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

The health of the river basin is determined by the health of its ecosystem to provide important and valuable resources and services for human use and the basin itself. However, the changes in the land use pattern, which is an effective reflection of anthropic activities, have greatly disturbed the health of the river and are the main driver of water quality reduction. Examining the relationship between land use patterns and river water quality provides an important basis for water quality safety and effective land use management. Therefore, the aim of this study is to investigate the influence of land use patterns on surface water quality based on the water quality monitoring data and land use data from 38 sampling points in the sub-basin of the Maroon River.

In order to sample from the study area, first, the boundary of the sub-basin of the maroon river was determined, and then the sub-basin was divided into different smaller sub-basins using the hydrological analysis tool in ArcGIS software, and the map of waterways in the region was also prepared. Then, sampling stations were selected from the exit point of each of these sub-basins in the main sub-basin area. In order to measure the water quality parameters of the studied area, sampling was done from 38 monitoring stations in the sub-basins in triplicates in the spring of 2023. The land use map was prepared using Landsat satellite images to evaluate the changes and the impact of land use patterns on the water quality status of the Maroon River sub-basin. Then, using geographic information system and multivariate statistical techniques, the effects of land use on river water quality in the Maroon sub-basin were estimated. In addition, in order to evaluate the quality of river water in different sub-basins, water quality data was analyzed using the water quality index (WQI).

The results of the evaluation of the distribution of land use patterns showed that the use of pasture is the dominant use in the sub-basin of the Maroon River and the water quality parameters exhibited significant changes in the stations covered by agricultural and forest use. The results of correlation analysis and linear regression of water quality parameters and land use patterns in the Maroon River sub-basin showed that agricultural land has a negative relationship with pH and DO parameters and a positive relationship with parameters ,  and Ca2+, forest land has a positive correlation with DO and a negative correlation with , and urban land also showed a negative correlation with DO. WQI values in different monitoring stations were estimated between 73.80 and 288.73 which showed that the health level of the river upstream of the sub-basin was better than downstream. In general, based on the WQI classification, 62.5% of the water quality of the Maroon River sub-basin was in the "poor" class, 25% in the "very poor" class, and 12.5% in the "good" class.

The findings of the research showed that agricultural land was the key factor affecting the water quality parameters and as a result the decrease in water quality in the sub-basin of the Maroon River, so limiting the discharge of runoff from agricultural activities is critical for improving water quality in the study area. This study highlights the importance of LULC changes in water quality for making informed decisions on proper watershed planning and management.

One of the most important principles in the exploitation of forest resources is to minimize the amount of damage to the soil and reproduction during exploitation operations. Estimating the amount of these damages can play a significant role in forest management. As a result of the traffic of exploitation machines, the forest soil undergoes destruction and changes. For example, the decrease in soil carbon deposition causes large changes in the concentration of atmospheric carbon dioxide and as a result, reduces the proper functioning of the ecosystem. Logging paths are paths that are created spontaneously as a result of going back and forth from a specific strip (for pulling wood by a tractor) on the forest surface. These routes are defined by the authorities before the start of exploitation operations for the movement of tractors and skidders, so that as a result, the whole area of the parcel, trees and saplings are not damaged, which sometimes obstructs the harvesting (such as stones and so on) in the way of logging, it is done and it is sufficient. The main purpose of these routes is the removal of wood from the forest. As a result of this activity, they lead to negative effects on the balanced system of the forest, including soil degradation and the production of runoff and sediment in the region. Although the use of ground logging system causes the most environmental problems, it is a common operation to remove wood from the cutting area, which causes compaction in the soil. Several studies have been conducted in different parts of the world to investigate the effects of logging on the physical and chemical properties of soil. The results of these studies have shown that ground logging causes soil compaction and increases the soil bulk density. The highest amount of these factors was also observed in the place of wheel tracks. Also, the results of the studies have shown that the intensity of soil compaction at a depth of 0 to 10 cm is higher than at other depths and the amount of organic matter in logging paths has been recovered after 7 years. In most of the studies conducted regarding the effects of logging, most of the physical properties of the soil have been taken into consideration, while other structural and chemical properties of the soil are equally affected by this activity and are transformed. In this regard, in the present study, all the chemical and physical indicators of the soil have been considered in order to investigate the impact of logging activities on them. Examining changes in soil properties alone is not capable of responding to management guidelines. Also, by examining and determining the changes of soil indicators in logging routes with different time history, it is possible to maintain the quality of the soil and help to renew it. Therefore, in this research, the effects of changes in time intervals on the variability of physical and chemical indicators of soil due to logging routes have been investigated.

Series 1 Nav Asalem belongs to watershed No. 7 Nav within the forest area of Talesh city under the supervision of the General Directorate of Natural Resources and Watershed Management of Gilan province. The forest cover is suitable and in good condition in terms of regeneration. The developed soil texture is mostly heavy to slightly heavy and in the area of shallow soils it is medium to light. The soil types in the studied plots are forest brown soil and forest washed brown soil. Linear sampling method was used to collect information. Then, at intervals of 50 meters, a sample line of 7.5 meters length was laid down on the logging paths perpendicular to the path, considering the center of the logging path. Then, at the beginning, on the wheels, and also at the end of the transect, soil sampling was done. Also, soil sampling was done at a distance of 30 meters from the logging roads (control area). Finally, 27 soil samples were collected from the depth of 0 to 10 cm using cylinder. By using soil samples, soil texture characteristics, apparent specific gravity, true specific gravity, total porosity, acidity, electrical conductivity and organic carbon percentage were measured. Analysis of variance and Duncan's mean comparison test were used to analyze the data.

The results showed that there is no significant difference between the measured properties (with the exception of the soil subsidence resistance) in the logging roads and the control area. The results of the investigation of soil subsidence resistance also showed that there is a significant difference between logging routes and the control area in relation to this index. In general, the presence and movement of exploitation machines in the forest causes many changes in the physical and chemical properties of the forest soils, as a result of which other major changes occur in the forest environment. In the current research, by examining the effect of ground logging operation on the soil properties of the logging routes, it was concluded that most of the investigated properties (with the exception of the soil subsidence resistance characteristic) were recovered after 5 years. Although the research results showed that there is a difference between the average characteristics of the investigated area and the control area, but these differences were not statistically significant. Therefore, it can be said that the soil of the logging roads has been able to return to its original state approximately within a period of 5 years. It seems that changing the logging routes after a maximum of 5 years and creating new logging routes (provided no new damage is caused to the forest ecosystem) or creating a consecutive rest period for the existing logging routes can restore the soil indicators of the forest ecosystem should be accelerated.

Drought is a natural phenomenon that occurs almost in most regions of the world, and due to its relationship with agricultural products and water resources, it is considered as one of the most important issues in environmental sciences. The effects of this phenomenon are greater in arid and semi-arid regions due to their less annual rainfall. In contrast to traditional methods, the use of remote sensing techniques and satellite images has been considered as a useful tool for agricultural drought monitoring. The main objective of this study is to investigate changes in agricultural land use using normalized vegetation difference index and satellite images.

In this study, Landsat satellite images were used to investigate the trend of agricultural land use changes in the Zayandeh Rood catchment during 1984-2023. To do this study, the normalized plant difference index was used for each year. Since various patterns of cultivation with different time differences are present in the study area during a year, it is not possible to use a selected image as the basis of a year, on the contrary, it is necessary to examine different images for different times of the year. To identify and specify the set of all the pixels that have gone under the cultivation surface in one crop year. Since this process would be very time-consuming, an innovative approach was used. First, in the Google Earth Engine system, all the annual Landsat images were called year by year. Then, the images with cloud cover were removed and the maximum filter was applied to the bands of the remaining images. Then, the normalized vegetation difference index of new annual images was created and by applying a threshold of 0.2, agricultural lands were separated from other lands. The extent of agricultural land was calculated in each year and the linear regression model was used to identify the change process. In other words, the extent of agricultural land was used as a dependent variable and time was used as an independent parameter on an annual scale.

The extent of agricultural land in 1984 was about 25 thousand hectares, which with a decreasing trend over time reached 21700 and 15180 hectares in 1994 and 2014, and finally reached its lowest value in 1401. It has reached 11.250 hectares. This trend shows a 55% reduction in the abandonment of agricultural land at this point in time. Also, the value of the normalized plant difference index in agricultural lands has experienced a decreasing trend over time, which indicates the change in the cultivation pattern towards low-density crops with low biomass such as wheat.

The results of the changes in the extent of agricultural use in the study area showed a decreasing pattern, so, there has been a loss of agricultural land, which is consistent with the decreasing pattern of the water level of the Zayandeh Rood watershed. This phenomenon can be directly attributed to the reduction of water resources in the region. In the last decade, the amount of water allocated to carry out agricultural activities in this region has decreased a lot due to the water volume of the Zayandeh Rood watershed approaching critical limits.

Wetlands, as one of the most important types of ecosystems in the world, are extremely threatened. In addition to being part of Iran's protected areas, the Parishan wetland is also known as an international wetland and biosphere reserve. Understanding the process of changing in this wetland, can be very helpful in improving its future status. Therefore, the purpose of the present study is to monitor the changes in the over a 30-year period.

For the purpose of the research, Landsat satellite images were prepared for four time periods of 1987, 1998, 2007 and 2016 along with other required data. By performing the required preprocessing in ENVI 4.7 software, Parishan wetland land-cover maps was extracted using Normalized Difference Vegetation Index and Normalized Difference Water Index combining with Decision Tree method in three class including water-body, vegetation and others land-cover.

The results showed that after 30 years only 13 hectares of 1963 hectares of Parishan wetland water-body remained. Monitoring of changes shows that Parishan wetland water-body has decreased by 1950 hectare in comparison to 1987, 3605 hectare in comparison to 1998 and 2272 hectare in comparison to 2007.

using satellite data and remote sensing techniques along with Decision Tree classification model indicate the capability of this method for identifying and classifying land-cover in wetland areas where vegetation and water are intertwined.

In recent years, increasing of greenhouse gases results in global warming and climate changes. Carbon sequestration is a result of carbon capturing in different parts of ecosystems, particularly in soil. The purpose of the present study is evaluation of carbon sequestration potential in wheat field, citrus garden and grassland in urban district of Behshahr.

The soil samples were collected from ten different points for each land use. They were randomly taken from a depth of 30 cm using systematic random sampling. Texture, apparent specific density, acidity, humidity, organic carbon and nitrogen of the soil were measured in laboratoty. The analysis of variance of soil properties indicates significant difference in studied land uses regarding to carbon sequestration.

The results showed that the average carbon sequestration in wheat field, citrus garden and grassland were 36% (Ton/Ha), 54% (Ton/Ha), 51%(Ton/Ha) , respectively. Totally, citrus garden had the highest carbon sequestration among studied land uses. Grassland and wheat field were ranked in second and third places, respectively. Via Pearson product-moment correlation, it was revealed that among all analyzed parameters, nitrogen had the most effect on soil carbon sequestration.

The results of the present study show how land use effects on soil carbon sequestration, hence considering these results is necessary for Lands Management in North of Iran.

Coastal areas worldwide hold significant social and economic importance. These areas, in addition to providing essential ecosystem services, have considerable potential for activities such as tourism, industry, and transportation, contributing significantly to the economic and social development of countries. Given that coastal areas are among the most complex ecosystems, they require monitoring and planning for enhanced protection. Timely and accurate identification of land use changes, which form the basis for better understanding human-nature interactions, provides the necessary groundwork for the efficient management and utilization of coastal resources.

The present study aims to investigate land use and land cover changes in the Chabahar coastal areas for four periods, including the years 1368, 1378, 1388, and 1398, using Landsat satellite time series data. Land cover mapping was performed through preprocessing and processing stages, followed by classification using a combined method. The accuracy of the produced maps was assessed using error matrix, Kappa index, and overall accuracy, which were greater than 80% and 0.8, respectively. Land use changes were analyzed using landscape metrics.

The results indicated that barren land had the highest land use percentage in all studied years. Saline and barren land cover decreased by 398.28 and 75.7 hectares, respectively, from 1368 to 1398, while aquatic land cover increased by 115.3 hectares in 1398 compared to 1368. The analysis of vegetation cover also revealed that this land use, along with human-made structures, consistently allocated the smallest area in all periods, gradually increasing. The accuracy assessment of land cover classification showed high accuracy in the produced maps, with the highest and lowest accuracy rates in 1368 (93.25%) and 1398 (85.6%), respectively. In 1398, the number of patches for aquatic land, vegetation cover, and human-made structures increased (830, 2662, and 4, respectively) compared to 1368 (146, 2386, and 1, respectively), while the number of saline and barren land patches decreased in 1398 (643 and 761, respectively) compared to 1368 (720 and 1060, respectively).

The study results demonstrated considerable changes in the Chabahar coastline over the past 30 years. The findings indicated a significant increase in vegetation cover from 1368 to 1398 (from 116.34 to 202.30 hectares), contributing a total of 85.96 hectares to land use. This increase in vegetation cover can be attributed to agricultural expansion. The detection results of changes in human-made areas also showed substantial growth (133.18, 205.74, 228.29, and 411.42 in 1368, 1378, 1388, and 1398, respectively) during the study period. Overall, it can be concluded that, based on the analysis of landscape metrics, the increase in human-made land uses and environmental changes has continued, and integrated management plans for coastal areas have not been adopted.

Soil resources play an important role in providing the necessary material goods for humans and other organisms and also deliver multiple ecosystem services that are essential for life on earth. They have also served for a long time as an important green infrastructure in protecting agricultural and forest landscapes by providing plants a foothold for their roots and holding the necessary nutrients for their growth. In addition, soils can provide various ecosystem services such as contaminant immobilization, rainwater control, carbon sequestration, and habitat provision that are directly beneficial for humans. Services provided by ecosystems for humans are called ecosystem services. Soil retention, which refers to the potential of ecosystems for controlling soil erosion and conserving soil, is classified in the class of regulating services.    

The InVEST Sediment Delivery Ratio (SDR) model was used in InVEST Software to quantify soil retention and erosion. The required inputs for implementing this model include land use maps, K-factor (soil erodibility), R-factor (rain erosivity), C-factor (land use and land cover or LU/LC), P-factor (support practices), DEM (digital elevation model), and the biophysical table. 

Based on the results, the potential of soil loss and sediment transport in the study area ranged from zero to 248.18 t/pixel and from zero to 57.25 tons per pixel, respectively. Soil retention is also estimated in a range from zero to 124.85 tons per pixel in the studied area. The largest amount of soil loss happened in sub-basin number 14 with 13716400 t/year and the smallest in sub-basin number 4 with 416594 t/year. Most of the ecosystem service of soil retention belonged to sub-basin number 13 with 4304414 t/ha/ year and the least to sub-basin number 4 with 5645 tons/ha/year.

The dense forests in the northernmost part of Semnan Province provide the most part of the ecosystem service of soil retention with more than 36 t/ha and the desert areas, the salt lake, and the salt marsh the least. Based on this, the province's forests, including dense, semi-dense, sparse and thin forests, contribute to the maintenance of soil in the province by a total of 4269166 tons per year. Also, good pastures maintain more than 18 tons per hectare of the province's soil every year, and the total function of soil maintenance by all types of pastures in the province, including good, medium and poor pastures, is 9395160 tons per year. Since the area covered by the pastures is 18 times more than that by the forests, we can say that most of the ecosystem service of soil retention is provided by the pastures due to the geographical distribution of this service in the province, despite the fact that forests are more capable in soil conservation than pastures. The orchards and rainfed agricultural land rank third and fourth, respectively, in soil retention with 7.86 and 2.15 tons of soil/ha, respectively. However, man-made land uses such as urban areas decrease this ecosystem service because they are usually accompanied by removing or reducing the vegetation. The urban areas are located in the northern part of the study area, and they have negative impacts on this ecosystem service. Therefore, protection of the forest and rangeland covers in the province is vitally important for the continued conservation of the ecosystem service of soil retention.

Determining the runoff coefficient in a distributed way can be used to identify the runoff producing areas. The runoff coefficient represents the ratio of runoff to total precipitation in different areas, where the previous soil moisture is not taken into account. The runoff coefficient without considering the effect of soil moisture is called the potential runoff coefficient, which is determined based on different parameters in hydrological studies. The changes in the watershed runoff coefficient depend on the topographic characteristics and especially the slope. Assessing the spatial changes of runoff coefficient at the watershed scale is very important for understanding the hydrological cycle under natural and disturbed condition. The location of homogeneous and similar units in terms of hydrological behavior in the watershed is determined and identified by determining the spatial map of runoff production. Meanwhile, determining the watershed response is important in the production of flood runoff volume. It should be noted that the similar units based on hydrological response are usually defined based on runoff production using field measurements. In this regard, the spatial data mapping provides the possibility of preparing a map of the runoff coefficient in a short time and will increase the accuracy of the work. Anthropogenic intervention in the natural water cycle through the destruction of vegetation in watershed areas, land use change, development of impervious surfaces lead to increasing the possibility of flooding in various areas. Various factors affect the occurrence of floods, which can be mentioned the intensity of rainfall, the slope of the land permeability, relief, characteristics of vegetation and different soil conditions. The runoff coefficient is one of the important parameters for estimating the peak flood of hydrological models and identifying important areas of sediment production and pollutants in runoff producing areas. Several factors have been used in determining homogeneous hydrological units with similar runoff coefficient, e.g., rainfall distribution, soil moisture, bedrock depth, evaporation, geology, land use, soil and slope.

The purpose of this research is to surface runoff potential mapping using combined table and the soil conservation service curve number (SCS-CN) method in the Mohammadabad Katul watershed in Golestan province. The area of study area watershed is 404 square kilometers and a main river length is 30.5 kilometers. The minimum and maximum elevation of the study watershed is 455 and 3671 meters above sea level, respectively. The average annual precipitation of the study watershed is 530 mm, and the average annual temperature is 16.5 centigrade degrees. Also, the average slope of the study area is 41.6%. The land use map of the study area was obtained from the General Office of Natural Resources and Watershed Management of Golestan province and the land use types were modified during the field surveys, then the land use map was digitized in the GIS environment. The soil map of the study watershed was also prepared based on previous studies and then digitized using GIS and the soil map has been prepared. The digital elevation model of the study area with a cell size of 30x30 meters has been obtained from topographic map with a scale of 1:25000. The slope map of the watershed was prepared from the DEM and then classified into four slope classes according to runoff coefficient table. Based on this, the necessary information to determine the runoff coefficient including the land use map, slope and soil texture was prepared. Then, the values of the potential runoff coefficient were determined using the combined table in the study watershed. Also, by incorporating the required layers, the curve number map of the study area has been prepared. The maximum 24-hour precipitation data of the nearest rain gauge station (Fazel abad) has been analyzed. After statistical analysis, the best probability distribution function fitted to the data has been selected for further analysis. Then, the runoff height and the value of the runoff coefficient were determined in 5, 10, 25, 50 years, return periods using the SCS-CN method. In the next step, the results of the combined table method and the SCS method were compared in estimating the amount and spatial distribution of the potential runoff coefficient.

The results of this study showed that the runoff coefficient was 39% according to the combined table method. The maximum coefficient of potential runoff in the study watershed was estimated to be 0.55, corresponding to the steep and agricultural land use of the study areas. Also, the minimum runoff potential value coefficient was 0.13. Based on the results, the combined distributed method incorporating land use, soil texture, and slope layers has the ability to determine the spatial changes of the runoff coefficient. In the following, the fitted frequency distributions were evaluated based on the goodness of fit criteria, and the Combined Laplace frequency distribution was chosen as the best frequency distribution to calculate the rainfall values in different return periods. The value of the runoff coefficient was 0.29 in 50-year return periods.

In the present study, the runoff coefficient map was prepared using the combined table method and SCS-CN method. In this regard, the GIS layers of slope, soil, land use and combined table were used to prepare the potential runoff coefficient map of the watershed. It seems that the calculated runoff coefficient based on the integration of the influencing maps takes into account the main and effective factors on runoff production, and provide an accurate spatial runoff coefficient map. As a concluding remark, it can be said that the combined and SCS-CN methods have provided similar results, but the runoff coefficient numbers provided by the combined method are higher than the SCS method. Considering the effect of several factors, including rainfall characteristics, relief, land permeability, vegetation characteristics and physiography on the flooding of a region, it is necessary to develop a method that can be used to map the runoff coefficient to the flooding map based on the affecting available factors. The integration of different layers in GIS and the use of a combined method is a useful tool for determining the runoff coefficient in ungauged watersheds, which allows the use of the runoff potential map in reducing the possible effects of floods.

Urbanization changes natural landscapes to human-made spaces and uses. With the expansion of cities, many of these spaces give way to roads, buildings and urban facilities and cause changes in different levels of the city, and these changes have very important effects on weather conditions (Shamsipour et al. 2013: 59). )The development of urbanization is one of the effective factors in increasing the air temperature in urban areas, which causes the creation of thermal islands in these places compared to the surrounding environment. This factor can have a negative effect on air quality and endanger the general health of society. (Mousavi Baighi et al., 2010. 190). What is considered as a fundamental defect in monitoring the temperature of the earth's surface is the lack of sufficient meteorological stations to know the temperature values. Today, this shortcoming has been solved by remote sensing and it can cover a large area of the earth's surface.

The study area is Amol city. The city of Amol is located in the Mazandaran province and the sides of the Heraz River with a height of 76 meters above sea level at 52 degrees and 21 minutes east longitude and 36 degrees and 25 minutes north latitude and at a distance of 70 kilometers west of Sari, the capital of the province, 18 kilometers south of the Caspian Sea and 6 It is located one kilometer north of Alborz mountain and 180 kilometers northeast of Tehran.In this research, Landsat 8 satellite images and Landsat 5 satellite images were used for 1990 in order to extract the land use map and surface temperature of 2020. In order to remove the effect of cloud cover from the images as well as the high intensity of sunlight, the desired images were taken from the summer season. Google Earth software was used for better accuracy of images, ENVI 5.3 software was used for atmospheric and radiometric corrections, and finally ARC GIS 10.8 software was used to prepare relevant maps.Using the atmospheric correction model (FLAASH), the data were qualitatively controlled and the radiometric error of the satellite images was corrected. In order to obtain a statistical set that represents the spectral pattern of land cover, training data must be selected before supervised classification of images. At this stage, information from the uses and topographical maps of the region were prepared using the visual interpretation of the images for all five floors, to prepare educational data for use in supervised classification operations. Maximum likelihood classification method was used for land use classification. This method is considered a part of the supervised methods for classification and for this purpose it uses a set of training data. In this method, after evaluating the probabilities in each class, the pixels are assigned to the classes that have the most similarity, and if the probability values are lower than the introduced threshold, they are considered as unclassified pixels.After that, the brightness temperature of the sensor is done by converting the digital values of band 6 in Landsat 4 and 5 and also band 10 in Landsat 8 to spectral radiance and converting the spectral radiance to the brightness temperature of the sensor in terms of Kelvin.Then, red and near-infrared bands were used to calculate NDVI to obtain the normalized vegetation difference index. After calculating NDVI we need to get Emissivity. Emissivity is the amount of reflection of a phenomenon relative to the black body. Then the land surface temperature (LST) is calculated. By using LST, it is possible to calculate the temperatures near the surface of the earth. In order to know and evaluate the correctness and accuracy of the classification, the user's accuracy, overall accuracy and Kappa coefficient were calculated in 1990 and 2020.

In this research, in the first step, the classification and the resulting changes were done in a specific time frame in Amol city and its surroundings. The classification results indicate that the classification in both periods, especially in 2020, was highly accurate, and its kappa coefficient and overall accuracy were at their highest coefficient, i.e. 100.After classification, the changes obtained in the area were examined for a period of 30 years and the changes were extracted for each land use in terms of hectares. The change of use from agriculture to the city and also from the city to roads and streets have the most changes. These changes indicate that the increase in urban use has caused a decrease in agricultural use and the size of urban areas has increased.Using Landsat satellite images, the temperature of the earth's surface has been studied in relation to land use and the results showed that the temperature is different in different uses. The highest temperature recorded for the years 1990 and 2020 in Amol city is related to urban use, the recorded temperature of which is 32.6 and 40.5, respectively, which shows the concentration of heat in urban areas. Urban use has the highest temperature due to the presence of man-made factors and heat absorbers such as asphalt, concrete and the presence of machinery. Also, the presence of tall buildings acts as a barrier to the heat escaping to the surroundings and in some way traps the heat inside the cityWith the development of urbanization in Amel city, a significant part of the area of natural and forest areas has been replaced by industrial areas, buildings and other infrastructures. The lowest temperature recorded in Amol city is related to forest use with 23.8 and 28.4 degrees Celsius. In forest areas, due to high albedo, high humidity and more open space, the temperature is lower and heat absorption is low there.The relevant researchers and experts in the region can use the results of this research to obtain information about the temperature of the earth's surface, land use, and also the changes that have occurred in the region, In order to predict the future situation of the region, they will take appropriate and correct policies.

Updated and correct information is necessary for using and optimized managing of a land. Land cover map is one of the most important information resources in natural resource management. The goal of this research is to provide Katalan land cover map for investigating land use changes during 12 years in this area.

For this purpose, satellite images such as Landsat ETM 2001 and OLI 2013 were used after performing necessary corrections whereas; GPS and topographic maps were implemented for surveying fields and gathering trained samples. Land cover maps were provided using supervised classification method with maximum likelihood algorithm.

The results of this study revealed that the study area comprises six classes viz. irrigated farm land, rainfed farm land, bare land, rock stone, range land and mine class. The overall accuracy and kappa coefficient for 2013 map were estimated 86.11% and 0.82, respectively and theses values for 2001 land use map were 78.26%, and 0.71, respectively.

The results of this research revealed that the class of farm land, bare land and range land were increased 1.84%, 1.29%, and 1.21%from 2001 to 2013, and the class of rock stone and rainfed farmland were decreased 5.09%, and 0 .62%, respectively. Also, there was not mine class in 2001 but this class was 1.36% equivalent to 49.3939 hectare of the whole area in 2013.

Today, there are two differences of opinion and approach review including the trend and intensity of land use change and land protection changes regarding the development of urban areas and the use of land, which explain the characteristics of the growth and expansion of cities and their environmental sustainability. The current trend of growth and development of urban and residential areas and the resulting regional changes have been proposed and introduced as one of the main challenges to define development strategies in urban areas.
Material and

 Today, achieving appropriate methods of measurement and evaluation and planning at all levels is supported by managers in urban areas. Although different factors such as location and natural, environmental, ecological, edaphic characteristics, social, cultural, economic and even political conditions are taken into consideration in the existing models and methods for land preparation and land allocation for different uses, it can be stated that in some of them, such as CLUE-S and AEZ models, only the change of land use, including agriculture, pasture and forest lands, has been considered. Now, the arguments about the planning of urban areas in relation to land allocation, research events in the field of land use in the form of principles and concepts of land planning have been more emphasized.

The present study aimed to model the allocation and zoning of urban land in the form of a case study in the city of Chadegan, located in Isfahan province, and also the modeling was performed using the integration of spatial modeling methods and multi-attribute decision making with balanced score card methods and clean production in the environment of geographic information systems.
Discussion and

The result of the research presented a descriptive model based on scoring 22 indicators related to 4 social, environmental, ecological and economic criteria or components. Thus, by identifying the features and attributes of each of the components and preparing thematic maps related to them based on the scores of each of the 22 indicators in the environment of geographic information systems, it is possible to allocate and zone urban lands in 4 situations including unfavorable, relatively favorable, favorable and highly favorable according to the type of users in urban areas.