فهرست مطالب مرتضی عبیات

Desertification is one of the factors in the destruction of natural ecosystems in arid regions of the world. Knowing the areas exposed to desertification is very important to combat this phenomenon. Remote sensing is a practical tool for evaluating and monitoring land degradation and desertification. The current research aims at the desertification intensity evaluation in Bandar Mahshahr County based on the spectral indices derived from satellite images. To begin with, utilized the ENVI software to extract several indices, such as NDVI, SAVI, RVI, TGSI, and Albedo, from the satellite image captured by the Landsat 8 OLI in the region. Then, Linear regression was utilized to determine correlations of spectral indices in the region, and the desertification intensity in the region was classified. The results showed that the correlation coefficient between NDVI and Albedo indices was -0.83, between SAVI and Albedo indices was -0.78, and between RVI and Albedo indices was -0.77. The correlation coefficient between TGSI and Albedo indices was 0.86. The higher correlation between TGSI and Albedo indicates that the Albedo-TGSI model is more appropriate for evaluating the desertification intensity in the region. The desertification map of the Albedo-TGSI model showed that the areas with less desertification intensity are located mainly in the northern and eastern parts, and the areas with more desertification intensity were situated in the southern and southwestern parts of the region

The objective of this study is to investigate spatial relationships analysis of the concepts of life quality, social capital, and rural entrepreneurship in Dezful County, which was done through the descriptive and analytical methodology and data collection by field and survey methods. To pursue the issue, 147 target villages were selected based on the Cochran formula from 238 in-habited rural areas in Dezful County. The principal research tool is a researcher-made questionnaire containing 250 manifest variables extracted from 23 latent variables in triple concepts. The statistical population consists of 30,032 household heads in the target villages, and questionnaires were randomly distributed among 379 of them based on Cochran's formula and multi-stage sampling method. The statistical population consists of 30,032 heads of households in the villages of this county. Ques-tionnaires were randomly distributed based on Cochran's formula and multi-stage sampling method among 379 family heads in the target villages in eleven rural districts of this county. In this research, the analysis of pairwise and general relationships between concepts was done through structural equation modeling (SEM) and investigating the situation of the Dezful's villages in relationships between structures utilizing gray relationship analysis (GRA) and fuzzy analysis. The results showed that the paired relationships of the concepts had a significance level lower than the assumed error rate of 0.05 evaluated as direct and positive. The highest and lowest relation-ships of the constructs belong to the relationship between life quality and social capital and the linkage of life quality and rural entrepreneurship with path coefficients of 0.949 and 0.875. Based on the layers combination of GRA and fuzzy analysis, the nearly two-thirds situation of the target villages is inappropriate in the general relationships of research concepts.

Estimation of soil moisture is essential for optimal management of water and soil resources. Landsat images with appropriate spatial and temporal resolution are good tools for these studies. The purpose of this study is to estimate and zoning the soil surface moisture in agricultural lands of Shushtar County in Khuzestan province using remote sensing indicators. To do this, first 25 soil samples of agricultural lands were taken from a depth of 0-15 cm and their moisture was measured. Then, normalized vegetation difference index (NDVI), soil reflection adjustment index (SAVI), surface temperature (LST), normalized moisture difference index (NDMI), normalized agricultural differential index (NDTI) and soil moisture index Infrared short band (SMSWIR) were applied to the Landsat 8 Image. In the next step, the values ​​of these indices were transferred to SPSS software for statistical regression and the soil moisture estimation functions were obtained by multivariate linear regression. The results showed; Due to the high coefficient of determination (0.73) and the low root mean square error (1.31) in the simultaneous method (Enter Method), this model was considered suitable for estimating and zoning the surface moisture of agricultural lands in the region. According to the research results, soil surface moisture was directly related to NDVI, SAVI, NDMI, NDTI and SMSWIR indices and inversely related to LST index. Also, LST index has a better estimate of soil moisture, which indicates a significant effect of this factor on the amount of soil surface moisture.

 Agriculture is the essential sector for promoting food security. Crop area estimation (CAE) can meet the requirements of the crop monitoring plan. The organizing basis of the cultivation pattern is recognizing the types of crops and examining the condition of their crop area. Shush county in Khuzestan Province has 300,000 hectares of the crop area. It is one of the agricultural hubs of Iran because it has a record annual production of more than two million tons of strategic crops such as wheat, sugar beet, and corn. CAE affects the amount of net production and shortage or surplus of produce for market steadiness. Traditional approaches for CAE are time-consuming and costly and are not widely enforceable. Remote sensing (RS) data provide good information for decision-makers by determining the crop type and the crop area. RS data has made it possible to avoid continuous reference to agricultural lands with less time and cost than another usual method and accurate CAE. Also, the use of multi-time images during the growing season of agricultural products allows the use of spectral curves when related to the crop calendar of each crop. This spectral curve is almost separate for each product and increases the ability to distinguish between products. Therefore, multi-temporal images support segregation based on multispectral images of products. The current study follows a speedy method with appropriate accuracy established on satellite image classification algorithms and spectral indices to identify and separate crops with RS data in Shush County.

 Landsat-8 data with path/row coordinates 166/38 extracted from the USGS website were used to identify and separate the cultivated lands of the region. The reason for choosing Landsat images is the relatively suitable temporal and spatial resolution, availability, and the appropriate time distribution with the product growth period. The Landsat 8 carries 2-sensors, OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor). The OLI sensor with a spatial resolution of 30 meters has 8-bands in the visible spectrum, near-infrared (NIR), short-wavelength infrared (SWIR), and a panchromatic band with a spatial resolution of 15 meters. The TIRS sensor can record thermal infrared radiation with a spatial resolution of 100 meters with the help of 2-bands in atmospheric windows of 10.6 to 11.2 micrometers for band 10 and 11.5 to 12.5 micrometers for band 11. This research used bands 1-7 of the Landsat-8 OLI sensor with a spatial resolution of 30 meters after the initial corrections of satellite images. The spectral similarity between the region's dominant crops has made it impossible to select a single image to differentiate and extract the cultivation pattern. Wheat and barley have a high spectral similarity. The peak of the greenness of these products is in the first four months of the year, which has high NDVI values at this time. Therefore, choosing a good time to separate the crops was feasible by referring to the Khuzestan Organization Agriculture-Jihad (KOAJ) and receiving the regional crops calendar in 2018-19. Then, the low-level cloud cover images on April 24, June 27, and August 30, 2019, were selected for classification based on the crop calendar. Planting, harvesting, maximum greenness, and ripening information of the dominant crops in the area were pivotal in obtaining image dates. In dates selected related to the images were considered planting, harvesting, maximum greenery, and ripening information of the region's dominant crops.

 According to the results, from total crop area in Shush county (163313.7 hectares) is allocated about 103513.2 hectares (63.4% of the county's crop area) to the ANN, about 102875.1 hectares (63.0% of the county's crop area) to the SVM, and about 102,277.3 hectares (62.6% of the county's crop area) to the NDVI, which in comparison with the KOAJ statistics, has an error of 0.11, 6.2 and 1.8%, respectively.
This difference is the similarity of the reflective spectrum in some places, which affects the separability and recognition of phenomena and increases the error in estimating the area under cultivation of different crops. The highest and lowest errors in estimating the area under cultivation in the artificial neural network method were in barley and rice crops, respectively, in the support vector machine method were in wheat and rice crops, respectively, and in NDVI index were in wheat and barley crops, respectively. The difference between the cropped area obtained from classification methods and NDVI index with cropped area statistics of Agricultural-Jihad Organization may be due to the following: First, the cultivation history of different has caused problems such as reflections of diverse agricultural lands in one image. Second, the agricultural lands in this area are small. Most of them are under one hectare. Also, the crops in this area are diverse. Third, the smallest region that the image used in the present study can distinguish is about 900 square meters, which is a large number for the agricultural lands of the study area and causes errors.

 The study results showed that the support vector machine method had the lowest error in CAE than the artificial neural network method, which indicates the higher accuracy of the support vector method in identifying and separating crops in the region. Comparing the area obtained from the NDVI index with the statistics of the Agricultural-Jihad Organization of Khuzestan province and evaluating the accuracy of this method indicated the higher efficiency of spectral indices in CAE for the region compared to classification methods. The NDVI index minimizes the error values of the results due to having a threshold and better identification of vegetation density. Therefore, based on the accuracy assessment results and comparing the cropped area with the KOAJ statistics, the utilization of the NDVI index provides the best CAE in the region.

Human activities such as land-use changes have a significant effect on the Earth’s surface temperature and the creation of heat islands. This study aimed to investigate the impact of land-use changes on the temporal-spatial pattern of the surface temperatures and heat islands in Shooshtar township between 2002 to 2020. First, the Landsat 2002, 2013, and 2020 images were classified using object-oriented processing methods, and then the Earth surface temperature was extracted by the split-window algorithm. Having measured the temporal-spatial changes in the surface temperature and the heat islands, the indices NDVI, UHII, and UHIII were implemented. The results showed an increase in Built-up areas as well as Barrenlands by 21895.40 and 26761.04 hectares, individually. By contrast, the Vegetation cover and Waterbodies decreased down to 43790.79 and 4865.64 hectares, respectively. According to the results, the maximum temperatures index revealed an uptrend in the temperature of all the landuses; there has been a constant increase with an amount of 7.40, 7.42, 6.82, and 6.87 degrees Celsius in the temperatures of the landuses the Vegetation cover, Barrenlands, Built-ups, and Waterbodies, respectively, during the 2002-2020 study period. The UHII and UHIII indices showed that the low land-cover class had a higher temperature than the classes with medium and large land-covers. Furthermore, the heat islands were distinguishably formed by 2013 and 2020 most in the northern, southeastern, and northeastern areas of Shooshtar township.

Soil erosion is a natural process that causes the level of soil loss by various environmental factors such as climate, soil, topography, and vegetation. However, human intervention can accelerate this process through land-use change and agricultural and construction activities. Therefore, today, soil erosion due to land-use change has become the most important issue of land degradation around the world, which results in landform change and disruption of the main functions of the ecosystem. These geomorphic reactions exacerbate soil erosion and increase the number of vulnerable areas. Recent studies have shown that the landscape characteristics of watersheds can explain about 65 to 74% of land-use changes in soil erosion and sediment yields; Because land-use reflects the interactions between humans and the environment and also describes the diverse human exploitation of space. The use of remote sensing data and GIS can provide a good understanding of how land-use changes and its optimal management. Also, by knowing the trend of land-use change, we can take steps towards balance and stability to prevent soil erosion and guide the ecosystem. Baghmalek Basin in Khuzestan province is one of the areas that are affected by human factors of soil erosion and factors such as land-use change, overgrazing, and interference in natural flood channels have intensified soil erosion and loss in the region. Degradation of rangeland lands and also lack of proper tillage operations on rainfed arable lands have been effective factors in erosion and sediment production in the region. In sloping areas, erosion has been rapid and accelerated, and erosion has filled irrigation canals. Also, due to the use of traditional methods in agriculture, the water stays on the soil for a long time and causes soil erosion and leaching downstream. In many parts of the basin, the land was not suitable for rainfed cultivation, but this type of cultivation was done in these areas and this action has caused the destruction and loss of soil in the basin. Therefore, according to the mentioned cases and also the importance of studying land-use change and their role in soil erosion over time and also emphasizing the efficiency and accuracy of the results of using remote sensing data and GIS, land-use changes in the basin Baghmalek and their role in soil erosion and sediment production (2019-2002) were studied.

In this study, an artificial neural network method was used to classify images and prepare land-use maps. Multilayer perceptron was used to classify the neural network. RUSLE model was used to estimate the average annual soil erosion. To extract the final soil erosion map, first, all the factors of the RUSLE model including R, K, L, S, C, and P were converted into GRID format maps and 30-meter scale, and then by multiplying all these layers, the amount of erosion The soil was calculated at the pixel level and the final map of soil erosion in the study basin was obtained. In fact, during this process, the information in the layer-specific pixels identified based on the RUSLE model relationships was combined in the GIS software environment by the Raster Calculator tool. In order to explain the possibility of sedimentation of eroded material and its movement in the canal network and finally, in the outlets of the basin, the values of the SDR sediment delivery ratio of the study area are calculated. To evaluate the effect of land-use change on soil erosion, the land-use map was compared with the soil erosion map of the same year and for each cover layer, the amount of erosion and the area of erosion floor was determined, which is given in the results section.

The results of land-use change showed that residential areas, barren lands, and rainfed agriculture increased by 1722.69, 3445.39, and 2584.04 hectares, respectively, and water zones, rangelands, and irrigated agriculture by 861.341, respectively, 42/6029 and 35/861 hectares have lost their area. Taking into account all the factors, the average landing limit is about 15 tons/ha/year, which for 2002 is 19.69 percent of the area and for 2019 about 45.36 percent of the area, the amount of erosion is more than acceptable have been. In this study, the sediment delivery ratio was between 0.12 to 0.23 and the maximum sediment load in the study area was between 0.29 to 0.58 and the total sediment was between 81051 to 313248. According to the results obtained in 2002, the area of floors of water zones, residential, barren lands, pastures, rainfed agriculture, and irrigated agriculture with erosion class of 10-15 ton/ha/year with an area of 818/28, 981/93, 83/83, respectively. 2454, 74/3927, 74/3927, and 05/4255 hectares, which have been changed to 654/62, 2490/24, 31109, 46/1582, 4418/70, and 4091/39 hectares in 2019. Also in 2002, the area of floors of water zones, residential, barren lands, pastures, rainfed agriculture, and irrigated agriculture with erosion class of 15-20 ton/ha/year from 90/41, 826/89, 2067/23, 4/341, respectively, 57/3307 and 95/4702 hectares have been changed to 533,723, 52/1086, 49/2618, 00/3075, 01/3721, and 06/4522 hectares in 2019. The area of residential areas, barren lands, and rainfed agriculture with erosion class of more than 20 ton/ha/year from 361.76, 904.41, and 1447.06 hectares in 2002 to 475.35, 1145.59, and 1627.94, respectively. Hectares in 2019 have increased. Also, the classes of water zones, pastures, and irrigated agriculture with erosion class of more than 20 ton/ha/year from 1593.49, 7664.75, and 8286.15 hectares in 2002 to 1274.79, 5417.86, and 7967.45, respectively. Hectares in 2019 have decreased. The general results show that in the study period between 2002 and 2019, the area of land-use classes with low erosion class has decreased and the area of high erosion classes has increased, mainly to the erosion class of more than 20 tons/ha/year.

The results showed that the increase of residential areas, rainfed agricultural lands, and barren areas, had a significant effect on increasing soil erosion in the study basin. According to the erosion maps obtained, the areas with higher erosion risk are mainly located in the rugged parts of the region. The results of estimating the criteria studied in the RUSLE method in the study basin indicate differences in soil properties and vegetation in different parts of the basin. According to the erosion zoning maps in the study area in 2002 and 2019, mainly the areas with the highest risk of erosion are located in rangeland lands and rainfed agriculture. The results of comparing the USDA, Vanoni, and Boyce methods with the amount of sediment load observations showed that the USDA model had better results in estimating the total sediment amount due to the low error rate compared to the Vanoni and Boyce methods. Also, comparing the total sediment estimated in the USDA method with the value obtained from the EPM method, shows the ability to combine the RUSLE and GIS models to estimate the amount of soil erosion and sediment load in the area.

The land-use changes and urban development are among the fundamental topics of spatial planning. Monitoring changes in previous years and predicting these changes in the coming years have a significant role in planning and organizing urban spaces. The purpose of this study was to investigate land-use change and urban development in Ahvaz with a landscaping approach based on balanced urban development. .Images of TM (1989), ETM+ (2002), and OLI (2019) of the Landsat satellite are the basis for analyzing this trend. LCM model was used to identify the past changes, while CA-Markov chain model was applied to predict the future changes. These images were classified using a support vector machine algorithm of the object-oriented method, and the land-use maps were prepared using three sensors with four classes of vegetation, barren areas, constructed areas, and water zones. The accuracy of maps was improved separately using NDVI and SAVI indexes in the classification of the images. The efficiency of the indexes was measure by kappa coefficients and the overall accuracy of land-use maps, and then changes were investigated using maps related to the superior index. The results showed that maps related to the SAVI index were more accurate and accordingly, they were used in assessing land-use changes. The LCM model showed that in the periods 1989-2002 and 2002-2019, 2602.92 hectares and 31174.77 hectares were added to the built areas, respectively. In both periods, the most changes were about converting barren lands to built-up areas and the least changes were related to the transformation of the built-up areas to water areas. The results of the CA-Markov model until 2029 showed the continuity of the increasing trend of built-up areas, such that in ten years, 2238.82 hectares will be added to the built-up areas, and it is anticipated that the area will reach approximately 12345.63 hectares by 2029.

Rural-Urban linkages can have a tremendous impact on regional development, as it is mentioned the city as an engine of regional development. These effects can be create positive and productive role or negative and parasitic on their field or area and different from region to another region and from city to another city. It is therefore logical understanding these effects can be effective in the planning area. This research forms the main stream issue is, “Identify and determine the status of significant rural-urban linkages with regional development levels as well as explain the role germ or Parasitic of the city about it”. The research method is descriptive and analytical and based on using field data and documents. The statistical population research includes villages of 20 households to higher in Ahvaz Township and the sample size is 90 villages or about 50 percent of villages in the township. Used software is included Expert Choice and ArcGIS. To determine the level of regional development use of 120 development indicators and ElectreIII method used. Effect of town by the 11 mainstream with 40 links the village with the city measured and obtained a significant relationship among them regional development levels. Research findings showed that a total of 40 rural-urban linkage in the area, 34 cases in 9 affecting flow city, having a significant relationship and have a positive with level of regional development and the results indicate a positive and productive role in Ahvaz city on the levels of regional development.

Recognizing and explore the possibility and bottlenecks, an essential first step in the planning process is the rural areas development. In this respect, determining optimal points for the establishment of service centers and measure the degree of rural areas development is of special importance; which often done using quantitative methods. This study conducted using AHP method to select the best points for the establishment of service centers in the Gheizanieh rural district of Ahvaz township; then methods multiple attribute decision making of compensation as well as integrated collection were used to determine the degree of rural development mentioned rural district. This research in terms of nature and method of descriptive and analytical, in terms of purpose is practical researches. Data collection was conducted in two ways: completing the questionnaires of 30 expert rural affairs and general population and housing census data in the year 1390. Data analysis was conducted on the ArcGIS10.3 and software Expert Choice, Excel and Visual Promethee. The results show which between parameters selected study, population density criterion of 0.261 percent, most points allocated as well as access to infrastructure measures, access to health and care services and access to means of communication and transportation are important in later stages. Map overlap criteria, indicates that two villages, nearly four percent of the study area in a very suitable position, two percent in the suitable position, about 32 percent of the moderately suitable, about 52 percent in the range unfavorable and about 10 percent of the study area located also quite unsuitable position to establish of optimal rural service centers. Thus, the two villages Nezheh and Gheizanieh Bozorg as the most developed rural district, has the greatest potential for creating service centers at the district level were detected.

If researchers and academics, believe that the discussions of urban development and rural development be done as separated from each? Answer such questions can be found in the form of regional development strategies. Therefore, strategies and policies for regional development have an important role in boosting economic activity and the development of deprived areas followed by, reduce differences between regions. Regional allocation of public facilities and funds can be a step forward to achieve balanced development and reducing regional inequalities; otherwise, the continuation of existing trends by focusing economic development in developed areas will lead to divergence and dissonance in national development. In general, regional development is following the creation of conditions and framework conditions suitable for continuous improvement of living standards, reduce unemployment; diversify economic activity, increased investment in the private and public sectors, increased economic prosperity, as a result, social and economic sustainable development. Considering this important, economic growth only goal of the strategy of regional development, but rather, justice, poverty elimination, economic sustainability, are the objectives of the strategy. Much research has been done regarding the assessment of regional disparities in global and national level; however, with the increasing number of case studies from developing countries, are increased reports of failure of the sustainable development approach for the achieve environmental, economic and the ideal community. In rural communities, there are issues and problems, resources and facilities, needs and priorities of their own. For this reason, in the context of national development planning its necessary the village, regarded as a special and specific section. In relation to country Iran, although the managers and decision makers periodically issues have been raised, such as rural planning, rural management, a fair distribution of resources, poverty elimination and much, but seriously has been done, focus for problem solving, because despite the different organizations trustee in the affairs of village can be seen a lot of inequality in rural areas country this matter is holding back at the expense of other areas and increase the gap between regions. So to be determined weaknesses of each of the townships from the different indicators of development at the provincial level. It would be a good base determine for distribution services considered for local managers and the needs of the regions on a comparative assessment and by taking advantage of view of spatial planning was paid to the spatial development each of the townships the maximum optimal use of resources. In this context, to meet the situation township of the province was selected about 76 variables in the form of 8 indicators, using multiple attribute decision making compensation method and integrated collection have been the degree of development of the province. This study has been done in terms of goal setting as a functional study and in terms of methodology descriptive, analytical method. In order to achieve the research objectives initially classified rural development indicators nine indicator variable 76 and information about them is collected statistical yearbook 1391 of Khuzestan governor general and additional information from the department of development and planning province and then using multiple attribute decision making compensation method such as: Topsis, Electre, Vikor, Promethee was paid to determine the level township of the province, based on the rate indicators for rural development In the form of Excel software; then for achieve the one result used of integrated collection such as: Aggregate, Borda, Copeland and Post. Eventually, for spatial representation of rural development levels, combined, layer townships of province Khuzestan, with indicators weights in ArcGIS10.4.1, and layers valued and well as the formed overlapped the layers. From the integration of different sectors of development indicators with shared overlap function, 27 township of Khuzestan province were grouped into five levels. The first group is includes the townships of Izeh, Dezful and Shoosh, the second group of the townships of Baghmalek, Behbehan, Shooshtar Ahvaz, Ramhormuz and Shadegan, group three the townships of Andika, Andymeshk, Abadan, Dashte Azadegan, Karoon, Bandar Mahshahr and Bavi, group four the townships of Ramshir, Khorramshahr, Lali, Omidiyeh, Hamidieh, Gotvand and group also includes the townships of Masjed Soleiman, Hendijan, Hoveize, Haftgel and Aghajari. Spatial distinguishing between different parts of the province in force remains and most measures of development concentrated in the center, north and east provinces; so that areas benefiting includes first and second levels located mainly in the north and east provinces and deprived areas included four and five levels located in the south and west. In this study, we tried to achieve balanced development of rural areas among the township of Khuzestan province, to be determined the distribution of rural development levels between township and their position relative to each other. The geographical distribution of rural development measures, proof the existence of spatial mismatch between cities in Khuzestan province this mismatch is significant at the provincial level in terms indices studied of population issues of health, education, culture, politics, services, communications and infrastructure. Most measures of development is concentrated in northern central and western parts Khuzestan province; so were the three areas on the first level and very convenient condition, six township on the second level and convenient, seven districts in the third and moderately suitable, six districts in the fourth and inappropriate and five areas in the fifth and in very bad condition and in a sense the warning position. A closer look at the results of the study could be detected separate three areas in Khuzestan province, from other township have abandoned their and continue their rapid grow and develop, located one in the west province (Izeh) and two township in northern province (Dezful and Shoosh). In general, the township, the ranking obtained, earns high ratings and this result of having potential environmental powers as well as long term policies implemented in this field, which is caused development of these areas. Deprived areas which cover five township (Aghajari, Haftgel, Hoveize, Hendijan and Masjed Soleiman), in most criteria of the study were accounted to the lowest level of development.

1. The practice of choosing the proper location for sanitary disposal of waste is a difficult, complicated, long and expensive process. This cannot be done without using a robust and reliable system that has the ability to use and analyze multiple strata of data. GIS is very suitable because of the capacity to deal with a great quantity of data. The system has the ability to simulate and control the parameters of hydrology, hydrogeology, physiography and the environment. The purpose of this research is to find a suitable waste landfill site in Shavur district of Shoosh city using the analysis of the parameters of the drastic model through the GIS and the hierarchical analysis process. In other words, this research attempts to analyze the components that are important in locating landfill in Shavur, Shoosh, through the GIS and AHP techniques, and identifies the most suitable site for solid waste disposal, which has the least harmful environmental and human impacts, and to provide the findings in the form of the map.
2. THEORETICAL FRAMEWORK: The concept of the landfill is a useful method to choose a landfill or waste site. Locating proper sites for municipal or rural waste disposal is a complex and multidisciplinary process that requires environmental, ecological, social, economic, technical or specialized considerations. Lack of land for landfill and population growth are two greatest challenges in urban and rural areas in the world. Hence, the selection of places for landfill is the major problem facing the waste disposal management system. Given the importance of the rural community and the challenges that such community faces in its development process, recognizing the characteristics of rural development planning and addressing all aspects of it are essential. Therefore, it is necessary to pay particular attention to waste management in national programs. Over the past few years, with the help of GIS capabilities, many studies have been conducted to facilitate the process of selecting waste disposal landfills and to decrease the expense of constructing such sites, in order to keep up the process of environmental protection and to meet the objectives of sustainable regional development as well as logically managing development plans and projects. The hierarchical analysis process is flexible, strong, and simple. It is used in situations where conflicting decision-making criteria make choosing between options difficult to apply. This multi-attribute assessment approach was first proposed in 1980 by Thomas L. Saaty, and has been numerously used in regional planning. In addition, the dramatic model is based on seven hydrological parameters that include ground water static depth, net nutrient level, aquifer material, aquifer environment, soil or soil layer material, topography slope, the effect of the unsaturated environment and hydraulic conductivity of the aquifer.
3. In terms of purposing, the present study is applied, and in terms of its nature and method, it is a descriptive and analytical research. Data collection has been done via documents and surveys. To achieve the objectives of the first research, the site's talent recognition camps for waste sanitary landfill, including five issues related to the human, hydrological, communication, environmental and topographic indicators, were identified with two variables. A total of 10 were identified. These criteria were estimated when a questionnaire was completed by 30 experts, using the AHP hierarchical process analysis, and it was valued in the Excel and Expert Choice environment, and the compatibility of each of the criteria and sub-criteria was estimated. Secondly, in order to prepare a vulnerability map for groundwater due to leakage of leachate, the seven hydrological parameters of the Drastic method were used, which include the following: groundwater depth (D), net nutrient (R), aquifer type or saturated environment (A), Soil layer (S), topographic gradient (T), influence of the environment of Vados, or unsaturated medium (I) and hydraulic conductivity (C). To show the mentioned spatial parameters, the layer of Shavur section of Shoosh was combined with the weights of the criteria in the ArcGIS 10.3 environment and the UTM coordinate system in Zone 39. Interpolation, Distance, and Surface functions in the Arc Toolbox menu were used to adjust the evaluation layers so that the most suitable and most demanding sites for rural waste disposal can be extracted from the output Layers. It should also be noted that for the production of the map of each of the parameters of the drastic method, the data from the study plan of hydro climate balance excavation of the Ahoodasht district of Shoosh city (Company in charge: Water and Power Organization of Khuzestan province) were used.
4. The results of the research show that from the total area of the site, about 39.38% of it is in a very inappropriate level. In other words, these areas are not suitable for waste landfill operations. After that, perfectly appropriate levels with 20.1%, appropriate levels of about 21% and relatively appropriate with 20.4% of the area are the next respectively. What is deducted from the final map is that from the total completely appropriate areas, three sites with titles; Landfill 1 to 3 have the best places to implement the project and have a better priority than other areas.
5. The proposed sites have been identified based on many environmental characteristics such as distance from surface water and underground water, distance from biological complexes such as towns and villages, distance from agricultural areas, distance from protected areas and proximity to major roads for ease of transfer and by taking into account the landfill location criteria. The location of each of the sites is as follows: Landfill No. 1, one kilometer away from Shavur, and two kilometers from the village of Khois, Landfill No. 2, seven kilometers from Alvan and two kilometers from the village of San Karim, and Landfill No 3. It is located nine kilometers from the city of Alvan and one km from the villages of Akiush in the south, and Khalaf Aziz in the north. In the end, it should be noted that any method, while having advantages, has limitations which can be determined in subsequent research by comparing the results of this method with other methods. The more numerous and more precise criteria and indicators are, the better the results will be. As a matter of fact, this requires further research in the future.

Considering the fact that one of the main indicators to measure spatial justice in a geographic area, undoubtedly, a fair and equal distribution services. If the distribution of rural services does not commensurate with the needs of residents, will cause a lot of problems in the regional system.  Therefore, the problem of this research will form the mainstream is an “assessment of spatial justice in the distribution of public services in rural district Mosherehat of Ahvaz”.

This study from to goal is a kind of theoretical research, application and in terms of the nature and method of analysis and description. Data collection was carried out in two forms questionnaires completed by 30 expert rural affairs and population and housing census data reveals of 1390. Used software is included Expert Choice and ArcGIS10.4.1. In this study, we used the analytical hierarchy process to determine of criteria importance coefficients and from multiple attribute decision making Methods; for example, topsis, electre, vikor, promethee and integrated collection; such as, the average rank, borda, copeland and finally post, to assess spatial equity in the distribution of public services was discussed.

Reviews in this study indicate that between selected criteria in this important, sanitary and therapeutic indexes allocated the maximum amount, for example, 0/163 to, and criteria education and culture, distance from the city of Ahvaz and also agriculture index.

Respectively, on the next level are the highest value and importance with scores 0/163, 0/133, 0/124 and 0/120. That between the 20 rural points of the rural district located three villages in absolutely perfect condition, one village an appropriate condition, three villages in moderately suitable The condition, four village unsuitable conditions, and nine villages in absolutely unsuitable condition. Thus, the village of Istgahe Khosravi as the most developed village of rural the district has known the greatest potential for creating service centers in the region.

Select Ideal sites to establish service centers at the level of a village can also be a good assistant for the villagers order to quick and convenient access to these services. If the distributions of rural services do not commensurate with the needs of residents will cause a lot of problems in regional system. Therefore, the problem of this research will form the main stream is, “evaluation of suitable zones for create of rural social service centers in lami rural district of Ahvaz”. This study from to goal is a kind of theoretical research, application and in terms of the nature and method of analysis and description. Data collection was carried out in two forms questionnaires completed by 30 expert rural affairs and general population and housing census data 1390. Also were used AHP analytic hierarchy process model and the ideal point method IPM for achieving the research objectives. Data analysis was carried out by in the application media of ArcGIS10.4.1 media and Expert Choice and Excel. The results show that the parameters of study, criteria for access to services sanitary and treatment with a 0/196 percent, to be allocated most score as well as population density criteria, access to infrastructure and access to educational and cultural services are important in later stages. A map overlay criterion indicates that the village of rural district lami, daghagheleh village is the perfect situation for create of rural social service centers and rural development. From calculation of the ideal point method it can be concluded that villages of jassanieh bozorg and daghagheleh, with amounts of 0/0070, 0/0246 have the least value Si and became known as the most developed villages in the district lami. Likewise three shaeimott with amounts of 0/0977 have the highest value Si and became known as the most disadvantaged rural villages in terms of and rural facilities.

Veneered surfaces, roofs of buildings, streets and the like in urban areas as a barrier against the infiltration of rainwater into the soil and groundwater recharge.They cause more of rainfall to surface runoff and floodsto be converted. Combined method influence, storage and transmission of Atlantis, as the most urban runoff management approach, including implementation of a network of underground ducts, using Atlantis materials and execution of drainage layers on it and store water collected from the network. In this way, the possibility of penetration, transfer and storage provided and benefit levels increased urban streets as well as the transfer and accumulation of contamination is prevented. Town sajadieh located in the lower elevations of the highway and besat shahrzad and street in the south and west causes waterlogging town streets in the rain times. The present study has a descriptive, analytical approach and to investigate the role drainage plate networks, channel and ecological reservoir as the new approach in connection with control and management of surface runoff in town sajadieh Tehran.