جستجوی مقالات مرتبط با کلیدواژه « کاربری اراضی » 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.

 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 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.

The purpose of this research is to evaluate the amount of soil loss in the land uses of the Nirchai watershed using the RUSLE model in Ardabil province. In order to carry out this research, first, the satellite image of the studied area related to the year 1400 and the month of June was received from the American Geological Research Center, and after atmospheric and radiometric corrections, a land use map was prepared using the supervised classification method using the support vector machine method. Then the RUSLE model was used to estimate the erosion rate. SPSS 21, Excel, ArcGIS 5.4, Archydro and ENVI 5.3 software were used to analyze and produce maps in this research. RUSLE model parameter layer includes rain erosion layer, soil layer, topography layer, vegetation layer and soil protection factor as well as various statistics related to rain gauge stations, hydrometry, topographic maps 1:50000, geology 1:100000 as well as DEM (20 meters area) and GIS geographic information system and remote sensing have been used. The results of this study showed that the average amount of annual soil erosion for the whole basin ranges from 0.5 to 14.25 tons per hectare per year. Also, the investigation of the regression relationships between the factors of RUSLE model and the amount of annual soil erosion showed that the topography factor (LS) with the highest value of the coefficient of determination R^2=0.93 is the most important in estimating the annual soil erosion using the RUSLE model.

The current research aims to investigate and determine the changes in land use during the last two decades in the villages of Rasht Nasha district of Rasht County; done. The research method in the present study is of quantitative type and based on the objective, it is of applied type. The statistical population of the villages of Lashet Nasha district in three villages (Jirhande Lashet Nasha, Ali Abad Zibakanar, Gafshe Lashet Nasha), between the years 2000 and 2020. In order to analyze the satellite images, at first, the pre-processing of satellite images (atmospheric corrections, geometric corrections, correction of solid lines, image classification) was investigated, and for the purpose of classification methods from Maximum likelihood method, artificial neural network, error matrix estimation, kappa coefficient were used. The results showed that during the study period, in the studied villages, agricultural land and water had a decreasing trend, and gardens and residential areas had an increasing trend. It is also worth mentioning that among the studied villages, the changes in residential areas in Ziba Kanaar and Gafsheh villages were faster than Jirandeh villages, and also the intensity of land use changes in the years 2015 to 2022 is more than other years. The current research aims to investigate and determine the changes in land use during the last two decades in the villages of Rasht Nasha district of Rasht County; done. The research method in the present study is of quantitative type and based on the objective, it is of applied type. The statistical population of the villages of Lashet Nasha district in three villages (Jirhande Lashet Nasha, Ali Abad Zibakanar, Gafshe Lashet Nasha), between the years 2000 and 2020. In order to analyze the satellite images, at first, the pre-processing of satellite images (atmospheric corrections, geometric corrections, correction of solid lines, image classification) was investigated, and for the purpose of classification methods from Maximum likelihood method, artificial neural network, error matrix estimation, kappa coefficient were used. The results showed that during the study period, in the studied villages, agricultural land and water had a decreasing trend, and gardens and residential areas had an increasing trend. It is also worth mentioning that among the studied villages, the changes in residential areas in Ziba Kanaar and Gafsheh villages were faster than Jirandeh villages, and also the intensity of land use changes in the years 2015 to 2022 is more than other years. The current research aims to investigate and determine the changes in land use during the last two decades in the villages of Rasht Nasha district of Rasht County; done. The research method in the present study is of quantitative type and based on the objective, it is of applied type. The statistical population of the villages of Lashet Nasha district in three villages (Jirhande Lashet Nasha, Ali Abad Zibakanar, Gafshe Lashet Nasha), between the years 2000 and 2020. In order to analyze the satellite images, at first, the pre-processing of satellite images (atmospheric corrections, geometric corrections, correction of solid lines, image classification) was investigated, and for the purpose of classification methods from Maximum likelihood method, artificial neural network, error matrix estimation, kappa coefficient were used. The results showed that during the study period, in the studied villages, agricultural land and water had a decreasing trend, and gardens and residential areas had an increasing trend. It is also worth mentioning that among the studied villages, the changes in residential areas in Ziba Kanaar and Gafsheh villages were faster than Jirandeh villages, and also the intensity of land use changes in the years 2015 to 2022 is more than other years. The current research aims to investigate and determine the changes in land use during the last two decades in the villages of Rasht Nasha district of Rasht County; done. The research method in the present study is of quantitative type and based on the objective, it is of applied type. The statistical population of the villages of Lashet Nasha district in three villages (Jirhande Lashet Nasha, Ali Abad Zibakanar, Gafshe Lashet Nasha), between the years 2000 and 2020. In order to analyze the satellite images, at first, the pre-processing of satellite images (atmospheric corrections, geometric corrections, correction of solid lines, image classification) was investigated, and for the purpose of classification methods from Maximum likelihood method, artificial neural network, error matrix estimation, kappa coefficient were used. The results showed that during the study period, in the studied villages, agricultural land and water had a decreasing trend, and gardens and residential areas had an increasing trend. It is also worth mentioning that among the studied villages, the changes in residential areas in Ziba Kanaar and Gafsheh villages were faster than Jirandeh villages, and also the intensity of land use changes in the years 2015 to 2022 is more than other years.

Today, studies and researches based on land use are carried out in order to meet the needs of the land surface with multiple uses such as agricultural land, gardens, residential areas and industrial areas, etc. Using remote sensing images as a new tool in surveying land cover and land use types, their changes over time can be checked and confirmed. In today's world and with the growth of technology, satellite observations are very important for understanding land use patterns in large areas and detecting changes over time.In recent years, the use of satellite images in determining land use and investigating the expansion of cities has been of great interest. The use of remote sensing technology with the aim of examining changes over time is an inevitable necessity. Paying attention to the adverse effects of land use change in the management of urban areas by planners using Landsat satellite image information is very useful. Therefore, due to the rapid growth of urbanization, not only a large amount of urban natural lands have changed their use, but the expansion of cities has caused socio-economic and physical use changes in the surrounding villages. Therefore, it can be claimed that the science of remote sensing is a comprehensive tool for managing natural resources and remote sensing satellites are the best and most accurate data sources for detecting, quantifying and mapping patterns of land use changes.

First, satellite images of three appropriate time periods were collected from different sources. The data were checked for geometric and radiometric errors and were received at the L1T level. To prevent errors, by displaying individual bands and different color combinations on the computer screen, the data in terms of radiometric errors were investigated and the atmospheric correction was done in the software using the ENVI method.To check the geometrical situation, the georeferenced image was prepared from the USGS site, and the intersections and important points were checked in the ENVI software. Then, the prepared images were classified by image classification and band combination software such as ENVI 5 and ILWIS and based on ground control, the classification was done. Relevant corrections were applied according to the needs of the obtained images. Coding and combination of color images for different decades were carried out. The next step was to determine the number of desired classes for supervised classification and to determine land use, and then to ensure the accuracy of the classification, a scattered sample was collected from all the studied areas. The fuzzy logic method based on the theory of adaptability was used to classify the image and extract land use and land cover maps. Finally, using this model, a map of land use was prepared from the studied area, and to evaluate the changes, the area of each of the land use classes in each period was drawn in the form of a table.To figure out the changes in the studied area, the maps obtained from the classification of images were studied with the orthogonal table method, and the prepared user maps were compared two by two and created as a matrix. The simulation was done in the relevant software such as IDRISI, GIS. By comparing the land use of the first two decades with the third decade and using the Markov chain method, simulating and predicting the trend of land use changes for the coming years was considered as the forecasting horizon in this research.

Geometrical corrections were made in ENVI software. The obtained images had no significant error and atmospheric correction was also applied. The RGB composition of the image was prepared and the desired OIF index was calculated by ELWISI software to prepare the best band composition of the images. The obtained combination was pasted together in ENVI and the desired range was classified. In addition, the images received from TM and ETM were combined using spectral bands and panchromatic bands, which have high spatial resolution, and a better image was created.

The 15-year study period with the expansion of built-up lands, shows the most destruction in the agricultural lands of the outskirts of the city and barren lands in the border and suburbs of the city and farming lands. This trend can lead to environmental damage and further reduction of agricultural lands in the region. Previous research and experiences show that the use of a GIS system in the field of implementation and management of land use changes, especially in agriculture, is inevitable. According to the result of the artificial neural network and Markov model and drought in recent years, it is necessary to note and manage the hydrology of the region. Also, due to the passage of two main roads, one from the southern industrial area (Southern Parian) and the other from the east, it is necessary to plan more precisely for the land uses and development of industrial and urban areas. The amount and type of cultivation in the plain lands of Firozabad need to be reconsidered so that foreseeable problems in the region can be solved before they occur. Undoubtedly, it is necessary to have a spatial database of the land use areas of the city under study, which comes from various sources, including satellite images, public information, and cadastral maps.

The purpose of this research is to investigate the relationship between LST and LULC in Heyran region. LULC indices consist of normalized difference of vegetation index (NDVI), normalized difference of built-up index (NDBI) and modified normalized difference of water index (MNDWI). The area of the studied area is 156.95 square kilometers, out of which in 1401, about 122.7 square kilometers are dedicated to forest area and only 33.2 square kilometers are dedicated to agricultural land. The values of the MNDWI index in the richest region in 2017 had an area equal to 12.27 square kilometers and faced a sharp decrease in 1401 and reached 1.68 square kilometers. Built-up areas (NDBI) increased until 2017 and decreased significantly until 1401. The maximum land surface temperature (LST) has reached from 35.42 degrees Celsius in 2013 to 39.04 degrees Celsius in 1401. The area with a temperature of 20 to 25 degrees Celsius has increased from 67.9 square kilometers to 124 square kilometers. Finally, Pearson correlation relationships showed that NDVI and MNDWI index had a negative correlation with LST index and there was a positive correlation between LST index and NDBI index. The highest positive correlation of 0.77 between LST and NDBI belongs to the spring of 2017, and the highest negative correlation of -0.71 belongs to the MNDWI and LST index, which was registered in the fall of 2017.

The present research is applied in terms of purpose, in terms of nature and method is of descriptive-analytical research. The statistical population of this study includes 37 rural settlements around the city of Rasht. In the field of sample population, according to the objectives of the study, 37 inhabited villages that share a same border with the city of Rasht were selected as sample villages. In this study, all 37 villages have been studied (total number). In this study, a researcher-made questionnaire was used to collect information. Finally, 516 people participated in completing the questionnaires. Data analysis was performed using one-sample t-test, Pearson correlation coefficient and multivariate linear regression.. The results of multivariate linear regression analysis showed that among physical factors, the factor of proximity to the city predicts up to 67% of the changes in the dependent variable. Indeed, two factors of proximity to work centers and communication routes access with coefficients of 0.548 and 0.511, respectively, were effective on land use changes. The results of studies for environmental factors showed that four indicators are effective on land use change. The tourism capacities of the village with the standard coefficient of 0.821 had the most impact. The unfavorable rural land for agricultural activities with a standard coefficient of 0.785 had an effect on changes in rural land use. Distance from irrigation sources and lack of access to water with coefficients of 0.613 and 0.568, respectively, were effective in changes in the dependent variable.

Soil erosion is very obvious and noticeable in Iran, where a large part of it is a desert and the soil does not have a suitable cover. In order to reduce soil erosion and control it, it is necessary to identify factors affecting soil erosion. Land exploitation methods, forest and pasture exploitation, creation of residential and urban areas, geological conditions, precipitation, weather factors, etc. are some of the factors that affect the intensity of erosion in the region. Therefore, knowing the quantitative values of soil erosion is effective in accurately estimating the adverse, hidden, and intangible effects of erosion

In this research, the Revised Universal Soil Loss Equation (RUSLE) Model has been used. The amount of soil erosion in the basin was calculated in two 20-year periods (1980-2000 and 2000-2020). This soil erosion model is calculated through six factorsA=R×K×L×S×C×P      (R) the Rainfall erosivity factor, (k) soil erodibility factor, (LS) are slope length and slope degree factors respectively, (c) vegetation management factor, and (P) soil protection factor. The data in this research for the implementation of this model including the rainfall erosivity factor (R), topography including slope length and slope degree (LS), and vegetation management (C) were prepared from the Google Earth Engine system. The soil erodibility factor (K) was obtained from the natural resources report. The BLM model was also used to estimate the evaluation of the RUSLE model.  The Google Earth Engine system was used to prepare the land use maps of each of the 20-year periods. The land use map of the first period was prepared using the supervised classification method and calling Landsat 5 images, and The land use map of the second period was done using the CGLS-LC100 product, which is produced and updated at the Copernicus Global Earth Center and using Sentinel satellite images

By analyzing the obtained maps, the rain erosion factor for the first period (1980-2000) has an average of 2.02, the minimum value is 1.80 and the maximum is 2.29, and the second period (2000-2020) is from 1.55 to 2.07 is variable, its average is 1.783. The erodibility factor of the region's soils varies from 0 to 0.349 and its average value is 0.0264. The topography factor of the studied basin varies from 0 to 250 and its average value is 8.77. The vegetation management factor varies between 0.181 and 0.505 and its average is 0.353. This factor varies between 0.315 and 0.494 in the second period, and its average is 0.429 and has an increasing trend compared to the first period, which indicates the decrease of vegetation in the study area compared to the first period. The ground protection factor is also considered to be 1. To calculate the annual average soil erosion rate of the Award Basin in the first period (1980-2000), the various factors of the RUSLE model were converted to the same raster format and cell size, and coordinate system. To determine the risk of soil erosion, the produced layers including the rainfall erosivity layers, soil erodibility, topography, vegetation and soil protection factor were multiplied with the help of the Spatial Analyst extension of the ArcGIS program. The amount of annual loss of soil in terms of (tons per hectare per year) was obtained on a cell-by-cell basis. According to the results, the amount of erosion in the first period varies from 0 to 59.62 tons per hectare and its average is 1.64. The highest amount of soil erosion is in the middle and eastern regions with high slopes. In the second period, the layers of the soil erodibility factor, topography and soil protection factor are the same as in the first period because they are considered constant. The amount of erosion in the area in the second 20-year period varies from 0 to 63.38 tons per hectare, and its average is 1.75 and shows an increasing trend compared to the first period. The RMSE, MAE and MSE statistical indices were used to evaluate the accuracy of the RUSLE model and the degree of agreement of its erosion classes with the output of the BLM based on the map of sampling points. Examination of the values of the mentioned indicators showed that the root mean square error, mean absolute error and mean square error statistics in the RUSLE model have low values of 1.23, 0.96 and 1.52, respectively, as a result this model has It is a small error. After preparing the land use map for the first period, it was determined that in this period, the studied basin includes four land uses: forest, agriculture, pastures and woodlands, and residential. In the second period, there have been forest uses, destroyed forests, agriculture, pastures and woodlands, and residential areas. Then the land use maps prepared in the Google Earth Engine in two periods were transferred to the GIS environment system and the area of each of the above uses was obtained. The area of forests in the studied basin has decreased by 1590.956 hectares and 2014.827 hectares have been added to the area of degraded forests. Also, 2128/368 hectares have been added to the area of agriculture in this basin, and 2557/865 hectares have also decreased from the area of pastures in this area. It should be noted that 5.6266 hectares have been added to the area of residential areas of this basin.Click here and insert your abstract text. Click here and insert your abstract text. Click here and insert your abstract text. Click here and insert your abstract text. Click here and insert your abstract text. Click here and insert your abstract text. Click here and insert your abstract text. Click here and insert your abstract text. Click here and insert your abstract text. Click here and insert your abstract text. Click here and insert your abstract text. Click here and insert your abstract text. Click here and insert your abstract text. Click here and insert your abstract text. Click here and insert your abstract text. Click here and insert your abstract text.

The findings of this research in two 20-year periods (1980 2000) and (2000 2020) in the studied area show that the amount of precipitation in the second period has decreased compared to the first period. The amount of Rainfall erosivity in the first period had a minimum value of 1.80 and a maximum value of 2.29. In the second period, its value varied between 1.55 and 2.07. Thus, the amount of precipitation in the second period did not greatly affect the process of increasing soil erosion. However, the examination of the pictures and maps prepared on the amount of land use changes shows that the amount of forest and pasture area in this region has decreased and the area of destroyed forests and agricultural and residential lands has been added. Therefore, the role of land use changes in increasing soil erosion is significant. The research results of Teimouri (2018), Mayahi (2021) and Arkhi (2022) also confirm that increasing rainfall, changing land use and reducing vegetation are effective in increasing soil erosion.

One of the important conditions for optimal use of land is obtaining information about landuse patterns and their changes over time. Landuse is usually defined based on human use of land, emphasizing the role of land in economic activities. Today, remote sensing technology is considered as the main element in landuse monitoring. The aim of the current research is to extract landuse maps for the years 2000 and 2021 in FirozabadKhalkhal region and to investigate the changes made in the studied time period in the region using the images of ETM and OLI sensors of Landsat. Also, checking the capability of basic pixel and object-oriented methods for landuse classification is another purpose of this study. In the current research, the object-oriented technique nearest neighbor algorithm and the vector machine method supporting the pixel-based algorithm have been used for landuse classification. Then, to verify the accuracy of these two methods, the overall accuracy and Kappa were extracted. The results of this evaluation show the high accuracy of the object-oriented method in extracting land use classes. Based on the results of the detection of landuse changes in the studied time period, the highest amount of changes occurred is related to the use of good pasture to poor pasture with a value of 51.72 square kilometers, followed by forest to good pasture with a value of 30.11 and the lowest changes It is related to the use of pasture and water with the amount of 0.03 square kilometers. The reasons for these changes are the increase in population, indiscriminate grazing of livestock, incorrect and illegal use of different lands. The use of more parameters such as scale, shape, compactness, color, texture, smoothness criterion and pattern for landuse classification in the object oriented technique can be considered as an innovation of the present study.

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

Wetlands as an integral part of the global ecosystem in flood prevention or mitigation, feeding aquifers and providing unique habitat for plants and animals and other services and benefits are key elements of a regional conservation strategy. Anzali International Wetland in Guilan Province is one of the 10 most valuable wetlands in the world, which has undergone many changes in land use and vegetation due to structural changes resulting from man-made processes, and its nature and ecological functions have been endangered. The purpose of this study is to investigate the application of remote sensing data in mapping changes in the spatial pattern of the landscape with the help of field work training areas at the bed of the wetland and to analyze the changes of territorial cohesion based on the metrics of the landscape. First, satellite data were analyzed and Sentinel-2 images from 2016 to 2020 were classified by training areas. Then, a map of land cover in 7 classes of agriculture, barren, reed, forest, rangeland, water and urban area was created for mapping and analysis of land use metrics. After extracting class-level and landscape-level metrics in Fragstats software and determining appropriate metrics using PCA method with R and Canoco software, LPI, LSI, ENN_MN, CA, TE, NP, SHAPE_MN, PARA_MN, IJN, ARE_ Applications were selected for better analysis of the area. Analysis of metrics indicates that, in general, the landscape is fragmented, more complex and irregular in form, and more discontinuous in terms of the degree of integration of structural elements.

Land use change has acted as a pivotal factor in environmental change and has become a global threat. Reviewing these changes through satellite imagery and predicting and evaluating their potential through modeling can help environmental planners and natural resource managers to make informed decisions. The purpose of this study was to review, model, and predict land use changes in the 30-year period of 1993-2013 by the Markow-LCM chain model in Kangan and Assaluyeh. For this purpose, land use maps were prepared using ETM +, TM and OLI satellite imagery in three periods of 1993, 2003, and 2013. Then verifying the maps and detecting the changes. Using the classification of the neural network and applying the Land Change Modeler (LCM Markov model) and the Land Use Change Modeling Approach have been implemented. The results of detection of changes in the first period with a kappa coefficient of 97% and the second period of 1993-2003 with a kappa coefficient of 94% indicate that the largest changes in the area in the water area and the largest decrease in the area in the vegetation area occurred. In order to calibrate the Markov chain model, the 2013 map was predicted and the error mapping matrix of the 2013 map reference model and mapping utilization yielded a copper coefficient of 93%. The results of modeling the transfer force using the artificial neural network in most of the sub-models The high accuracy was 60-93%.