricultural land area (292 hectares), 15% of the industrial land area (165 hectares), and 36% of the urban land area (393 hectares) were, in fact, unsuitable for development, which was deemed appropriate due to the lack of air pollution criteria in the traditional approach to land use planning. The 2432 hectares of land use included 802 hectares of agricultural areas, 929 hectares of industrial lands, and 701 hectares of urban areas will not change if the air pollution criteria were considered or not considered. As a result, considering four different land uses (agricultural, urban, industrial, and lands without use) for Mobarakeh county, a maximum of 16 different modes of conversion of land uses to each other can be expected, which just ten conversions identified in the study area and no conflicting conversions in these conversions. As a result, the selection of suitable areas for urban areas compared to other land uses is more impressed by air pollution criteria. On the other hand, more stability of industrial lands is related to the fact that the permissible air pollution levels for this land use were different from the other lands. The reason for these changes was twofold: first, the inadmissibility of air pollution limit for each land use; second, the allocation of suitable areas in terms of air pollution in which there was the minimum health effect.

The purpose of this study was to evaluate suitable sites for developing land uses as well as agricultural, industrial, and urban towards achieving sustainable development in one of the most significant places in terms of the environment. According to the results of this study, to evaluate the potential of agricultural, industrial, and urban land uses, in addition to traditional criteria, air pollution criteria such as PM10 and NOX should be considered.‏

The purpose of this study is to allocate multi objectives of agricultural, urban and industrial land uses in Mobarakeh county, by considering the conflicts with other land uses for optimal allocation of land uses. In order to standardize and determine the weight of ecological, physical and socio-economic criteria and sub-criteria for each land use, the AHP model was used and after evaluating the potential of area for the intended land uses that obtained by WLC method, all land uses were integrated by using the MOLA method. In the last step, the best patches for each land use were identified by TOPSIS method. The results of this study showed that all the mentioned areas after the integration of land uses include those pixels whose usefulness in weighted linear combination maps in agricultural land use from 0.98, in industrial land use from 0.86 and in urban land use from 0.9 has been more. Also, by considering the constant weight of three land uses, Mobarakeh county has the sufficient capability to develop approximately 1100 hectares for each land use in the future. Besides land potential for each land use, their conflicts with each other have been resolved by using the MOAL method, it can be claimed whether in the process of assessing the potential or allocating different land uses, the optimal land allocation is used for allocate conflicting land uses, much better results It will lead to a move towards sustainable development thinking.

effective management and protection of wildlife populations depends on human understanding of the relationship between wildlife populations and habitats. The destruction and fragmentation of habitats reduces the living area of local communities, limits them to small habitats, and isolates wildlife populations, leading to increased intra-reproductions, reduced genetic diversity, and eventually the increased risk of extinction in the long run.  Therefore, habitat optimization modeling techniques have been developed based on the analysis of the relationship between species and habitat to determine the range of species’ distribution and habitat suitability which is required for the preservation and management of populations, especially the endangered species. The Gazella subgutturosa is currently protected by the Iranian organization for environmental protection and placed as the vulnerable class in the Red List of IUCN. Characterized by special natural features, Monteh Wildlife Refuge is regarded as one of the best protected habitats for Gazella Subgutturosa. In fact, it is considered as one of the richest habitats in the Middle East in terms of wildlife diversity and the high number of animal species living there, making this biologic field seem much more important. This study sought to evaluate the Gazella subguruttosa’s habitat in Moteh Wildlife and present a desirability model in this regard, trying to identify optimal habitats for Gazella subgutturosa in the region, determine the factors involved in the desirability of such habitats, and discover its limiting and threatening factors. The Gazella subgutturosa habitat threatened the area. Thus, to reduce the interference of human activities with the wildlife activities, it is necessary to identify and preserve areas that are more important in terms of preservation by preparing a map of habitat desirability. This helps identify the most destructive and threatening factors to the habitat and target species, and prevent the reduction of the target population by controlling and eliminating such factors.   

with an area of 205,000 hectares, the Moteh Wildlife Refuge is located in the northwest of Isfahan province, having a cold or semi-arid cold climate. Having surveyed the region in spring, summer and autumn of 2018, this study recorded the presence points of Gazella subgutturosa species in Moteh Wildlife Refuge via direct and indirect observation (the dung and footprints), using the Global Positioning System. Following the review of the related literature and interviews with experts and Moteh Wildlife Refuge’s park rangers, 12 variables were identified, all of which were analyzed in terms of correlation with each other before starting modeling. As for analyzing the data correlation, six environmental variables including maps of distance from rangelands, slop, distance from waterways, distance from agricultural lands, distance from main roads, and distance from mines were selected. The map the desirability of Gazella subgutturosa habitat was, then, developed based on the presence points of the Gazella and environmental variables, presented in two classes of desirable and undesirable. Moreover, the MaxEnt model was validated via the area below the curve which shows the probability of discernment between the points of presence and absence of a model.  

According to the results of the response curves, Gazella subgutturosa prefers areas far from mines and agricultural lands which are near water resources and rangelands, and areas with low slope. The level below the curve was found to be 0.92, indicating that the model worked well. According to the table obtained from MaxEnt, the most important factor in selecting the Monteh wildlife Refuge as the Gazella subgutturosa habitat is its distance from the rangelands, with 33.3% contribution and 36.3% effect coefficient, with the habitat’s desirability considerably decreasing with an increase in distance from the rangelands, followed by slope, waterways, agricultural lands, roads, and mines as other variables involved in this regard. The Jack Naifchr('39')s chart shows that distance from wetlands alone greatly contributed to modeling. The results of the classification of the habitat’s desirability model show that 40240 hectares, equivalent to 19.7% of Monteh Wildlife Refuge are classifies as desirable in terms of the Gazella subgutturosa habitat’s desirability, and 164102 hectares, equivalent to 80.3%, are placed in the undesirable class.  

In this study, the AUC value was found to be 0.92, indicating a very good performance of the model. Moreover, distance from the rangelands was identified as the most important factor in the desirability of the Gazella subgutturosa habitat, with the habitat’s desirability considerably decreasing with an increase in distance from the rangelands. The findings also suggested that Gazella subguruttosa prefers areas near the rivers. The results of other studies also indicate the high importance of water resources for Gazella subgutturosa species. In general, monitoring and careful management of water resources, preventing the advancement of mines, and controlling the entry of domestic livestock to prevent the destruction of regional vegetation are some important measures that should be carried out in managing the habitat of this species.ش

Road networks as an integral part of the transportation infrastructure have deleterious ecological effects on habitats and wildlife populations. Vicinity impacts of road networks on habitats together with habitat fragmentation have caused decrease in habitat quality, biodiversity decline. Road networks development is one of the most important risk elements for valuable habitats and species of the Chaharmahal & Bakhtiari province. So, it is necessary to evaluate habitat’s condition and ecosystem services into conservation systematic planning and minimizing its negative impacts. For this purpose, first, the habitat quality of Ovis orientalis Gmelin, (subspecies isphahanica Nasonov), Panthera pardus Pocock, and Ursus arctos Linnaeus,were modeled using Integrated Valuation of Environmental Services and Tradeoffs (InVEST). Then, the vicinity impacts of road networks was assessed using the Vicinity Impact index. To assess the efficiency of the current protected areas network and identifying the priority areas for conservation the Marxan software was used. Results revealed that a large area of the Ch & B province were considered as the suitable habitats for target species. However, high density of the road networks affect 14% of the Ch & B ares which increased the impotance of identifying the prioirity areas in terms of high ecological values and low vicinity impact. The results also showed that eastern, western, and southwestern parts of the province have high ecological values and low vicinity impact. Approximately, 28% of these areas are currently protected which showed the relative efficiency of the current protected areas network.

In recent years, the rapid growth of cities has been led to an increase in the production of various types of solid wastes in urban areas. Although landfilling is the last step in municipal solid waste management, but it is one of the common methods in developing countries’ municipal solid waste management. The purpose of this study is to accurately locate urban landfills in Naien county by using a combination of fuzzy and boolean methods.

In this study, AHP model was used to standardize and determine the weight of criteria and sub-criteria. The innovation of this research is the combination of the results of fuzzy and boolean logic. The fuzzy method consists of two groups, the first group is calculation the weight of criteria and the other one by calculating the weight of sub-criteria, and the results of boolean logic with five classes including calculation the weight of criteria and sub-criteria.

The results of this study show that the mentioned fuzzy and boolean methods have identified 34, 48779, 16000 and 7630 hectares of areas in Nain county as the most suitable areas for creating urban landfills. According to the weight of methods, a single map with four main patches is resulted by combination of these four methods, which includes a total of 5055 hectares in Nain.

The results of this study show that the combination of fuzzy and boolean logic results provides better areas for landfill than using the methods individually.

Industrial and economic developmentalong with population growth and increased exploitation of natural resources may upset the environmental balance. Inappropriate land use, along withpollution and destruction of natural resources are considered to be serious problems caused by environmental imbalance in many parts of the world. These problems indicate the limited capacity of environment to resist human exploitation of land. Industrial site selectionis considered to be one of the key factors in sustainable regional planning due to the different environmental impacts of industries. Because of the developmentin industrial areas and the existence of numerous mines in GolpayeganCounty, it is necessary to optimize industrialsite selection in accordance with environmental standards and regulations. Therefore, the present studyintegrates hierarchical analysis with multi-criteria evaluation methods to investigate 24 different criteria with the aim ofoptimizing industrial site selection in accordance withenvironmental standards and regulations in GolpayeganCounty.  

In accordance with the rules and regulations of setting up industrial and manufacturing units and similar studies,the conceptual model of Golpayegan county site selection was prepared based on three criteria: physical, biological and socio-economical. Followingthe preparation ofinformation layer for each criterion, spatial analysis ofEuclidean Distance was performed for each of them.Then, information layers produced in the previous steps were standardized using Boolean and fuzzy logic. The integration and overlapping in Boolean method was performed using AND logic.At this stage, all the information layers were entered into TerrSet software and standardized using fuzzy model and membership functions of the software’sfuzzy sets. The real scale (from 0 to 1) was used in this study to determine the membership function.Higher membership value in this range indicates higher utility while lower membership value indicates lower utility. In the present study, AND operator was used to integrate maps.Hierarchical analysis was used to determine the weight of each factor. Afterwards, the maps were integrated using fuzzy overlay method, weighted sum model and weighted linear combination (WLC) method. In this way, a map was produced for the industrial park site selection. Then according to the histogram curve and its breakpoints and also according to the environmental conditions of the region, it was classified into 5 classes.  

An inconsistency rate of 0.04 was calculated in the present study to evaluate the accuracy of judgments made about the weight of the criteria and sub-criteria.Distance from Mouteh Wildlife Refuge, distance from faults, distance from wells and distance from roadswere identified as the most important criteria for assessing the industrial capacity of the region. Maps produced using the Boolean method include two classes of 0 and 1,the valuesin the fuzzy overlay, weighted sum and weighted linear combination methods rangebetween 0 and 1, while they range between 0 and 0.7 in the weighted sum method and between 0 and 0.8 in the weighted Linear combinations method. 2783.5 hectares of the study area have the potential of serving as industrial sites based on the Boolean method, indicating that 1.7% of the study area is suitable for industrial construction. Combining moderate, good and highlysuitable classes using fuzzy overlay method showed that 1769.13 hectares or 1.1% of Golpayeganregionare suitable for industrial site construction. Combining good and highlysuitable classes usingweighted sum method showed that 1758.77 hectares or 1.09% of Golpayeganregionare suitable for industrial site construction. Combining good and highlysuitable classes using weighted linear combination method showed that 1902.78 hectares or 1.18% of Golpayeganregionaresuitable for industrial site construction. No matter which method is used, suitable areas for industrial site constructionare located in the southeastern region of the County and in vicinity of the main road.  

Comparing the results of the present study with similar studies indicates that the Boolean logic finds the least number of suitable areas for industrial park construction and its selected areas must have an appropriate score in all evaluation criteria. Findings indicated that due to the specific characteristicsof the Analytical Hierarchy Process, this method can be useful in the investigation of regional planning issues. It can be concluded that Weighted Sumand WLC are more effective than Boolean and fuzzy overlay methods. Results indicate that all four models located landssuitable for industrial development in the southeastern areas of ​​the County and in vicinity ofits main road, thus these areas should be prioritizedin future planning, policy making and investment for industrial development. Furthermore, given the concentration of agricultural activities in GolpayeganCounty and its numerous tourism capacities, the development of agricultural conversion industries and ecotourism related industries within the predicted authorized areas can be considered as priorities of regional development. Nowadays, sustainable economic development in most countries depends on industrial development. Sustainable development of industries creates more opportunities for social and economic growth. Sinceappropriate site selection for industrial parksharmonize the goals of economic development with the goals of urban development, economic enterprises and environmental objectives, it is considered to be a step toward sustainable development. Achieving such a goal requires a revision of the site selection criteria in accordance with the sustainable development indicators. This increases national and local employment rate and accelerates industrial growth without damaging the environment. .

Land suitability evaluation plays an important role in environmental sustainable management. Besides, it is a prerequisite for land planning which affects sustainability of the activities and sustainable development. The current study aims to evaluate and model the agricultural, urban and industrial development in Great Isfahan (as the most crowded center of Isfahan province and the most important agricultural and industrial hub of the country) using the data in 2018. Land-use planning is increasingly focusing on the aspects of environmental conservational and sustainable development. Choosing the appropriate areas for this purpose is a complex process which requires lots of effective factors. We use multi-criteria evaluation of the land-use allocation models applying geographic information system. First, the required data (including topographic variables, water resources, geology, land-use, accesses, infrastructure factors, biological resources, soil and climatic parameters) were identified, suitability maps were prepared using fuzzy method, and the weight of the factors was determined employing the analytic hierarchy process. Then, the prepared maps were combined using the weighted linear combination method. Finally, the final maps of land-uses suitability were prepared and classified according to the expert opinions. The findings show that approximately 586.9, 197.2 and 24 km2 (20.3%, 6.9% and 0.08%) of the total area of the region is suitable for agricultural, urban and industrial development, respectively. Besides, the northwest and southeast of the region are in an appropriate area. We conclude that MCE and GIS techniques are effective tools for land evaluation and planning. The results of the present research can be used as a multi-criteria decision analysis to obtain a deep insight into the sustainable use of natural resources. Moreover, three possible scenarios (current ecological and socio-economic trend, conservation of agricultural lands and urban-industrial development) can be designed and modeled based on.

Evaluation of land capability is a way of knowledge of nature and preventing its destruction. The Logic scoring of preference method is one of the new approaches in land evaluation. This method consists of three main components: the attributes tree, the preliminary criteria and the aggregation structure. Criteria and sub-criteria of the conservation model, criteria weightings and standardization functions were determined by the resources reviewing, environmental attributes of the area and consulting with local experts. Then, the decision tree is formed, after that, the sub-criteria, criteria and attributes were weighted. Their replacement capability was determined. Replaceabilityorsimultaneitymeans identifying importance of criteria and sub-criteria in decision making. So, more or less effect of criteria was determined on the final decision by the ranges of positive and negative numbers. Aggregation of criteria and sub-criteria were done by Weighted Average Power Method. Conservation maps were prepared with two scenarios without_with the replaceability criteria. Scenario result of without replaceability shows the region's conservation value better than the replaceability scenario. The research results showed that rivers and aquatic ecosystems, scarce native plants and Mountains with high slope and shallow soil are sensitive to degradation. The proposed GIS-based LSP method is an enhanced MCE approach that represents an excellent tool for discussion and deliberation among stakeholders, decision makers, land-use planners and other experts.

Climate change and human activities have increased negative pressure on natural ecosystems. Wetlands are such ecosystems that widely affected by these negative changes. Birds as a part of wildlife in a wetland have damaged by destruction of wetlands, so, a large group of them, are at risk of extinction. Habitat destruction in wetlands in arid and semi-arid areas has more negative effects on these birds because of water limitation in these regions. Hamun wetland on the boundary of Iran and Afghanistan is one of the vulnerable ecosystems that are faced by the effects of drought and human activities. Since this wetland has international importance for breeding and resting of migrant water birds, determination of habitat requirements and spatial distribution of water birds in this wetland are essential. In this study, by field studies and Maximum Entropy model, suitable habitats of water birds and waders were determined in 2015. Based on these results, southern parts of Hamun_e_ Saberi and some parts of Hamun_e_ Himand and Pouzak were determined as suitable habitat for water birds. Results of this paper are useful for conservation activities in this wetland.

Investigation of the future trend of changes in the density and health of the vegetation due to climate and land use/land cover changes can be useful in ecological and environmental studies using time series data especially in dry and semiarid brittle ecosystems. Time series analysis is a powerful tool for investigating the trends of natural phenomena in the past and present. The Satellite Time Series provides the most appropriate data for analysing the trend of changes in natural and human phenomena and predicting for the future. A time series is the collection of statistical data collected at regular intervals. Determining the trend (increasing, decreasing and unchanged) of the vegetation can be one of the ways to help manage vegetation monitoring. In this regard, the use of statistical tests to determine the trend of time series data is essential. There are different methods for determining the process, which are divided into two sets of parametric and nonparametric methods. Since satellite imagery is one of the best time series illustrations, the use of these data in trend studies is fruitful. Vegetation indices are used to monitor and evaluate vegetation dynamics using satellite imagery. NDVI is the most famous useful in plant monitoring. The NDVI, is used as a useful indicator of photosynthesis capacity identification, usually used to examine environmental and ecological changes. Therefore, remote sensing through the NDVI satellite index can measure surface vegetation changes due to the strong correlation between the vegetation and this index. The NDVI is also reliable for identifying vegetation stress because, as a result of degradation of vegetation in the land, vegetation characteristics such as health, density are majorly changed Materials and methods Monthly MODIS NDVI times series images from the MOD13A3 series, were collected from the site of NASA from 2003 to 2014 (144 images). Then the images from Gavkhuni basin have been extracted to determine the trend of vegetation changes. Mann-Kendall test was presented based on the significance of the Tau Kendall correlation coefficient (τ) and then developed. Correlation coefficient measures the relationship between two series of variables to determine if the first variable increases with increasing the second variable, or decreases or the patterns of change are not relate together. This method is widely used to handle time series. In general, Mann-Kendall statistical test can be used to determine the uniform trends of ubnormal distribution data based on the ranking. Given that the Mann-Kendall test, in addition to the trend, also specifies the type of trend occurring, this model does not require the input of normal data. In the test, for time series data trends, positive values indicating incremental trends and negative Z values represent decreasing trends. Results Vegetation fluctuations of mean monthly MODIS NDVI time series images of Gavkhoni basin from 2003 to 2014 were presented. The maximum vegetation cover is observed in spring months. This increase reached its maximum during the course of the study in 2007, and then reached its maximum four months later and then sharply declined in 2008. In 2009, vegetation cover in Gavkhuni basin is relatively modest. In fallowing, the fluctuations are almost the same, but declined sharply in 2014. In addition, the highest vegetation density is observed in the western and central regions of Gavkhuni basin. Also, this figure shows that vegetation density is high in 2003-2006 and has declined significantly by 2014. Accordingly, the vegetation cover increased in January 2003 through January, a dramatic drop in February, a slight decrease in March to May, a modest increase in June to July, a slight increase in the months of July to September, in October And November has been a slight decrease, and December has seen an increase in vegetation. The trend of long-term vegetation changes in Gavkhuni basin based on 144 images of the monthly MODIS-NDVIwere implemented in the Idrisi Tersset software. At first 144 time series images were converted into TSF file format. The resulting trend map indicates that the vegetation trend is incremental with a value of τ equal to 0.68 to a decreasing trend with the value of τ equal to -0.65. Accordingly, the trend of increasing vegetation is more dispersed in the north-eastern and central to west parts of the basin, and slightly to the south of Gavkhuni basin. In addition, the largest decline in vegetation occurs in the central regions of the east and south of Gavkhuni basin. This trend is evident in the northern and western basins as well as in the south of the basin. In addition, decreasing trend of vegetation is more concentrated in areas of basin which referring to the use/land cover map are aquaculture. This trend indicates a sharp decrease in the rain-fed agriculture. Referring to the land use/land cover map, the vegetation cover of the Gavkhuni wetland during the study period has also been subject to decreasing or unchanged trend. The vegetation of the rocky areas of the north-east of the basin has also increased marginally. Accordingly, the most extensive areas indicates unchanged trend of vegetation in Gavkhuni basin. The results showed that the largest decline in vegetation was observed in 2007, when the catchment area was faced with drought at this time. Also, the annual average vegetation map in 2014 with the least amount of vegetation density has been encountered. Due to the fluctuation of vegetation, the need for serious attention of planners is required because it can be said that vegetation as the representative of environmental health also reflects the characteristics effective biophysics in growth, such as adequate water, undiluted and nutritious soil, etc., provide both the protection of wildlife and soil conservation against erosion. Also, since vegetation cover has declined from 2003 to 2014 in the months of April and May (when is the beginning of the growth season in the Gavkhuni basin), it indicates a crisis in agriculture in the Gavkhuni basin. The regional variations of vegetation in Gavkhuni basin from 2003 to 2014 through the time series images of MODIS NDVI was determined using non-parametric Mann-Kendall Tau and contextual tests, and areas with increasing, decreasing and unchanged vegetation cover were determined. The results showed that the extent of the vegetation variation trend as well as the extent of the decreasing trend in the Contextual Mann-Kendall method was more than Tau Mann-Kendall, and the trend in most of the area remained unchanged, which only indicates whether vegetation is present in this area or not. This case is achievable by comparing the trend map with land use / land cover map in 2014 or following years. In addition, it was revealed that the decreasing trend with the sever vegetation decline has occurred in the central regions of the Gavkhuni basin and along the Zayandehrud River and also in the urban areas, which can indicate the high urban growth and land use /land cover change from the vegetation to the construction site in this basin. Accordingly, a sharp decreasing trend was observed in the northern and western regions as well as in the south of the basin, which with referring to the land use /land cover maps and type /vegetation maps, these areas are highest proportion of rangeland vegetation and fertile farming along the Zayanderroud River. These lands affected by land cover/land use and have been severely subjected to land degradation due to the dryness of Zayandehrud Rive in recent years. This urged urgent measures to prevent land degradation. In addition, since the highest reduction in temporal monitoring in the Gavkhuni basin has been observed in the months of April to June, and these months are growth season and cultivation in the Gavkhuni basin, this necessitates a serious actions to mitigate the risks. Also, the study of vegetation trends showed that during the study years, saline lands in the Gavkhuni basin increased and the agricultural land was significantly reduced.

Soil is one of the most important production factors that has a great impact on human socio-economic life and the process of soil erosion is one of the environmental issues that threatens the environment, natural resources and agriculture. Spatial and temporal information of the soil loss and soil erosion on the land has a significant role in influencing management practices, soil erosion control and watershed management. Therefore, this study was conducted with the aim of studying the spatial and temporal estimation of soil erosion during 1994, 1999, 2008 and 2015 in the sub-basin of Menderjan with an area of 21100 hectares located in the west of Isfahan province using RS and GIS. In the present study, while conducting field studies, various data and information including the digital elevation model, satellite images, soil, and statistics on rain gauge stations were used as a research tool. Estimation of soil erosion in the study area was carried out using RUSLE Model. The results of this study showed that the amount of soil erosion in 1994, 1999, 2008 and 2015 was 0.001 to 233, 0.001 to 297, 0.001 to 231 and 0.001 to 215 "ton/”ha.year”. The topography factor in the study area with the correlation coefficient of 80% had the greatest effect on the estimation of annual soil erosion by the RUSLE model. This research corroborate the effectiveness of modern GIS technologies and remote sensing in temporal simulation for quantitative, exact, and point-to-point estimates in the whole area to obtain soil erosion content.

Desertification means land degradation in arid, semi-arid and dry sub-humid regions as a result of various factors, including climatic variations and human activities. In this research, the study area with an area of 136 thousand hectares located 20 kilometers far away from east Isfahan was selected. Due to the proximity of this area to Isfahan city and the impact that desertification phenomenon on the city, studying the desertification in this region is of great importance. To assess the current status of desertification, the multi criteria Analysis and MEDALUS model was used. For this purpose, in the first step and based on the local situation, six qualitative criteria, including climate, soil, groundwater, vegetation, soil erosion, desertification management and policy evaluation were considered. These indices have been standardized and quantified based on their effect on desertification in the frame by scoring 100 to 200. The qualitative value of each criterion has been obtained by multiplying the weight of the Analytic Hierarchy Process (AHP) and integration of layers based on the weighted linear combination. Finally, the desertification status map has been acquired through multiplying weight to the layer value of each criterion and integrating layers according to the method of weighted linear combination in Geographic Information System (GIS). According to the results, 35.49% of the area of the region falls in a severe class and 64.5% falls in very severe class of desertification. Besides, the climate criterion with a weight of 0.29 has the greatest impact on the phenomenon of desertification and then it goes to the management and soil criteria with weights of soil 0.23 and 0.21, respectively. Therefore, to assess desertification and executive programs to deal with it in the region, considering these criteria are of great importance.

Vegetation is the most important factor influencing the sustainability of rangeland ecosystems. Therefore, it is important to understand the environmental factors and their effect on vegetation and restoration of rangeland ecosystems. The aim of this study was to identify factors influencing on Gundelia tournefortii L. distribution. Accordingly, the information of Gundelia tournefortii L. was determined in six habitats in Isfahan province. Random- systematic sampling was conducted to calculate canopy and density of the species. In each rangeland place, climate, physiography and soil factors were identified. RDA ordination analysis using CANOCO software was used to investigate the vegetation relationship with environmental factors. In the cluster analysis and RDA ordination analysis, six main habitats of the species were classified into three groups. The first axis of ordination showed a very strong correlation with canopy cover and density and the second axis showed a very strong correlation with soil depth. According to study of the habitats of this species, annual precipitation about 250 to 500 mm, altitude 2300 to 2500 meter, slope about 10 to 40 percent and average of annual temperature about 10 ̊C to 12 ̊C are appropriate for presence of this species.

The present study aims to improve the assessment, soil salinity accuracy, using of OLI Landsat satellite image dated to 26 May 2015 and topographic parameters in the eastern region of Isfahan. Ground data were collected in date second half May by using the random sampling method from 29 sampling sites from the depth of 0-30cm. Spectrum indexes include OLI sensor bands, salinity indexes SI1, SI2 and SI3, soil indexes SBI and SCI, and vegetation indexes NDVI and RVI were obtained from processing referenced ground images. Also, topographic feature including slope percent, orientation of slope and elevation from sea level were extracted from Digital Elevation Model (DEM), then to estimate the salinity linear regression the stepwise method model was used. From analysis, regression indicated that on 99% statistical level, there is a meaningful correlation between EC of topsoil samples, elevation from sea level and band 4 (R2=0.68). The salinity map acquired from the regression model indicates the salinity is very high in the region so that more than 70% of the area has a salt concentration of more than 60 ds/m. Finally, the reliability of the model was evaluated using 20 percent of the samples. Results indicated that the model can estimate soil salinity by an RMSE=6.54 ds/m. According to the research results, Conclusion They are using elevation from sea level parameter with satellite data is Beneficial in the soil salinity research and causes improve the accuracy of the assessment.

This study aimed to evaluate the effects of environmental factors on plant species production in some range sites in Isfahan province. Systematic randomized sampling was performed during 10 years (1377-1387). Four and six parallel transects with 400 and 200 meters lengths were established in each of Steppe and semi Steppe sites respectively. Fifteen 1 by 2 meters plots and ten plots with size of 1 by 1 meter were established along each transect in Steppe and semi Steppe regions respectively. The production of plant species were recorded in each plot using double sampling method. Grid layers of bioclimatic and topographic variables were prepared in ArcGIS 10.1 and values for each range site were extracted. Soil samples were collected from range sites and some physical and chemical properties of the collected samples were measured. Canonical Correspondence Analysis (CCA) was used to evaluate the relationships between environmental factors with the plant species production. Cluster analysis was also used to group the studied range sites based on environmental factors. According to the results, minimum temperature of coldest month, annual mean temperature, electrical conductivity, calcium carbonate and sand percentage in steppe region and precipitation of wettest month, annual precipitation, elevation, organic matter and potassium in semi Steppe region were identified as the most important ecological factors affecting plant species production. Maximum of mean plant species production in Steppe was 64.4kg/ha and semi Steppe 144.1kg/ha. Sixty Steppe was from shrub species while grasses composed 56 percent of production in semi Steppe region.

In the recent years, human activities have led to changes in land use and land cover, consequently, these changes lead to the structure and function of ecosystems. Spatial-Temporal Change Detection of land use is important to understand the relationships and interactions between human and natural resources and to make appropriate decisions Due to changes in land use and land cover occurs in broad surfaces, therefore, remote sensing technology is a useful tool for evaluating changes. The aim of this study is to investigate trend change of land use and land cover of the surrounding of the Zayandeh Rood River, as well as to investigate the water demand for agricultural land use of remote sensing and GIS techniques. For this purpose, the OLI images in 1392 and ETM Landsat images of 1382, after correction and preprocessing required, land use /land cover map were produced using the hybrid classification, based on maximum likelihood image processing in 10 classes. The post-classification methods was used to monitor changes in the period of 10 years. The results showed that in the period, dried, more than 40 percent of the Gavkhooni wetland and Zayandeh Rood, the area as well as suffering damage to the structure and the physical – social and ecological sustainability. 19/2 percent increased was observed in the agricultural land in the western part of the study area when the amount of water consumption in the western part in the period 1382 -1392, 52/59 and 60/22 percent, respectively. After that central part, and the lowest water consumption was calculated for irrigated farming in the eastern part. Salty lands have been developed during this period, more than 90 percent. Urban expansion has occurred in the period 1382 -1392 with an area of ​​552 hectares per year.