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.

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.

The deficiency of surface water in arid and semi-arid territories has exacerbated the dependence on groundwater resources, resulting in considerable reductions in groundwater levels. This phenomenon has been particularly pronounced in numerous plains throughout Iran, where the diminution has exacerbated issues related to land subsidence. A comprehensive understanding of groundwater level variations is imperative for enhancing water management strategies and alleviating the associated hazards. A range of statistical, mathematical, and machine-learning methodologies have been utilized to model the dynamics of groundwater aquifers. Recently, deep neural network algorithms have gained prominence in the investigation of surface and groundwater resources, particularly in light of the spatiotemporal characteristics inherent to groundwater. In the present investigation, a hybrid spatiotemporal data mining framework, denoted as Wavelet-PCA, was employed to analyze data acquired from 44 piezometric wells situated in the Qahavand plain over a span of three decades (1988-2018) for the purpose of elucidating temporal and spatial patterns associated with fluctuations in groundwater levels. Subsequently, a sophisticated deep recurrent neural network architecture incorporating Long Short-Term Memory (LSTM) was implemented to model the time series data resulting from the data mining procedure. Various degrees of wavelet transformation were applied to effectively capture the intricate trends in groundwater levels. The LSTM model exhibited a coefficient of determination (R²) of 0.85 for the training dataset while achieving an R² of 0.62 for the testing dataset. The research additionally examined regional patterns of land subsidence utilizing radar interferometry data obtained from the Sentinel-1 satellite during the period from 2014 to 2019. The results revealed an average maximum subsidence measurement of 9 centimeters, with the most pronounced subsidence noted in regions that are undergoing the most substantial declines in groundwater levels. This observed relationship between groundwater depletion and land subsidence underscores the necessity for judicious land use planning and the implementation of effective water resource management strategies in analogous regions.

In the current era, following the occurrence of environmental crises, the destruction of resources and the creation of obstacles on the way to sustainable development, it is necessary to carry out programs based on the recognition and assessment of ecological potential so that exploitation in It should be fed continuously from the environment and the natural values of the environment should be preserved. Therefore, after formulating development strategies and implementing social economic programs, geographical survey of the region and recognition of its environmental capabilities and then determining the ecological potential of the land for different uses with the aim of continuous exploitation with the least Destruction and preservation of the environment is an inevitable necessity. The ecological capacity of the land allows the planner to determine the direction and solutions of the region's development based on the region's capabilities, and provide a plan that fits the conditions of the region. Evaluation of the ecological potential is an effective step and a suitable tool to direct the current activities and uses in the land towards sustainable development. FAO defines "land suitability assessment" as an assessment process that considers the performance of land when used for a specific purpose. The assessment process is directed towards optimal land use by providing important information about the opportunities and constraints in using a given land.

According to the review of various library sources as well as the conditions of the region, 10 criteria of Elevation, slope, Aspect, distance to main roads, distance to waterways, distance to fault, distance to landslide points, distance to flood plains, Normalized Difference Vegetation Index (NDVI) and land use were investigated as different criteria for capacity measurement. To study the capacity of the studied area and to prepare suitable areas for the development of Ecotourism, the following steps were carried out; A): Assessment of land suitability to check the capacity of the region for tourism development using the MCE method First step) defining the set of evaluation criteria (information layers),  The second step) standardizing the criteria, The third step) defining the weights of each criterion, Fourth step) preparation of the final map: in the last step, the obtained weights were multiplied in the required layers and then added together. The fifth step) using the final desirability layer produced at the end of the fourth step, places that have a higher value than other areas, using the location method based on suitability and area (ZLS) as suitable places. They are selected for the development of nature tourism. B): Selection of the most important socio-economic parameters and ranking of the spots: the values of these indicators were extracted for the selected spots and at the end, the rank of each spot was determined using the TOPSIS method.

The results of the AHP questionnaire show that the Criteria of slope, Elevation and NDVI are the most important Criteria affecting the development of Ecotourism in this region. The results obtained for the development of Ecotourism in the studied area show that 21,269 (8.63%) hectares of the area are without capacity, and 6634 (2.70%) hectares are of the area with very high capacity. Due to the fact that a minimum area is required for the development of concentrated Ecotourism, in this study, seven areas with areas of at least 100 hectares were selected from the very high capacity category. Based on the results obtained from the AHP method, respectively, the indicators of the diversity of the area, the amount of pristine, the distance to road, the total population within 5 kilometers of the area and the average suitable map have the most importance on the selection of the best area for the development of Ecotourism. The results of the TOPSIS method show that region 2 is the best place for the development of Ecotourism in this watershed with a score of 0.8188. Then regions 5 and 1 were selected as the second and third regions with scores of 0.7868 and 0.6506 respectively. The places with the lowest rank are regions No. 4 and 3 with a score of 0.3197 and 0.0464 respectively.

Among the different capabilities of each region, tourist attractions are one of the most important natural resources in each region, and are important factors in attracting tourists and attracting capital, and thus are the main basis for sustainable development for the region. The results of the survey show that all three selected final regions are in the central part of Noor city and region 2 has the largest area (370.759 hectares) in terms of area. Also, according to the average map, it is equal to 0.928 and in terms of access, it is 144 meters away from the main road, and its virginity is 80%. Various studies (Balist et al., 2019), (Zarei et al., 2013), (Pour Ahmed et al., 2013) in the world show the superiority of this model (the combination of AHP method and TOPSIS method) over other models confirmed in their studies.

In Iran, specifically in Sari, neglecting the mutual relationship between public transportation and urban development has led to uneven development. The main objective of this study is to assess the possibility of implementing the TOD development model in Sari with future studies approach. This study uses a quantitative method to achieve its goal. Documentary, library, and field study methods were used to collect data. The data collection tool in this study was a questionnaire distributed among 50 experts in urban and transportation planning using cluster sampling. Hierarchical analysis, statistical analysis, and SWOT techniques were used to analyze the data. Initially, four bus stations on Keshavarz Boulevard, Pasdaran Boulevard, Azadi Boulevard, and Imam Reza Boulevard in Sari were selected. Based on public transportation-based development criteria, these four stations were compared, and using the AHP method, the Imam Reza Boulevard bus station was selected as the best station for public transportation-based development. Then, a SWOT analysis was conducted for it and the scenarios were developed based on a qualitative futures studies approach. The positive aspects of this station include suitable residential density, diverse bus stations within an 800-meter range, and the potential for increased density. Its weaknesses include a lack of parking around the station, a lack of green space, and the absence of pedestrian and vehicular separation. Its most important strategies include smartening the public transportation system, appropriate distribution and deployment of land uses, and improving the quality of public transportation.

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.

In the research, the carbon storage capacity of Urmia's urban and suburb green infrastructures were analyzed. Urmia is characterized by a cold climate with a dense building structure with scattered green spaces, especially in the surrounding areas and neighborhoods of the city. The research was carried out using the carbon storage model available in the InVest software package. The results revealed that more than 57% of the study area has a carbon storage capacity of less than 2 tons, and less than 6 percent of the area has more than 30 tons per hectare, which is limited to the gardens and groves along the Shahrchai River. Soil carbon storage has the highest share with 2344.41 tons, and above biomass carbon storage followed closely with 1403.47 tons. The total amount of carbon storage in the studied area is 3900.9 tons per year. The carbon storage was highest in gardens and groves, followed by barren lands with sparse vegetation and rocky outcrops mountain’s without vegetation and soil cover had no carbon storage. Dense plants and trees have the highest storage capacity per unit area, However, the amount of storage depends on the season, so it is necessary to consider the selection and expanding the urban green spaces according to the types of plants and their compatibility with the climatic conditions and urban spaces of Urmia. As a result, it is necessary to create and develop urban green spaces at the same time as physical development, it should be the priority of Urmia's urban development plans.

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.

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.

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

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.

 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.

, the purpose of the current research is to assess and zonate the risk of flooding using the MFFPI model in Shafarood watershed, Gilan province. In this regard, in order to achieve the goals of the research, 6 parameters of the MFFPI model were used, including the parameters of slope, slope, flow density, soil texture, rock permeability, and land use. For this purpose, Landsat 8 satellite images, topographic map with a scale of 1:50000, geology 1:100000 of Razvanshahr city (taken from the Natural Resources Organization) were used to extract and prepare functional maps. In the next step, the mentioned maps were produced in the Arc Map environment. Finally, based on the scoring table of the MFFPI model, each of the maps extracted using the Raster Calculator plugin was given a weight corresponding to the classification class, and the weighted layers of the parameters of domain curvature, slope, flow density, soil texture, rock permeability, and land use were produced. In the last step, by combining the 6 parameters of the studied model, the final flash flood zoning map for the Shafarood watershed was prepared and produced in 5 classes (very low, low, medium, high and very high risk). The results of the final flood zoning showed that the areas of the southern and southwestern parts of the basin had very high and high risk potential, and on the other hand, the central parts of the basin had medium and low risk potential. The results of this research can help managers and relevant officials to identify and deal with possible flood risks in the future, especially in areas with high flood risk potential, to prevent financial and life losses for the studied area by making correct decisions.