جستجوی مقالات مرتبط با کلیدواژه « land use » در نشریات گروه « جغرافیا »

By employing urban growth and development modeling, it is feasible to delineate a developmental trajectory that aligns with the specific circumstances of a city, considering environmental factors, natural elements, and population dynamics. The aim of this research is to propose an urban development model for Shushtar, which can serve as a valuable tool for analyzing the intricate processes of urban transformations. To accomplish this objective, two datasets were utilized: urban land use maps (including educational spaces, healthcare facilities, residential areas, etc.) and Landsat satellite imagery for key land uses such as rivers, barren lands, and forests, spanning three time periods: 1991, 2004, and 2014. These datasets were processed using GIS and MATLAB software. Existing urban land use maps were digitized and subsequently updated using Landsat satellite imagery. Subsequently, influential parameters in urban development were introduced as inputs to the Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm. After training the model for the years 1991 and 2004, the predicted results of urban development using the algorithm were compared with the actual situation in 2014, demonstrating a high accuracy of 93.7%. The land use change map, resulting from the change detection process, can be generated based on multi-temporal remote sensing images and their integration with urban land use maps, enabling an analysis of the associated consequences. The use of intelligent algorithms in this research has facilitated modeling with a high level of accuracy. The obtained results are deemed acceptable, and this development has also been predicted for the upcoming years.

Rivers besides the positive effects of the rivers in the areas, there are also risks that, if not paid attention to them, can cause a lot of damage. Accordingly, in this research, the geometric status of the river studied and the proper use of the marginal areas of the river are determined based on the morphology of the region. In this research, the aerial photographs of 1360 and satellite imagery of 1397 have been used to investigate river changes. In accordance with the objectives, using ARCGIS and Auto Cat software, the first step was to investigate the morphological status of the river and then using the fuzzy logic and AHP combination model to zoning the areas suitable for the development of residential, agricultural and green spaces. The results of the survey of the morphology of the river indicate that the second period is closer to the first period than the Meander River, and the river in general has tended towards the Meander over time. Also, the study of the displacement rate indicates that the first open with 32.66 km long has an average of 33.3 meters, and the second interval with 27.17 km long has an average of 17.2 meters displacement. In addition, the results of zoning of the marginal areas of the river indicate the proportion of the western margin of the river for the use of residential, agricultural lands and green spaces.

 Urban land use patterns undergo fundamental changes over time, and in creating these changes,the role of humans and their activities is the most important. Therefore,modeling and predicting land use changes in the future,considering their changes in the past,will greatly help city managers and planners in making better decisions to guide the future development of the city.In line with the mentioned cases,the purpose of the present research will help to reveal the changes and modeling the development of Kerman city. To achieve this goal, the images of TM, ETM+ and OLI sensors of Landsat satellite were used for the years 2010 to 2020,respectively,in order to prepare land use maps of the studied area. In addition, the parameters used in this research included distance from highways and roads,distance from higher education centers and distance from military centers.In the pre-processing stage, after applying geometric, radiometric and atmospheric corrections,image highlighting operations are performed and using the supervised classification method with the maximum likelihood algorithm,in three classes of built land, barren land and vegetation of land use maps.were prepared In the second stage, the changes made in terms of area, trend and spatial distribution were investigated and analyzed. In the next stage, based on these changes and three independent variables, the modeling of the potential of multi-layered use conversion was done. This method can be used to predict future changes.

The research method is descriptive-Analytical, the research data is prepared by documentation and field methods and references to organizations. The types of users were examined at the Kerman city level and the ratio of each was obtained.

The forecast results of 1405 show the fact that if the current trend of changes continues until 1405,the area will increase by 1357 hectares compared to the current situation, and the area of ​​barren land and vegetation will decrease by 1077 and 472 hectares. The results of this study can help urban planners and managers to better understand the current conditions and make appropriate decisions in the future for proper land cover management.

Land use and land cover change includes the conversion of natural land cover into impermeable surfaces as a product of the rapid growth of urban and rural areas. One of the topics that has attracted the attention of researchers in recent years is the impacts of these changes on the temperature of the earth's surface as a vital parameter for the environment and human life. In this study, the relationship between the changes in land cover and the temperature of the earth's surface has been investigated using Madis sensor satellite images, focusing on Mazandaran province. In order to analyze the data, Moran's index and hot spot analysis have been used from 2012 to 2022. The findings showed that following the changes of the land cover in the studied area, the surface temperature of the province has increased by 1.46 degrees during the studied decade. Also, during the same period, the night temperature of the province has increased by 1.02 degrees Celsius and its daily temperature has increased by 1.89 degrees Celsius. Also, more than 98% of the urban lands, which are considered as the hottest parts of the province, are located in hot clusters. The results of this study can play an important role in better planning the regional development of Mazandaran province and create healthier residential environments and provide very useful information to help manage and plan the development of residential land in order to achieve environmental sustainability.The results of this study can play an important role in better planning the regional development of Mazandaran province and create healthier residential environments and provide very useful information to help manage and plan the development of residential land in order to achieve environmental sustainability.

Earth surface temperature provides important information on the role of land use and land cover on energy balance processes. Therefore, the purpose of this research is to evaluate the LST patterns due to changes in land use (LULC). The studied area is located in Talesh region with an area of 300.6 square kilometers. For this purpose, Landsat images were downloaded in dry and wet seasons from 1365 to 1401. Four user classes were identified by maximum likelihood classification (MLC) and support vector machine (SVM) in 36-year intervals. The Kappa coefficient values for the SVM model were equal to 0.7802 and for the MLC model it was equal to 0.5328. NDVI, NDSI, and NDWI spectral indices were calculated for vegetation, barren soil, and water and were compared with LST in the above years. Changes in land use during the years 1365 to 1401 were an important factor in changes in the temperature of the earth's surface, which averaged from 13.7 degrees Celsius to 39.5 degrees Celsius in the wet season and -0.37 to 41.07 degrees Celsius in the dry season has been variable. Water areas and vegetation have the lowest and barren soil have the highest LST values. The highest negative correlation of -0.74 belongs to the NDVI index in 1365 and the highest positive correlation of 0.79 belongs to the NDSI index in 1365. The area of the forest area has decreased by 20.3% and agricultural land has increased by 217% in 36 years. Barren lands have changed the most and decreased from 2.68 square kilometers to 12 square kilometers. In general, LST has increased due to the increase of human activities such as the expansion of agricultural land and deforestation in the studied period.

Implementation of land reforms in Iran has brought about significant social and geographical changes in rural villages across the country. These changes have predominantly disrupted the existing social structures in these rural areas. While several studies have been conducted on this subject, few have explored the local perspective and the context-specific nature of these social structures. Hence, this study aimed to investigate the effects of land reforms on the social structure of Qaleh Shian Village in Kermanshah Province. The research adopted a qualitative paradigm and employed a descriptive-exploratory methodology. The study population comprised individuals, who possessed a deep understanding of the village and had resided there for over 50 years, with their lands being subject to land reform laws. These individuals were selected through purposive sampling and data were collected through individual and semi-structured in-depth interviews. Content analysis was conducted for data analysis. The research findings revealed that prior to land reforms, the social structure of Qaleh Shian Village had encompassed a ruling class (consisting of landlords, sharecroppers, and overseers), independents (including landowners, independent farmers, and settlers), and followers (comprising tenant farmers, sharecroppers, day laborers, and migrants). However, after the implementation of land reforms, this classification had undergone changes, resulting in a social structure characterized by landowners (comprising large and small landowners, as well as water rights holders), followers (including agricultural laborers and settlers), and educated individuals (comprising educators, teachers, physicians, and supporters). Furthermore, the results indicated that although land reforms had mitigated social inequalities to some extent and partially fulfilled people's expectations, landlords, sharecroppers, and overseers continued to wield social status and power within the community. Based on these research findings, it is recommended that planners and policymakers give due consideration to the geographical factor in social structuring during land reforms.

In recent years, global population growth and urban expansion have led to significant land use and cover changes. These changes have numerous detrimental consequences, such as increasing surface temperatures, deforestation, desertification, degradation of ecosystem services, biodiversity loss, and threats to food security. Therefore, monitoring and modeling these changes are essential for optimal land management and sustainable utilization of natural resources. Given that the Aras River Basin has undergone significant transformations over time, particularly in built-up land developments, this research focuses on modeling land use/land cover changes in this area.                  

Initially, land use maps for the region were extracted for the years 2000 and 2020 from the Globeland30 project of the China National Geomatics Center. Subsequently, two maps were prepared to illustrate the potential growth of built-up land based on a land development scenario. This was achieved using advanced decision-making analysis methods based on GIS, including BWM and MEREC. Finally, these two maps, along with the land use maps, were combined to form the input for the CA-Markov model. The modeling process was carried out twice: once using the BWM + CA-Markov combination, and again using the CA-Markov + MEREC combination for the year 2040. 

The examination of the results demonstrated that in the output of the combined BWM + CA-Markov model, the extent of built-up land increased from 603 square kilometers in 2020 to over 930 square kilometers in 2040. Meanwhile, this figure was approximately 829 square kilometers in the output of the MEREC + CA-Markov model. Furthermore, the final results obtained from the intersection of these combined models also indicated an increase in the extent of this land from 603 square kilometers in 2020 to 930 square kilometers in 2040.

The continuous growth of built-up land in this basin can lead to the destruction of environmental resources and pose threats to ecosystems. The findings of this study provide relevant managers with valuable insights for optimal management of future conditions and the provision of necessary infrastructure.

In the era of climate change, ensuring food security through the utilization of agricultural lands in and around cities is paramount. These lands are threatened by urban expansion, and their preservation requires the support of urban planners. This research examines the issue of repurposing urban agricultural land for other urban uses from a social practice perspective rather than a physical or legal one. The article explores why and how changes in agricultural land use occur and the potential for intervention, guidance, and management of this process from a social practice standpoint. The case study focuses on agricultural lands in the west of Tabriz city over more than 50 years, from the approval of the first urban plan to the present. The study employs historical reconstruction for analysis. “Sayings” are analyzed using texts from urban development plans, while “doings” are derived from maps of the current situation from different years and interviews with long-time neighborhood residents. The findings indicate that changes in the three sources of meanings, materials, and competence have altered social practices in different periods during this period. If this continues, it could lead to changes in land use methods. Also, multiple meanings and corresponding materials and competence coexisted during each period, weakening or strengthening the dominant social practice. Throughout the period, the differing perspectives of urban management, landowners, and citizens have influenced the process of social practice.

Knowledge of wildfire-prone areas is useful for identifying future challenges and formulating management strategies, therefore, monitoring and studying the behavior of this phenomenon can be effective in this regard. In this study, the areas affected by wildfires in Kermanshah province were obtained using the information related to the active fire of MODIS satellite during the years 2001 to 2022. Then, using the kernel density function, the density of fire occurrences for each year was calculated and the wildfire data was prepared in the form of density per square kilometer. Different density maps were entered into the non-parametric Mann-Kendall analysis in the form of a time series to calculate the trend of changes at a significance level of 95% or more (99%) with this method. According to the results, during the past 21 years, an area equal to 3613.31 square kilometers of the province's land has experienced an increase in the density of fires, and this amount is equal to 644.39 square kilometers for the decreasing trend. None of the protected areas of Kermanshah Province have a decreasing trend of wildfire density; however, areas from the north and northwest, west and east of the study area have an increasing trend of wildfire density. Most of the areas with an increasing trend of wildfires are located in high areas with high rainfall and are covered by Zagros forests. Among the protected areas, Shahu and Kohsalan as well as Buzin and Markhil have the most fluctuations and changes in wildfires density. The fact that a large part of these areas is covered by oak forests, drought, temperature increase, and the spread of intentional fires may be among the effective and important factors in this phenomenon. The fact that a large part of these areas is covered by oak forests may be among the effective and important factors in this phenomenon

Land is a vital natural resource for human survival and the basis of all ecosystem services. However, land degradation through land use and land cover changes has become a serious global issue. Rural-urban migration in developing countries, along with the conversion of nearby villages into urban areas, has largely driven the rapid increase in urban settlements. Evidence shows that northern Iran has been experiencing rapid land use changes, which have endangered the region's stability over the last three decades. This article aims to identify and compare the growth and expansion changes of Amol city, located in Mazandaran province, over three decades from 1986 to 2016. Urban growth is defined by the absolute increase in the population living in cities, while urban sprawl is defined by changes in land cover over time.

To produce images of land cover changes in different years, Landsat time series image data (TM, ETM+, and OLI/TIRS sensors) were used. A linear unmixing model based on the extraction of end members was employed, identifying two classes of land: urban and non-urban. To verify the classification accuracy, high-resolution images from Google Earth and field observations using GPS were employed. Moran's spatial autocorrelation analysis tool was used to analyze the spatial distribution of land cover, and the trend analysis tool in ArcGIS software was employed to analyze the trend of spatial changes in urban land.

The findings show that the city's population doubling over these three decades has not only been accompanied by a 60% horizontal expansion into surrounding green and open lands but also increased building density and the number of floors. Validation of land cover classification, using the ambiguity error matrix, with an overall accuracy of over 90% and a kappa coefficient of over 80% for the obtained images, indicates high accuracy. Based on Moran's spatial autocorrelation analysis, the development of Amol City follows a cluster structure. Calculating the difference in land cover data over the 20 years from 1996 to 2016 revealed that 28 percent of the total city area, equivalent to 890 hectares, has undergone significant changes, including fundamental alterations in land use and land cover. The expansion of Amol City has generally occurred from the center to the periphery, with the least changes in the central parts and the most changes in the northern and eastern parts of the city.

Population growth and urban expansion not only lead to the destruction of natural resources and the environment but also exacerbate urban management problems in providing infrastructure and services. Therefore, the goal of planning should be to achieve optimal development that prevents increased migration from villages to cities. This can be achieved both at the macro level, by distributing urban roles complementarily and strengthening the role of villages, and at the local level, by emphasizing the balanced distribution of the city's population and endogenous growth.

The rapid growth of the urban population and its increasing concentration in metropolitan areas is one of the most obvious developments in the settlements of contemporary Iran. Spatio-temporal population movements have led to complex changes in land cover patterns. This article aims to investigate and analyze the spatial-temporal changes in the urban population and the resulting land cover patterns in the last few decades in the metropolitan area of Isfahan. The research method in this research is descriptive-analytical, and by using the analysis of census data and statistics of urban blocks, as well as the method of classification of Landsat satellite images, it has been done. The findings of the research show that during recent decades, the absolute increase of the urban population has reached the area of 35 km to the area of 25 km of Isfahan city. The results show that the spatial-temporal movement of the urban population in the Isfahan metropolitan area is in the stage of centralization and extensive development. According to the spatio-temporal movement of the urban population, the land cover pattern has also undergone extensive changes. The most important pattern of urban growth resulting from demographic changes in the metropolitan area of Isfahan indicates that the semi-centralized pattern of this region in the 1981s turned into a centralized pattern and was pushed in the 2011s.

Ecosystem services (ES) refer to the benefits derived from the structure and function of ecosystems and play an important role in human well-being and welfare (Adelisardou et al., 2021). The two interconnected approaches of carbon sequestration and habitat provisioning are ecosystem services that have the potential to mitigate climate change and biodiversity loss caused by the built environment (Varshney et al., 2022). The rapid urbanization of Tehran in recent decades has led to significant disruptions to both the natural and urban landscape. Sustainable population growth, industrialization, and urbanization processes have led to the reduction or destruction of natural vegetation, the development of urban constructions, various human activities (such as transportation and production centres), and drastic changes in land cover/land use (LULC). These factors have also contributed to an increase in energy consumption, which has resulted in elevated surface temperatures in urban environments. Under these conditions, the current research aims to examine two ecosystem services - regulatory services (carbon storage) and support services (habitat quality) - provided by the InVEST model. The research will focus on the role and impact of these two crucial services in enhancing the quality of the environment and analyzing the climate of the Tehran metropolis.

The current research aims to investigate the effect of land use/land cover on changes in carbon storage (regulating service) and habitat quality (supporting service) at spatial and regional scales using the InVEST software. The carbon storage model integrates land use and land cover (LULC) data with information on carbon storage inventories in four main carbon storage pools: aboveground biomass, belowground biomass, deadwood, and soil organic carbon. This integration enables calculations and spatial distribution of inventories and carbon storage in the area. To conduct habitat quality modelling, several components are necessary, including the (LULC) map, threat sources, impact weight tables, impact distance for each threat, and the sensitivity of each habitat to the threat source. One of the important inputs of the InVEST model is the land use/land cover map. In the present study, the classification of local climate zones (LCZ) was utilized to calculate and generate a land use and land cover (LULC) map for the city and suburbs of Tehran.

The results showed that the highest amount of carbon storage on an annual scale is associated with aboveground biomass and soil organic carbon, while the lowest amounts are found in deadwood and belowground biomass. The aboveground biomass in region 22, specifically the Chitgar Forest Park area and the northeastern areas of the region where trees are densely and sparsely distributed, has the highest carbon storage capacity. It is estimated to be between 218 and 335 tons per hectare per year. After that, the southern and southeastern parts of region 15, as well as the northern and eastern parts of regions 8 and 14, which are characterized by open mid-rise land cover, are ranked next in terms of carbon storage. The results of the Habitat Quality Index also showed that the highest amount of habitat quality, indicated by a 16% coverage (values between 0.7 and 1), was concentrated in the northern parts of the study area. The habitat quality gradually decreased towards the southern and, in particular, the southwestern areas. In 65% of the study area, the habitat quality is extremely low, primarily due to urban development and settlements in the southwest of the city. The central (10, 11, and 12) and western (21 and 22) areas of the municipality have the lowest habitat quality due to the lack of urban green spaces, the destruction of existing ones, and the expansion of settlements and industrial complexes. Finally, to measure the sensitivity of ecosystem services to climate, we analyzed the effect of two primary climate components: temperature and precipitation, on ecosystem services. The results showed that although the correlation coefficients between the studied series were relatively low (temperature and ES=0.221, precipitation and ES=0.234), the regression analysis indicates that both ecosystem services will decrease under conditions of increasing temperature and decreasing precipitation.

In this study, we evaluated the spatial changes of two carbon storage services and habitat quality concerning land use/land cover change in the Tehran metropolis and its surrounding suburbs. The results showed that the land is covered with dense and scattered trees, as well as open mid-rise, sparsely built, open low-rise, and low plants. These areas had the highest absorption values in all four carbon pools. In this sense, Region 22 and the eastern part of the Northern Region had the best conditions for carbon absorption. The output of InVEST habitat quality also indicated that the highest amount of habitat quality, with a coverage of 16% (values between 0.7 and 1), is found in the northern parts of the basin. Gradually, the quality of the habitat decreases towards the southern areas, especially in the southwest. Although the obtained results indicate the favourable ecological potential of some areas in the metropolis of Tehran, climate change and human activities have severely affected this potential. Based on the linear relationship between the normalized series of climatic components (temperature and precipitation) and ES, there was an inverse relationship between temperature and ES and a direct relationship between precipitation and ES. As a result, both regulatory services and ecosystem support will decrease under conditions of increasing temperature and decreasing precipitation.

In this study, the effects of land use changes with surface temperature of karaj cityand spatial autocorrelation have been discussed using the moran index. for this purpose, landsat OLI- TM satellite imagery has been used in 2000 and 2018. first, the images were taken and the required images were applied. then classification using object orinted method and nearest neighbor algorithm was developed and the earth surface temperature was extracted with split window algorithm (imagery). The results showed that the arid land has the highest temperature in 2000 and 2018, respectively, due to the lack of vegetation, the high capacity of absorption of heat by barren soil, and the use of blue zones in 2000 and 2018 respectively, has a temperature of 38 - 25 (° C), which is دفع and has lower heat temperatures. also, the results showed strong relationship between land use and temperature. finally, the hot and cold clusters of karaj city heat islands were extracted using the hot spots analysis index (hotspot). Space autocorrelation analysis with global Moran's indices showed that the Earth's surface temperature was cluster - like. the analysis of hot spots confirmed the focus and cluster of the heat islands of karaj city in space with increasing periods of time.

This study was conducted with the aim of analyzing the distribution pattern of land uses in the district 3 of Ahvaz. Land uses were evaluated at the regional, district and neighborhood levels by calculating indices of Compactness, Herfindahl-Hirschman, Fragmentation, Simpson’s Diversity, Entropy, Built-up Land Density, and analytical tools available in ArcGIS software, including ANN, DD and GWR analyzes. Therefore, this research was done with a practical purpose and a descriptive method, and the data was collected by a library method. It should be mentioned that so far a few articles have been written on the evaluation of the pattern of land use distribution by these methods and also on the case of the district 3 of Ahvaz. The study showed that in the district 3 of Ahvaz city, the existing per capita land uses wer 12 m2 higher than the standard per capita. Zone 2 had the highest density and compactness and zone 3 had the highest dispersion. Despite this, the pattern of distribution of land uses in the zone 3 showed more mixture, diversity, concentration and continuity. Spatial distribution of 46% of land uses was highly clustered and the land use direction towards the center of the district was favorable. This orientation attracted the population in the center of the district. As a result, Land uses in three Ahvaz regions do not have proper distribution and it is necessary to prepare a plan to organize land use.

The study aimed to explore land use changes and their relationship with the surface temperature using Landsat satellite images from 1990 to 2019. For this purpose, the urban land uses were classified and analyzed using 50 land sample positions from the visible composition of the Landsat  images using the supervised classification algorithm in the GIS. The results showed that urban lands had undergone significant changes. The surface temperature of the different uses using the glow temperature algorithm showed that free lands at 33.5°C had the highest temperature, while the lowest average temperature at 25.4°C was for the use of gardens. In terms of temperature variability, the gardens at 7.5°C had the most variable average temperature, while the water agricultural zone at 2.1°C had the lowest level of temperature standard deviation. The results of correlation analysis between temperature difference and land use change showed that the correlation coefficient between temperature changes and urban areas was 0.86 and 0.82 in the irrigated agricultural zone. Regarding the use of gardens, waste lands, and marsh areas, the correlation between periodic land use changes and temperature changes was more than 0.8, which is significant at the reliability of 0.95. But at the level of rangelands, rain fed agriculture and water zone, the correlation or significant connection were not observed at the level of confidence.

Soil erosion is the most common type of land degradation occurring in arid and semi-arid areas, as well as in flooded areas, due to natural and human processes. Erosive factors lead to the loss of land fertility, transforming damaged areas into abandoned lands and disrupting the balance of natural ecosystems. Soil erosion, as an important environmental issue, poses a threat to the sustainability of natural resources and soil productivity, turning it into a major problem in many parts of the world. To address this challenge, evaluating soil erodibility and preparing a risk zoning map is one of the most important preventive measures. One of the methods for estimating soil erosion is the SLEMSA model, which utilizes basic environmental information to assess the amount of soil loss. Consequently, the present research aims to determine soil loss values and create zoning maps for high erosion areas using the SLEMSA model and remote sensing data. The results obtained from this study can assist organizational managers and executive departments in formulating effective plans to control soil erosion and contribute to the achievement of the country's sustainable development goals.

The SLEMSA model divides the soil erosion environment into four physical systems: crops, climate, soil, and topography. These control variables are then integrated into three sub-models: the soil erodibility sub-model, topography sub-model, and vegetation sub-model. In this study, the topographic factor map is generated using two parameters: slope and domain length. These parameters are derived from the Digital Elevation Model (DEM), obtained from the SRTM Digital Elevation Data version 4 of the Google Earth Engine system, with a spatial resolution of 90 meters. To create the soil erodibility map, rain kinetic energy maps and soil erodibility factors are required. The Google Earth Engine System’s Global Precipitation Measured (GPM) v6 data was used to extract rain kinetic energy. Simultaneously, the soil erodibility factor was obtained from a geological formations map acquired from the World Soil Database (HWSD) for the year 2022. Additionally, a vegetation factor map was generated using ESA-CCI global land use data.

The topographic factor map was created using slope and domain length maps. Based on this factor's map, it is evident that the highest values are in the high mountain areas of the basin. The soil erodibility factor map is prepared based on soil erodibility and rain kinetic energy. The results of the soil erosion factor map for this basin show that erosion is more evident in areas with weak and unstable formations mainly affected by the kinetic energy of rainfall. The vegetation factor map was prepared using released energy maps and land use maps. Considering the direct relationship between the vegetation factor and erosion, it can be concluded that the highest soil losses occur in areas with a higher vegetation factor. Consequently, the combination of topographical factors, erodibility, and vegetation indicates the amount of soil erosion in terms of tons per hectare per year. The research findings indicate that the marginal areas from the northeast to the southeast of the basin, in the altitude range of 1880 to 3622 meters, lack suitable vegetation due to the high altitude and slope. Also, due to the high amount of precipitation in these areas, an increase follows the speed of surface runoff. Additionally, sensitive formations in these areas contribute to intensifying soil erosion. Approximately 11.7% of the basin area is in the erosion risk group, with the erosion rate ranging from 37.1 to 67.7 tons per hectare per year. Planning, management, and control measures are needed to address soil erosion and protection in these high-risk areas.

The results of this research indicate that approximately 96.61% of the region has a low to moderate erodibility rate. Meanwhile, the lowest erosion values are observed in the middle and outlet areas of the basin, characterized by lower altitudes and better vegetation conditions. These areas are more favorable in terms of sensitivity to erosion, and the presence of annual rainfall between 460 and 600 mm leads to a decrease in runoff, consequently reducing the rate of erosion. On the other hand, the highest amount of erosion can be seen in the Doab and Kakareza watersheds, attributed to inappropriate vegetation, annual rainfall exceeding 600 mm, and structures with low resistance. Finally, it can be said that in Iran, especially in Lorestan province, the lack of models to estimate erosion with limited data has become a significant challenge. Therefore, the purpose of this research was to investigate soil erosion in the Karkheh watershed of Lorestan province using the SLEMSA model. Utilizing simple environmental data, this model shows promising potential for estimating soil erodibility in the Karkheh watershed of Lorestan province.

Desertification in arid and semi-arid areas is an invisible and very dangerous phenomenon, and if it continues, it leads to the destruction of the land and the loss of renewable natural resources. Several factors play an effective role in the occurrence of desertification in a region, among which the phenomenon of land subsidence can be mentioned. Land subsidence is a geological process that occurs in a long-term balance and coordination between human activities and the hydrogeological environment. Today, land subsidence caused by the extraction of underground water has become a global problem, and it can even be the site of other hazards and threaten the society. The challenge of establishing a balance between groundwater consumption and land subsidence control is essential for sustainable development and curbing desertification. In order to meet their needs, including agriculture, industry and drinking, human societies depend on underground water sources and provide the required water through underground water. These conditions have become more severe in Iran due to its location in the arid and semi-arid belt, along with the improper distribution of rainfall with excessive extraction of underground water. In Iran, this phenomenon has extensive ecological, economic, social and environmental consequences due to the multiplicity, extent and complexity of the environmental and human factors that cause desertification. Hence, the precise monitoring and analysis of the intensity of desertification is of great importance for risk assessment and risk assessment. Therefore, it is necessary to know the criteria and indicators effective in the occurrence of desertification in order to achieve a model that can monitor the intensity of desertification in order to manage and plan the desert areas correctly and on principles. For this purpose, the aim of this research is to evaluate the state of desertification by IMDPA model based on two criteria of underground water and subsidence in the Rafsanjan watershed located in the northwest of Kerman province.

In this research, two criteria of underground water and subsidence rate were used as key criteria to prepare the desertification intensity map. According to the available information and the goals of this research, the criteria of underground water were scored based on electrical conductivity indicators, sodium absorption ratio, and groundwater level drop. For the subsidence criterion, the subsidence rate index was used in the year 2014-2015. In the next stage, a weight between 1 and 4 was given to each index based on its effect on desertification. The weighting is linear and equal in proportion; So that value 1 is the best and value 4 is the worst weight. Zoning of the mentioned indicators was also done by geographic information system and interpolation methods. The subsidence criterion was evaluated using the subsidence map prepared from Sentinel 1 satellite images in the year 2014-2015. In the end, the final map of the desertification situation was obtained according to the IMDPA model and based on the geometric mean of the criteria.

The average electrical conductivity measure in Rafsanjan watershed was 9351.4, which with a score of 4, is in a very severe desertification situation. Also, in terms of absorbable sodium, this watershed with an average of 12.28 and a score of 1, put it in a state of low desertification. In addition, according to the results of the groundwater quantity criterion based on the average level drop for the aquifer located in the Rafsanjan watershed, it was determined that the average drop of groundwater is about 54 cm with a score of 4, and is in a severe state of desertification. The subsidence of the aquifer located in the Rafsanjan watershed has varied from seven to less than one centimeter per year. Also, based on the average values, the average subsidence in the water year 1394-1395 in the region was in the low category with an average of -1.25 and a score of 1. Examining the areas with subsidence and the level of the drop in the underground water level showed that the drop in the underground water level can be considered as the main reason for the subsidence in the Rafsanjan aquifer. The overlap of three indicators of groundwater criteria, including: electrical conductivity, sodium absorption ratio and level drop, showed that 2.74, 59.07, 37.15 and 1.02 percent of Rafsanjan watershed are in low, medium, severe and There is a lot of desertification. Also, the overlap of the underground water and land subsidence criteria showed that the intensity of desertification is placed in three levels: low, moderate and severe, and the highest level corresponds to the moderate severity.

Rafsanjan watershed is one of the critical areas of subsidence. For this purpose, it is very important to evaluate land degradation caused by subsidence and drop in the underground water level in the Rafsanjan watershed. The results of this research confirm that according to the underground water criteria, the average electrical conductivity, absorbable sodium, and the drop in the water level of the region are in very severe, low, and severe desertification. In addition, in terms of the intensity of desertification from the point of view of water quality, the region is located in low, medium, severe and very severe classes. Finally, the intensity of desertification according to the two investigated criteria (underground water and subsidence) is placed in three levels: low, medium and severe, and the highest level is related to moderate severity. The results of this research will create a clear horizon for managers and planners of the natural resources sector, which will lead to a precise understanding of the criteria and indicators effective in the occurrence of desertification in the region. In addition, it is suggested to identify other effective factors in the region and introduce them to the desired model for accurate estimation of this phenomenon.

Tehran is one of the most polluted cities in the world. The air pollution is caused by different factors such as centralization, increased traffic and incorrect location of the spatial pattern, consumption of fossil fuels, lack of rules and regulations for limiting industrial areas and nonobservance to the environmental guidelines. Sometimes, these factors are intensified because of the climatic factors. The aim of this study is to identify the relationships between the residential urban factors and Tehran's air pollution and to determine the extent of their importance. The intended techniques found through radar data showed that the physical pattern and the consequences of the urban planning system are considered some of the effective structures in increasing the air pollution in Tehran. Hence, the correlation coefficient between the height environment of urban buildings and constructions (the third dimension of the city) and Tehran's air pollution was calculated to be 0.86. In other words, in the case of proper planning or with the possibility of modifying the structure of the height environment in city up to 86%, it is possible to adjust and control the air pollution. The results were in line with the spatial pattern of PM2.5 particles and carbon monoxide regarding urban land use, industries, commercial centers, transportation, organizations and health centers and had the highest coefficient of determination with the spatial pattern of Tehran' air pollution. Considering the traffic, the index had the highest correlation with the spatial pattern of PM2.5 particles. Meanwhile, in the dangerous and unhealthy parts of the spatial pattern, a large number of nodal points with little distances formed traffic channels. Thus, by identifying these channels and managing urban traffic, the air pollution can be controlled to a larger extent. It should be mentioned that because of the impossibility of decreasing or eliminating driving forces in the creation or intensification of the air pollution, the residential environment of Tehran can be directed toward an appropriate environmental pattern by changing or maintaining the structures and functions through a change in the patterns of macro-urban management and the urban planning models consistent with the human functions and spatial pattern.