جستجوی مقالات مرتبط با کلیدواژه "کاربری اراضی" در نشریات گروه "جغرافیا"

Floods are one of the natural phenomena that can cause significant damage to infrastructure, farmlands, and the environment. This phenomenon primarily occurs due to heavy rainfall, snowmelt, or a combination of these factors. Therefore, the aim of this study is to map flood hazard zones and examine their relationship with land use using the Analytic Network Process (ANP) model in the Razi Chay watershed in Ardabil Province.

In this study, data from Landsat 8 satellite imagery from 2022, a 30-meter ASTER DEM map, a 1:50,000 scale topographic map, a 1:250,000 scale geological map, and other detailed information of the studied watershed were utilized. Ten parameters influencing flood occurrence were analyzed, including elevation, slope, slope aspect, vegetation cover, geological formations, distance from the river, flow direction, land use, precipitation, and drainage density. The Analytic Network Process (ANP) model was employed to determine the importance of each variable.

Among the studied parameters, slope (with a weight of 30%), elevation (with a weight of 21%), and land use (with a weight of 17%) were assigned the highest weights, indicating their significant influence in controlling flood occurrence in the Razi Chay watershed. The results show that approximately 36% of the Razi Chay watershed falls within high-risk and very high-risk zones. These areas are typically located in the lower part of the watershed, often at the confluence of the two main streams. Considering the spatial distribution of settlements in the region, it can be concluded that most of the settlements in the lower part of the watershed are exposed to flood risks

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.

Soil erosion is a spatiotemporal phenomenon influenced by variable processes, necessitating multiple observations over time and space. These measurements inherently contain a level of uncertainty and are costly and time-consuming. With the advancement of spatial technologies, Geographic Information Systems (GIS), interpolation methods, and the increasing range of environmental data and remote sensing, soil erosion models play a crucial role in designing and implementing soil conservation management and strategies. The most significant empirical models for estimating annual soil erosion losses include the USLE and its modified version, RUSLE, widely used globally for soil erosion estimation. These models consider factors such as raindrop erosivity, soil erodibility, slope length and steepness, cover management, and conservation practices, with most parameters now readily obtainable through high-quality remote sensing data.

The study area, the Alashtar watershed plain, spans 80305 hectares in the northern part of Lorestan province and Selseleh county. Geomorphologically, it lies within the elevated or folded Zagros unit, characterized by thrust faulting and multiple fractures. The watershed predominantly features a mountainous landscape, with hills and mountains covering 65.39% of the area. The minimum elevation is 1500 meters, the maximum is 3600 meters, and the average elevation is 2100 meters. According to the De Martonne method, the watershed has a Mediterranean climate with an average annual rainfall of 506 millimeters.The study area's aquifer is free-flowing, with all wells situated in the alluvial aquifer. In the mountainous part of the Alashtar watershed, carbonate formations, fracture systems, and weathering in the form of snow have developed karstic aquifers, which are the source of the Kehman River. The Kehman River, after originating from the southern heights of Green and hydrating the Alashtar plain, joins the Simreh and then the Karkheh rivers. The Alashtar plain, at the center of the watershed, is a graben surrounded by the Green, Varkhash, Mahab, Sarakheh, Darikanan, and Nashate heights, with geological formations dating back to the Mesozoic and Cenozoic eras. The predominant Jurassic-Cretaceous limestone rocks cover a significant portion of the Alashtar watershed, serving as the primary recharge units (karstic water sources). The soils of Alashtar belong to the brown soil group with a clay concentration horizon, characterized by very deep, dark brown to reddish-brown soils with a heavy texture, containing 3-15% coarse gravel in the surface layers and relatively high amounts of hard limestone grains in the sublayers.The LAMPT model is basically based on the global soil erosion equation, which calculates the net rate of soil erosion. The environmental parameters of the model, including climatic data, land cover and geomorphology, were obtained from meteorological departments, natural resources and Sentinel-2 sensor satellite images during the target year (2023). To complete the data, field surveys were conducted and training data samples were also selected to prepare the land use map. The basis of LAMPT model is RUSLE model, in this model Sediment delivery ratio index (SDR) is used to show the spatial patterns of distribution and performance of pure soil sediments at the basin level. This model integrates the general characteristics of the basin landscape (land use classes, landform parameters, soil types, land cover and management) and precipitation values to simulate the gross soil erosion rate, SDR and net sediment yield at the basin level.

The findings indicate that the average annual soil loss across the watershed is 9.42 tons per hectare, which is consistent with the sediment yield measured at the Sarab-e-Seyyed Ali station (watershed outlet) with an average annual rate of 10.1 tons. The model demonstrates adequate precision in estimating soil erosion and resulting sedimentation. An assessment of soil erosion losses across different land use classes, derived from Sentinel-2 satellite images, shows that 60% of the Alashtar watershed area comprises pastures. The soil erosion rates in pastures with weak, moderate, and dense canopy cover are 17.7, 11.3, and 9.1 tons per hectare per year, respectively. Given the extent of pastures in the Alashtar watershed and the high erosion rates, particularly in those with weak canopy cover, land use planning and optimal utilization of pastures are essential to reduce soil erosion rates in this area.

Conclussion:

In this research, the LAMPT model based on climate, land cover and geomorphological data was used to estimate the annual net rate of soil erosion in the Alashtar watershed. Estimating the net rate of soil erosion during 1402 using this model showed that the average annual soil loss at the basin level is 9.42 tons per hectare per year. The classification of the soil erosion map shows that 35% of the basin has an annual soil loss of more than 10 tons. In agricultural uses, rainfed fields have the highest rate of soil erosion during the year with the amount of 7.5 tons per hectare during the year. Considering the area of pastures in the Elashtar catchment area, the high rate of soil erosion in them, especially pastures with weak canopy, planning land use and optimal use of pastures is necessary to reduce the rate of soil erosion in this basin. The evaluation of the accuracy of the LAMPT model in comparison with the annual average sedimentation rate at the sediment measuring station of Sarab Said Ali (outlet of the basin) showed that the LAMPT model has a high accuracy in estimating the soil erosion and the sediment caused by it, and its difference with the ground data is small, so the use of This model is recommended to calculate soil erosion and its annual losses. According to the findings of the research, it is suggested that the northern and northeastern sub-basins of the basin should be prioritized for protection and watershed management measures. In addition to this, pastures with weak crown cover should be given special attention in terms of land use for watershed management and pasture management.

Land use changes and land surveying are one of the main topics of sustainable development. Land use change is an important example of human influence on the environment, which causes structural changes in social, economic and physical dimensions. In order to provide rational science for regional planning decisions and sustainable development, prediction models of land use patterns can be used. Therefore, land use map is one of the requirements of any national and regional development planning. the main purpose of this study is to monitor the evolution of the land use system and predict its changes using the Markov chain. Land use changes were evaluated using land use maps obtained in 2013, 2018, and 2023 using the change analysis tool (LCM) in TerrSet software. the changes in land use during the considered years show that man-made land use has changed from 9.81% in 2013 to 11.6% in 2018 and 12.73% in 2023, which indicates the growth and development of the city. On the other hand, the use of irrigated land has increased from 2.98% in 2013 to 1.03% in 2023, which can be attributed to urban development, drought and water shortage.

In recent decades, land use and land cover changes, driven by various factors, have led to unprecedented degradation of ecosystems, particularly in peri-urban areas. The primary aim of this study is to assess land use changes with an emphasis on the peri-urban garden cities of Zanjan over the period from 1993 to 2023. This research utilizes satellite imagery from Landsat 5, 8, and 9 across the 30-year period and applies the fuzzy supervised classification method to categorize the satellite images. The results indicate that the highest growth in built-up areas occurred between 2003–2013, followed by a slowdown in recent years. Gardens initially expanded but began to decline from 2013 onward. Similarly, water resources and agricultural lands, after experiencing a period of decline, showed improvement by 2023. In contrast, rangelands exhibited a continuous downward trend. This study emphasizes the importance of ensuring the sustainability of peri-urban garden cities in Zanjan and recommends the adoption of entrepreneurial approaches to promote urban agriculture sustainability. The findings highlight that precise land use policies and management for garden cities around Zanjan can prevent irregular development and foster spatial equilibrium. In recent decades, land use and land cover changes, driven by various factors, have led to unprecedented degradation of ecosystems, particularly in peri-urban areas. The primary aim of this study is to assess land use changes with an emphasis on the peri-urban garden cities of Zanjan over the period from 1993 to 2023. This research utilizes satellite imagery from Landsat 5, 8, and 9 across the 30-year period and applies the fuzzy supervised classification method to categorize the satellite images. The results indicate that the highest growth in built-up areas occurred between 2003–2013, followed by a slowdown in recent years. Gardens initially expanded but began to decline from 2013 onward. Similarly, water resources and agricultural lands, after experiencing a period of decline, showed improvement by 2023. In contrast, rangelands exhibited a continuous downward trend. This study emphasizes the importance of ensuring the sustainability of peri-urban garden cities in Zanjan and recommends the adoption of entrepreneurial approaches to promote urban agriculture sustainability. The findings highlight that precise land use policies and management for garden cities around Zanjan can prevent irregular development and foster spatial equilibrium. In recent decades, land use and land cover changes, driven by various factors, have led to unprecedented degradation of ecosystems, particularly in peri-urban areas. The primary aim of this study is to assess land use changes with an emphasis on the peri-urban garden cities of Zanjan over the period from 1993 to 2023. This research utilizes satellite imagery from Landsat 5, 8, and 9 across the 30-year period and applies the fuzzy supervised classification method to categorize the satellite images. The results indicate that the highest growth in built-up areas occurred between 2003–2013, followed by a slowdown in recent years. Gardens initially expanded but began to decline from 2013 onward. Similarly, water resources and agricultural lands, after experiencing a period of decline, showed improvement by 2023. In contrast, rangelands exhibited a continuous downward trend. This study emphasizes the importance of ensuring the sustainability of peri-urban garden cities in Zanjan and recommends the adoption of entrepreneurial approaches to promote urban agriculture sustainability. The findings highlight that precise land use policies and management for garden cities around Zanjan can prevent irregular development and foster spatial equilibrium. In recent decades, land use and land cover changes, driven by various factors, have led to unprecedented degradation of ecosystems, particularly in peri-urban areas. The primary aim of this study is to assess land use changes with an emphasis on the peri-urban garden cities of Zanjan over the period from 1993 to 2023. This research utilizes satellite imagery from Landsat 5, 8, and 9 across the 30-year period and applies the fuzzy supervised classification method to categorize the satellite images. The results indicate that the highest growth in built-up areas occurred between 2003–2013, followed by a slowdown in recent years. Gardens initially expanded but began to decline from 2013 onward. Similarly, water resources and agricultural lands, after experiencing a period of decline, showed improvement by 2023. In contrast, rangelands exhibited a continuous downward trend. This study emphasizes the importance of ensuring the sustainability of peri-urban garden cities in Zanjan and recommends the adoption of entrepreneurial approaches to promote urban agriculture sustainability. The findings highlight that precise land use policies and management for garden cities around Zanjan can prevent irregular development and foster spatial equilibrium. In recent decades, land use and land cover changes, driven by various factors, have led to unprecedented degradation of ecosystems, particularly in peri-urban areas. The primary aim of this study is to assess land use changes with an emphasis on the peri-urban garden cities of Zanjan over the period from 1993 to 2023. This research utilizes satellite imagery from Landsat 5, 8, and 9 across the 30-year period and applies the fuzzy supervised classification method to categorize the satellite images. The results indicate that the highest growth in built-up areas occurred between 2003–2013, followed by a slowdown in recent years. Gardens initially expanded but began to decline from 2013 onward. Similarly, water resources and agricultural lands, after experiencing a period of decline, showed improvement by 2023. In contrast, rangelands exhibited a continuous downward trend. This study emphasizes the importance of ensuring the sustainability of peri-urban garden cities in Zanjan and recommends the adoption of entrepreneurial approaches to promote urban agriculture sustainability. The findings highlight that precise land use policies and management for garden cities around Zanjan can prevent irregular development and foster spatial equilibrium.

The rivers are the most important supplies of fresh and agricultural water in the cities and villages. The importance of chemical quality of waters is becoming increasingly important due to the increase and diversity of Anthropogenic activities in the urban and rural environments. Therefore, the current study aimed to investigate the trend of land use changes and the chemical quality of surface water in a period of twenty years in the Qaranquchai River in Hashtrud Ccounty. The Qaranquchai is one of the sub-basins of Qezel Ozen River in the northwest of the country. In this research, Land use maps for the years 2021 and 2001 were prepared and drawn using Sentinel 2 and Landsat 7 satellite images, and were examined their changes. The chemical quality data of surface water in the hydrometric stations of the Qaranquchai basin, including Mg, Ca, EC, TDS, Cl, HCO, SO4, K and Na were obtained from the Regional Water Organization of East Azarbaijan province from 2000 to 2020. Then, their changes over 20 years were analyzed using the Mann-Kendall test. The results of the analysis of land use changes showed that in 2001, the largest area of land use was pasture, while in 2021, rainfed land had the largest area in the Qaranquchai basin. In fact, during the studied years, with the increase of rainfed agricultural land from 38% to 53.1%, pasture land decreased from 60.17% to 42.3%. The results of the investigation of the changes of the chemical quality indicators of the water in the hydrometric stations in the Qarangochai river in the studied time period, showed that the trend of changes was increasing. The result of the increasing process of each of the anions and cations in the river water has caused its quality to decrease.

The purpose of this research is to investigate and analyze the physiographic characteristics and land cover of Koze Topraghi watershed in Ardabil province using geographic information system. In this regard, by using Landsat 9 satellite images, the topographic map of the area and the use of the digital elevation model of the land to prepare slope factors, slope direction, DEM, land use and vegetation. The results of the factors showed that the highest point of the studied area with a height of 2540 meters is located in the south of the studied area and the lowest point of the studied area with a height of about 1400 meters is located in the northern parts of the basin. In the study area, slopes of more than 70% are observed in the northeast, south, southeast elevations, and due to the lack of vegetation with low coverage, especially in the eastern parts, they are highly vulnerable to erosion. Low slope areas in the studied basin are mostly located in the central areas. The general direction of the slope in Kozetopraghi watershed is southeast and northeast. in the studied area, the slope decreases from east to west and from the heights to the center of the basin. On the other hand, in order to prepare and classify the land use map of the studied basin, the support vector machine method was used. The overall accuracy and Kappa coefficient for the land use map of the studied basin were equal to 99.93 and 0.99%, which had acceptable accuracy, in order to prepare the vegetation map for the year 1402, Landsat 9 satellite data was used and the factor map was prepared. the values of the vegetation factor in the basin ranged from -0.21 to 0.85, which often had more density in the southern parts.

Rapid physical and population development and growth in recent decades has caused many problems in cities, and Ardabil city has not been exempted from this due to its historical antiquity and high population and physical growth. This research examines and evaluates the land suitability index per capita in Ardabil city using the overlap model and spatial analysis in the geographic information system (GIS) environment. The main purpose of this study is to determine the per capita suitability of land for different urban uses and provide solutions to improve planning and sustainable urban development. For this purpose, first, spatial and descriptive data related to urban land use were collected from different sources and then processed using spatial analysis tools in GIS. The research results show that the use of this model can help identify suitable areas for future developments and optimize existing uses. The findings of this research show that there is an inequality of compatibility among some urban uses such as residential areas with more than 42%, educational use with more than 35%, administrative use with 38%, medical use with 25% and sports use with 16%. They have neighboring uses. Tourist use with more than 80%, religious and cultural use with more than 75%, and commercial use with more than 70% are in completely compatible and relatively compatible conditions with their neighboring uses and have the least incompatibility with other uses. Therefore, urban planners and designers should pay special attention to the proper distribution of neighboring uses based on spatial-spatial components, while allocating the best space to the uses needed to solve the current shortage, in the programs related to future development. This study provides practical suggestions for improving urban planning policies and land management in Ardabil, which can be used as a model for other cities.

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.

This study aimed to assess the habitat quality of the Tajan watershed in northern Iran through land use changes from 1992 to 2052 and to investigate its relationship with landscape metrics, including number of patches (NP), patch density (PD), edge density (ED), largest patch index (LPI), landscape shape index (LSI), and splitting index (SPLIT). Landsat 8 and 4 images were processed to produce land use maps for 1992, 2022, and 2052 using maximum likelihood, cross-combination, and CA-Markov methods in ENVI and TerrSet software. Habitat quality was also assessed using InVEST in three scenarios based on the land use maps. Relationships were analyzed using least squares regression and Spearman's correlation test. The results showed that from 1992 to 2052, forest and agricultural areas had the most decreasing (-82,460 hectares) and increasing (76,392 hectares) changes, respectively. Habitats in the central part of the watershed had higher quality than those in the northern and southern parts. The relationship between habitat quality and land use changes is significant and inverse (-0.95

Nowadays, deep learning as a branch of artificial intelligence acts as an alternative for human with hopeful outcomes. Open Street Map as the biggest open source data is used as a complementary data sources for spatial projects. It is notable that is some advanced counties the accuracy of VGI data is higher than governmental official data. This research aims to use artificial intelligence to produce and subsequently promote completeness of OSM data. Res_UNet architecture was utilized to train landuse categories to the network. The result shows that IoU metric is about 83 percent that implies a high accuracy paradigm. Then, united-based method was used to calculated completeness of OSM data. The unit-based results show that completeness of building blocks, forest, fruits garden and agriculture land are: 3.6, 9.7, 90.4 and 81.88 respectively. It shows the low volunteer  participation rate to produce OSM data. On the other side the high accuracy achieved by deep learning leads us to complete OSM data by artificial intelligence instead of human prepared data. The advantage of using machine rather than human may be utilized in undeveloped countries or low density population regions as well as inaccessible areas.

 the purpose of this research is to investigate the relationship between land use changes and ground surface temperature in Parsabad city in Ardabil province using Google Earth Engine system. In this regard, the land use map of Parsabad city was prepared by calling the data of Sentinel 2 and Sentinel 1 satellites in the Google Earth Engine programming environment, and in the next step, its correctness and overall accuracy were validated using the Kappa coefficient. In the next step, the data of Sentinel 5 satellite was used to investigate the aerosols of the studied city, and its daily trend was calculated using the regression and skewness method during the period of 2023-2018. In the next step, the pollution density map of the studied city was drawn and by calling MODIS satellite data, temperature anomaly map and average temperature during the time period of (2018-2023) were prepared, and the night LST trend and the night LST thermal island profile chart in the mentioned time period In the summer months (July) with an average of 297 Kelvin, and minimum values are observed in the winter months (January) with an average of 270 Kelvin. Finally, by extracting the data of city aerosol density maps with average temperature in ArcMAP software environment, the correlation between these two phenomena was analyzed by simple linear regression method. The results showed that there was an inverse relationship between these two phenomena. Also, the amount of daily aerosols has been increasing since the middle of 2021 and its negative skewness has shown the increase of pollution in the inner city areas in recent years.

Cultural centers in cities are of special importance and due to the large number of visits by citizens; they should be given the attention of urban planners. The location of cultural centers and how they are scattered in cities affect the amount of citizens' use of these centers. In recent decades, geographic information system as a computer-based technology has attracted the attention of many specialists in various fields. This technology has even been able to play an effective role in locating urban services in different parts of the country and numerous researches have been conducted for this purpose. Khorramabad city in the center of Lorestan province does not have a proper distribution of cultural centers. The purpose of this research is to investigate the current state of cultural centers in Khorramabad city in terms of locating and identifying suitable places for building new cultural centers. The research method is that first the effective factors in locating cultural centers are identified. Then, these factors are prepared in the form of information layers and weighted. Finally, suitable places for the construction of cultural centers are determined by summing up the weights of the information layers.. All the above steps have been done using Arc GIS software. The research results show that the cultural centers in Khorram Abad city are not properly distributed. By using the capabilities of geographic information technology and considering the effective factors in the location of cultural centers, it is possible to determine suitable places for the construction of new cultural centers.

Land surface temperature (LST) is an important factor in the study of global warming and climate change. Natural and man-made activities, especially land use and land cover changes, have a significant effect on land surface temperature. The purpose of this study is to estimate the surface temperature using Split window algorithm in Tabriz and determine its relationship with land use changes. For this purpose, OLI and TIRS images of Landsat 8 in 2013 and 2019 were used and after performing various pre-processing stages, vegetation index (NDVI), water extraction index (MNDWI), urban development index (NDBI) and land surface temperature were estimated using multispectral and thermal bands. Land use maps were prepared using object-oriented classification method in eCognition software and then accuracy assessment coefficients were extracted. The results of this study showed that the most land use changes are observed in rangeland use, which in the 7-year period, most of it has changed to road and urban land use. The results also show a negative correlation between NDVI and surface temperature and the highest temperature occurs in areas with poor vegetation. Therefore, considering the role of vegetation in modulating temperature conditions, the need for vegetation protection seems necessary.

In the current research, land use changes and spatial development trends of Arak metropolis and surrounding villages were evaluated and predicted. Land use in three time periods 1990 (Landsat satellite), 2006 (Ester satellite) and 2023 AD (Sentinel satellite) was prepared using support vector machine classification and the amount of changes in each land use was calculated. Then, the land use changes and spatial expansion of Arak metropolis and the surrounding villages were predicted using Markov chain-cellular automata model for the horizon of 2040 AD. The results show the high dynamics of land use changes, especially built land use, at the regional level. This is due to the large spatial development of the metropolis of Arak, which has had a profound effect on the peri-urban area. Calculations showed that during the years 1990 to 2006, the built-up area with an increase of about 4104.3 hectares has reached 8391.8 hectares. During the period from 2006 to 2023, a total of 3516.7 hectares has been added to the mentioned land use area. In this regard, a large percentage of agricultural lands in the region have been changed to built-up use. The results of the Markov chain-cellular automata model showed that until 2040, the greatest amount of spatial dynamics will be between built-agricultural uses. It is predicted that up to 2571 hectares of agricultural land in the region will be converted into built-up land by 2040. In this regard, many constructions will take place in Arak-Qom axis and Arak-Shazand axis. In the area of Pirasher, North Arak, the built-up development will be in the form of spatial development of villages and expansion of villas.In the 21st century, more than half of the world's population lives in cities, which has caused two major and interconnected "population" and "environmental" crises to occur. As a result, valuable lands outside the city have been swallowed up by buildings and their belongings (Yarahmadi, 1378: 9). Despite being aware of the adverse effects caused by the physical development of the city on the natural environment, one should also accept the fact that the phenomenon of urban development is inevitable. Although urban growth can meet a part of this need, development often happens in the suburbs, where the development of irrational land uses leads to the loss of quality natural resources and the destruction of sensitive ecosystems. In order to control and guide such developments, specifying the dimensions of the desired development, choosing the correct location of the land, and applying protection policies in line with social and economic goals, requires precise and scientific planning (Rasouli, 2011: 127). Therefore, irregular urban development has destructive effects on cities and their surrounding environment, including the heterogeneity of natural landscapes and the destruction of agricultural lands. Although scientific findings have proven that this model is not effective for urban development, it is still the dominant model of urban development (Batisani and Yarnal, 2009). In general, it should be acknowledged that what is criticized today as the negative aspects of the city and urban development is mainly not the nature of the city, but rather the unbalanced and exogenous process of the city, which is often the result of physical growth and development of cities exceeding infrastructure development. The services and services required, or the priority of scale over performance and the superiority of quantity over quality. (Pourmohammadi and Jam Kasri, 1390: 31-54). In our time, the uneven physical development of cities has created one of the most important issues in land use. This development is actually the continuation of the expansion of the city around it; Because around big cities, there are areas that always go through the period of transition from rural to urban exploitations (Shakoui, 2012: 213). In this way, the protection of rural spaces and settlements and preventing their transformation into residential spaces, villas, roads, industrial facilities, etc., along with maintaining their ecological and productive capacity, as well as the sustainable management of agricultural and garden lands, is becoming more and more difficult and changing their use. Despite the need of cities and villages for green spaces, especially around big cities, it is happening explosively and continuously. With industrialization and urbanization, the world economy is developing rapidly, but rural areas are shrinking. This issue has received serious attention in many countries (Liu and Li, 2017; Jai et al., 2021). In the process of urban-rural transformation, farmers strongly want to improve their living conditions. The occupation of agricultural lands due to new residential constructions has increased sharply, which has led to the widespread evacuation of rural residential lands (Tan and Lee, 2013). In addition, the migration of rural people to the city has intensified rural evacuation (Gay et al., 2019; Hu et al., 2016). The spatial changes of the surrounding villages have caused traditional agriculture to change from an indigenous-rural society to an urban-rural society (Liu and Wang, 2018). Behind these spatial developments, the evolution of human-land relations, industrial-agricultural relations, and urban-rural relations has caused the reorganization of rural social, economic and spatial structures (Wang et al., 2015), so that at the micro level, Many cities are gradually separated and show significant spatial differences (Gu et al., 2019). In this process, the spatial developments of the surrounding villages have also changed.

Landforms play a pivotal role in shaping ecosystems and influencing land use practices, as well as in governing flood dynamics across diverse geographical areas. Concurrently, prioritizing the study and conservation of natural systems is imperative for attaining sustainable development objectives. Therefore, the utilization of spatial data analysis and elevation models holds significant importance in assessing the characteristics of various landforms (Lin et al., 2021; Dikau, 2020). Research indicates that geological attributes profoundly influence the formation and characteristics of landforms (Nazaruddin, 2020; Kurnianto et al., 2023). This correlation stems from the intricate relationship between elevation data and geomorphological processes, making it a valuable proxy for geological formations (Dede et al., 2024). The concept of Terrain Position Index (TPI) was elucidated at the ESRI International Conference through an informative poster presentation detailing its calculation methodology (Weiss, 2001). However, delineating many landform classifications necessitates comprehensive investigations into various geological features as primary inputs (Laamrani et al., 2014; Dragut et al., 2006).

In this study, the TPI method was employed to create a map depicting the landforms of the region. The Terrain Position Index (TPI) quantifies the variation between the elevation at the central point (z0) and the mean elevation (ẑ) of the surrounding area within a designated radius (R). In the formula, (n) represents the total number of neighboring points considered during the assessment.Z ̂=1/nR 1 nR∑▒i∈R Z_i (1)TPI yields positive values when the central point is situated at a higher elevation compared to its surroundings, while negative values indicate a lower elevation. Typically, TPI outputs fall within the range of +1 to -1. Values beyond this range might suggest anomalies within the elevation dataset.Moreover, the Deviation (DEV) metric assesses the geological context of the central point (z0) by integrating TPI with the standard deviation (SD) of the elevation. The equations are as follows (Wilson J., Gallant, 2000):DEV=(z_0-Z ̂)/SD (2)SD=√(1/nR) ∑▒i=〖(Z_i-Z ̂)〗^2 (3)TPI<-focal (x,w=f,fun=function (x,…)×[5]-mean (x[-5])) (4)Positive TPI values signify elevated areas like peaks, while negative values denote low-lying regions such as valleys, and zero values represent flat terrains like plains (Wilson J., Gallant, 2000) (Figure 3). It's noteworthy that in this study, TPI maps and subsequent landform maps were prepared using scales of 10, 20, 30, 40, 50, and 60 meters.

TPI serves as a valuable tool for categorizing landforms by revealing disparities across various scales. Elevated TPI values (positive) typically denote ridges and peaks, whereas negative values indicate low-lying areas, with values nearing zero indicating flat or gently sloping terrain. Consequently, the study area's landforms were classified into 10 categories based on TPI variations across the six different scales employed in this investigation, as illustrated in Figure 8. The generated TPI outcomes underscored the significant impact of spatial resolution on landform classification, manifesting differences in the proportion of landform areas between high and low TPI values. For instance, transitioning from the finer scale of 10 meters to the broader scale of 60 meters resulted in a reduction in the proportion of U-shaped valleys from 5.64% to 2.61%, as well as a decrease in the percentage of valleys and cuts situated on uplands and slopes from 67.55% to 66.05%. Conversely, the proportion of high ridges experienced an increase from 0.81% to 2.84%, while that of mountain peaks rose from 0.11% to 0.39% (Table 4).

Valleys predominantly host bare lands, constituting the highest percentage at 92%, while agricultural lands are primarily situated in mid-range drainages and plains, covering approximately 92% of the area. Pasture lands are predominantly located in mid-slope drainages, while forest lands are observed in mid-slope drainages as well as in high and sloping areas.Urban areas exhibit the highest proportion in mid-slope drainages and slopes, whereas garden lands are most prevalent in drains, valleys, and sloping terrains. This diversity underscores the distribution of various land uses such as agriculture, natural resources, wildlife habitats, urban areas, road networks, pastures, protected areas, agroforestry, and ecotourism across distinct landform features. It's worth noting that the analysis of land use and land shape considered a neighborhood radius of 10 meters.Regarding flood susceptibility, low flood risk classes are predominantly associated with high lands (high ridges), while medium flood risk occurs in mid-range drainages, and high flood risk is prevalent in numerous landforms including drains, valleys, and sloping terrains. Mid-range drainages are particularly susceptible to flooding. As indicated in Table 3, the highest classes of flood hazard risks are correlated with plains, while the lowest risk classes are attributed to peaks with medium and high slopes and upstream drainages. Areas characterized by high slopes and peaks generally exhibit low flood risk, while those with mid-slope drainages and sloping lands fall within the moderate risk category, and valleys pose a relatively higher flood risk. This model offers insights into flood risk assessment and facilitates sustainable management strategies for the region.

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.

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.

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.

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.