جستجوی مقالات مرتبط با کلیدواژه « satellite images » در نشریات گروه « محیط زیست »

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.

Evapotranspiration is one of the most important elements of the hydrological cycle. Estimation of evapotranspiration is imperative for effective forest, irrigation, rangeland and water resources management as well as to increase yields and for better crop management. The aim of this study is to calibrate the SEBAL algorithm in estimating evapotranspiration in the Sohrin-Qaracheryan plain, which is affected by flood spreading. In this study, Landsat 8 satellite images were used in 2020-2021 to obtain the coefficients of the relevant bands. Then, the net radiation flux on the earth’s surface and the earth’s heat flux is obtained using incoming-outgoing radiation fluxes from albedo, surface emissivity, land surface temperature, and plant indicators. Next, the sensible heat flux is calculated by determining the hot and cold pixels. Finally, evapotranspiration maps are plotted. Based on the results of this research evapotranspiration obtained from soil water balance model and SEBAL algorithm were estimated as 24115 and 19642 m3, respectively. Also, the calibration of the results obtained from the SEBAL algorithm with reference evapotranspiration was done using R2 and RMSE statistical indices, and were calculated the values of these two indices as 0.64 and 2.15, respectively.

In the present time, land use changes are being conducted without clear and logical programming or regarding the environmental effects of the changes. Because land use changes occur in a large scale, remote sensing technique is a useful and valuable tool for monitoring the changes. The aim of this research is investigation of the effects of land cover changes on rangelands of Ghoorichay chatchment located in the north of Ardabil province using remote sensing technique.

In this investigation, TM images for year 1987, ETM images for year 2001 and OLI-TIRS images for year 2015 were collected and analyzed. After image pre-processing enhancements and corrections, the images were classified using maximum likelihood supervised classification method. Then, considering study area features, the images were classified into four land cover classes: dry land, range land, bare land and village. Moreover, NDVI index and slope layer were used to increase classification accuracy. At last, land cover changes and their effects on the range lands were detected. Overall accuracies and kappa coefficient were evaluated.

According to the results, during the studied period, 5885 hectare (49.7%) of study area had changed. The most land cover changes were related to range land with intensive decrease of 2540 hectares (21.4%) which was changed into bare land and dry land.

Additional information such as slope layer and NDVI index in assistant with supervised classification of satellite images can increase the accuracy of image classification to provide land cover maps.

Nowadays, monitoring the wetlands land-use change trends using satellite images is one of the most important tools for managing and conserving wetlands. The goal of this study was to investigate land cover change in Meighan wetland as a remarkable wintering wetland for water birds and waders in the middle of the country during 2008-2018 in order to evaluate the trend of the changes in this wetland and make managers prompt a proper decision for the effective management. In this study, images of the geo-referenced Landsat satellite, ETM+, OLI 8 TRIS were used and after applying necessary corrections on the images, results were analyzed in the ENVI 5.4 software. The results of the change detections indicated that the area of the wetland has decreased by 63.31% during the study period. Vegetation covers of the wetland diminished by 64%. During the study period, barren lands have increased by 11.6%. Also, the area of agricultural land in the border of the wetland has expanded by 23.15%. Besides, reviewing water birds and waders abundance in 2008 and 2018 showed that abundance of the most families of water birds and waders were higher in 2008. Taking the environmental importance of Meighan wetland into account as a place hosting large populations of water birds and waders, we recommend that management plans to survey and systematically control of this wetland should be implemented.

GharehGheshlagh wetland is one of the most important wetlands in Iran in terms of having a variety of plant and animal species especially birds. In recent years, agricultural development and land use change in this region has reduced water areas of this wetland. The present research was conducted due to the necessity of the assessment of the variations occurred during last years and forecasting the future status of this unique ecosystem in order to make decisions about the land use management. For this purpose, Landsat 8 satellite images were used as a reliable tool to investigate the trend of changes. In this regard, the images provided in three different years were classified to cover two periods of 12-year and 15-year using Support Vector Machine and Random Forest models. Then, considering the existence of land uses including barren landscapes, saline fields, water areas, and also vegetation and agriculture in the region of GharehGheshlagh wetland, their changes were evaluated. The results represented the immethodical development in agriculture area over a 15-year period from 2001 to 2015. The land use changes had a negative impact on the wetland water areas and it had caused remarkable reduction in the water level of the wetland, which necessitates for agricultural management and prevention of its future development in the region of the wetland can be mentioned as the most important result of the present study.

Rapid urbanization and constructions are considered as the main cause of many environmental problems on the earth, especially in urban areas. Todays, functional and structural roles of green spaces have been emphasized further in improvement of urban ecosystem. As green space is one of the most important classes of land use in urban ecosystem, studying its changes is an important step in order to improve human-dominant ecosystems.

In this study, remote sensing and geographical information system were used in order to investigate spatio-temporal changes of urban green space in Ardabil city. To achieve the mentioned purpose, Landsat satellite images including TM-1987, ETM+-2000 and OLI- 2014 were used.

Results indicate that green spaces in Ardabil city have intensely decreased during the investigated time and in the during past 27 years about 1507 hectares of the green spaces of this region have been constructed and only 8 per cent of the city is covered by green space.

Results show intensive changes in spatio-temporal green space pattern in Ardabil city. In order to prevent further destruction and elimination of urban green spaces, along with improving it in Ardabil City, the existent policies should be revised.

Reviewing the Function of many environmental conservation organizations over the past decades, including in Iran, shows that the focus of environmental orientations and policies, due to the lack of accurate and reliable information, is more dependent on the application of instructions and guidance methods, and less Quantitative management approaches are used. Therefore, this study is aimed at modeling the process of land use changes in the last thirty years (1987-2018) and predicting the future status in case of continuation of the current trend and using improper management patterns. For this purpose, the InVEST software is used to analyze the present situation and to draw future conditions. The results in map form provide a good opportunity for managers and decision-makers to infer trends in future changes and modify management patterns to improve conditions. 

In this study, satellite images of Landsat 5, 7 and 8 According to years 1987, 2000 and 2018, were used for land use mapping in Jajrood protected area through extraction in ENVI 5.3 remote sensing software and ArcGIS 10.3 software. The accuracy of the classifications has been evaluated. According to the purpose of the study the area of study is divided into 10 user units. These units include poor rangelands, rich rangelands, planted forests, agricultural lands, barren lands, dam, residential areas, rivers, dirt and paved roads and the status and area of each user unit was determined.Finally, the scenario generator model of the InVEST software version 3.6.0., which uses a completely new approach to quantify and map, was applied in mapping the status of the future.  

According to the results of the past 30 years, the extent of residential areas, roads and planted forests has increased, and the extent of river distribution has decreased, as a result poor rangelands increased and rich rangelands decreased as well as changes in barren lands was clearly visible. So that, the extent of the barren lands has declined by the year 2000 due to the conversion  to man-made use  (near residential areas) and poor rangelands (due to favorable weather conditions, including suitable rainfall). The situation in the Barren areas during the period ending in 2018 has increased due to the bad weather (drought) and the irregular grazing of livestock and the conversion of poor rangelands into the Barren areas. The agricultural lands have increased over a period of time due to its proximity to residential areas and then a downward trend has taken place due to increasing land value. In recent years, the Mamlou Dam has also been constructed and operated in the area. In fact, because of Jajrood's proximity to large city of Tehran and the increasing population, the need for ecosystem services in the area has increased, and man-made uses being replaced natural land uses.Future forecasts showed that the extent of planted forests, barren and residential areas would increase; rangelands and agricultural lands would decrease. During the study period, rich rangelands marked as the most reduced area and residential areas marked as the most increased area.

The Jajrood Protected Area has undergone significant land use changes over the past 30 years due to human intervention. These changes have been caused by economic and social changes. It has been accompanied by management challenges in adherence to safeguards and efforts to achieve the defined goals for such areas. The changes of natural land use and the replacement of man-made use in the face of unnecessary development have undermined the natural landscape of the Jajrood Protected Area. This study showed that changes in multiple ecosystem services will act as major drivers of human change through changes in land cover / land use.In addition to identifying land use change, identifying suitable areas for natural capital conservation, man-made use development and sustainable land use, spatial development planning can be carried out in a way that reduces future uncertainties. It will result in making informed decisions and foster synergies in both environmental and development sectors.

Numerous studies have been carried out on climate change and weather change. Some of these studies include the study of surface water resources. Because these water resources are, on the one hand, highly affected by climate change, they also affect the Peripheral environment and the Environment. Most of the studies in this field are based on the data of meteorological stations, hydrometer stations and different satellite images. Landsat satellite imagery is well suited for studying for decades, due to its relatively old age. The purpose of the present study is to study the changes of Namak (salt) Lake and Hoz-e Soltan Salt Lake using quantitative and qualitative meteorological data of ground stations and Landsat satellite images.

First, using the available climatic parameters, the period and time steps of the study were determined. These parameters included mean temperature, maximum and minimum temperature, rainfall, relative humidity, evaporation and so on which were measured at three stations of Qom province including Qom, Salafchegan and Kahak stations. This was done by routing and examining climate change and climatic mutations in each of these parameters. In such a way, by using graphical representation and appropriate statistical test, unusual changes were extracted and that special year were excluded. Next, images of Landsat satellites were taken at selected times in the previous step. These images were pre-processed, processed and post-processed. Classification indices of four classes of water, salt land, common soil land and vegetation were applied and localized in Qom province.

Based on the study of changes in climate parameters, inappropriate years eliminated and study times from 1989 to 2019 with 5-year time steps were selected. Images of these times were classified for the Namak Lake, Hoz-e Soltan Salt Lake and their surrounding environment using the Support Vector Machine (SVM) method in ENVI software. This classification was applied to the images every seven steps and yielded the area of each class of water, salty soil, common soil, and vegetation. The results of classification were controlled by the visual method and a number of ground samples. Next, the class changes were modeled and calculated. The rate of change of each class and its conversion into other three classes were calculated between the time steps and its results were presented as a change matrix. The change matrix was expressed as a percentage of change and as a change in metric units (square meters). On this basis, it was possible to survey the major changes of each class and study it.

In general, the trend of climatic parameters and the water zones of Qom province changes have been similar. During the study period for the Hoz-e Soltan wetland basin, the mid-study period of about 2004 with a surface area of 61667 hectares can be considered the driest year in the period of study. In the case of the Namak Lake, the years 2004 to 2014 are also the driest years. 2009 is the driest year in the study area, with an area of about 281 hectares. Investigating these changes by identifying the basin of both water resources and their differences will provide valuable information to researchers.

Studying the extent of change and destruction in resources in previous can contribute to efficient planning and utilization of these resources and limiting similar adverse changes in the future. Since changes in resources occur over large expanses of land, remote sensing technology can serve as a essential and valuable tool for monitoring these changes. The purpose of this study was to monitor the land cover changes in Qaresu watershed in Ardabil province using the remote sensing technique.

In this study land cover changes was consulted in 30 years from 1985 to 2015. Landsat images of the study area pertaining to July 1985, 2000 and 2015 were acquired. After geometric and elevation corrections, the images were classified by the supervised approach using the maximum likelihood method. The NDVI index, DEM, and slope layers were used to enhance the image classification accuracy. Classification accuracy was assessed with Kappa index and overall accuracy indexes.

The results showed 20.43% change in the watershed’s land uses over the period from 1985 to 2000, 41.426% over the period from 2000 to 2015, and 27.99% over the period from 1985 to 2015. In all three periods, the greatest changes were in dry farming.

Results showed despite high capability of Landsat images in mapping land use, using additional layers like NDVI, elevation and slope percent can improve separation accuracy of land using.

Investigating and understanding the impact of dust storms on wetland vegetation changes can lead to useful information for their optimal management. In this study, the wind rose and hurricane rose diagrams of the research area were prepared using wind statistics of Ahvaz meteorological stations. Changes in vegetation cover of Shadegan wetland were determined using classified soil-adjusted vegetation index (SAVI) maps of MODIS satellite images from 2002 to 2011 and correlations of vegetation changes were analyzed using dust storms data of Ahvaz meteorological station. The results showed that the major winds in the region flow from northwest to west and have the ability to create dust. The trend of changes of the number of stormy days, the concentration of dust and vegetation, were proportional to each other. The correlation between the number of dust days per year and the percentage of area with good vegetation cover showed relatively good relationship (the coefficient of determination was 0.47). The correlation between total dust concentration and vegetation cover, with a coefficient of determination of 0.58, indicated the high effect of dust on vegetation cover in the study area. The trend of changes in dust concentration with vegetation index was decreasing in one, two, three, four, and five months before image date. The relationship between dust concentration one month ago and vegetation percentage (SAVI index) with a coefficient of 0.99 showed the highest correlation. The negative and significant effect of dust storms on vegetation doubles the importance of the issue in Shadegan International Wetland, and on the other hand, the use of satellite images can provide accurate information with less cost and time to manage vegetation water and soil resources for managers.

Rey city has experienced unprecedented urban growth in recent decades that leading to drastic changes in the land use of the region. Therefore, the purpose of this article was to investigate the changes in land use area of Rey city during the years 1988 to 2006 using aerial photographs and satellite images of Landsat and IRS. With supervised and unsupervised classification of the satellite images, 4 land uses types including urban lands, agricultural lands, green spaces and barren lands were extracted. Land use layers were compared in pairs and the rate of land use changes was extracted. The results showed that urban land use made and urban green space have increased 369.7 and 55.6 hectares, respectively, and agricultural lands and barren lands have decreased 213.8 and 211.5 hectares, respectively. The growth of residential areas during a period of 6 years from 2000 to 2006 totally with 212.7 hectares has been faster changed than a period of 12 years from 1988 to 2000 with 157 hectares. A pairwise comparison matrix of land uses was used to determine the amount of environmental damages caused by unprincipled changes in the region land uses in the studying period. The results show that the conversion of barren lands, agriculture and urban green space into residential lands with the amounts 44.65, 42.44 and 14.85 causes high degree of environmental damages. Land use change, especially the loss of vegetation, has a negative impact on the landscape.

Following the rapid economic and social development in recent decades, human activity to use natural resources has been reflected in the form of infrastructure and agricultural activities. This has severely affected forests as an important ecosystem which are considered potential environmental resources for future evolution. The purpose of this study is to detect changes of Guilan province forest levels during a period of 20 years (1996-2016), also modeling and predict these changes for the next 15 years using the geomod model. Landsat TM and OLI sensor images were used to prepare land use maps for 1996, 2006, and 2016 periods. Satellite images were classified into forest and non-forest classes using the maximum likelihood method and multiple educational samples. The geomod model was simulated based on the changes made in the period 1996-2006, changes in forest cover using the variables of height, slope, direction, distance from residential, distance from a road, distance from forest, with implementation for 2016. The predicted validation results of the forest cover map in 2016 is indicator the overall accuracy and value of the kappa index equal to 94.19% and 0.9159, respectively. Based on the results of detecting changes during the study period (1996-2016), 1054.97 hectares of forest area in Guilan province has been reduced and with the continuation of this trend and stable conditions in the next 15 years until 2031, another 871 hectares will be reduced from its level. Given the importance role of Hyrcanian forests, it is necessary to conduct multi-time studies to monitor and detect changes. Obviously, the information from such studies can be used in managerial and strategic planning.

Nowadays, the urban sprawl phenomenon has become one of the most important concerns of planners and policymakers. The lack of attention to this phenomenon has led to irreparable consequences such as threatening natural resources, and social, economic, physical, and environmental constraints and disadvantages. In order to better understand such a model, it is necessary to evaluate and identify the socioeconomic factors affecting it.

  the methodology in this research was a combination of descriptive and explanatory research, the type of research was applied, and its approach was considered quantitative and qualitative. Data collection was done using library and field survey methods. Also, remote sensing and Landsat satellite images of the studied area during the mentioned period was used. In addition, to analyze Zanjan’s urban sprawl, the method of classified classification, land use classification and cross-feasibility model, the extent of changes in different land uses, and the Holdern model were used. In order to predict the trend of changes and to investigate possible changes in land uses for the 2026 horizon, the Markov chains model was used.  

In the studied area, the results of the research indicated that over the past three decades, with uneven development in Zanjan City, the urban area has almost tripled. Theoretical analysis of Zanjan’s urban sprawl according to Heldern model indicated significant urban sprawl domination in the physical development of Zanjan, which always had more effect than the population growth. During the studied years, Zanjan’s urban area had a multiplier increase that in contrast to this expansion, had a significant decrease in orchards and agriculture. In this situation, what made a big difference were the changes in orchard and agricultural land uses. Translation errorThere were many factors involved in this matter, most notably the growth of urban population and urban sprawl.    

Based on the forecast for 2026, the probability of land use changes to the city over the next 10 years is significant, during which Translation errorthe amount of built-up areas in Zanjan will reach 6311.88 hectares. It should be noted that orchards and Translation erroraaaagricultural lands have only a 23.56% possibility of conversion to urban areas. Therefore, necessary actions are required to prevent over-urbanization. In developed countries, considering the importance of sustainable development, environmental protection and the efficient use of various sources, smart growth, and urban development are highly important. Moreover, preventing the excessive growth of the city's boundaries, the high-ranking agenda, and the use of the compact city pattern, as well as the direction of the expansion of the city towards regolith and abandoned lands with the aim of preventing constructions in agricultural land can be considered.

Given the importance of soil and water resources in the development of sustainable agriculture, increasing world population and the growing need for crop production, predicting crop yields using plant simulation models and remote sensing technology is very crucial. The aim of this study was to estimate the yield of rice components including straw, paddy and biomass of Hashemi cultivar during different growth stages with SWAP model and to provide regression equations by extracting NDVI and SAVI plant indices from Sentinel-2 and Landsat-7 and 8 satellite images. It was done in the National Rice Research Institute. Comparison of statistical variables indicated that the mean values of coefficient of determination (R2) and model efficiency factor (EF) in estimating the yield of rice components in different stages of growth with SWAP model were more than 0.70 and 0.90, respectively, and with an error of 1.93 to 6.54% was equivalent to 134.21 to 470.43 kg/ha. The slight difference between the measured and simulated values showed that the SWAP model estimates the rice yield in the study area with appropriate accuracy. The results also showed that the extracted NDVI and SAVI indices with very good accuracy estimate the yield of rice components at different stages of growth. However, the highest amount of correlation was related to the reproductive development stage. Finally, R2 for NDVI at different growth stages as well as  the entire growth period for straw, paddy, and biomass were higher than the SAVI index, revealing more accuracy of NDVI than SAVI.

Study of resources changes and destruction in previous can be useful in the planning and optimal use of resources to control inappropriate changes. Because of land use changes occur on large-scale, remote sensing techniques is a useful and valuable tool for monitoring the changes. The aim of this research is to monitoring of land cover changes in Khojin watershed located in the south of Ardabil province using remote sensing technique.

First TM, ETM+ and OLI images for the year 1986, 2001 and 2016 were collected respectively and after geometric and elevation corrections, images were classified using maximum likelihood classification method. To increase classification accuracy, NDVI, elevation and slope percent layers were used. Kappa and overall accuracy indexes were used to calculate classified images accuracy.

Based on results, in the first period (1986-2001) 22.36%, in the second period (2001-2016) 20.73% and in the third period (1986-2016) 28.08% of area has changed and in all 3 periods, changing from rangeland to dry farming reached the most change.

Results showed despite high capability of Landsat images in mapping land use, using additional layers like NDVI, elevation and slope percent can improve classification accuracy of classified images.

Human activities such as agriculture and urban development (particularly settlement expansion and road construction) as well as biological and environmental processes, structure and pattern of the landscape. The aim of this study was to investigate the effects of land use changes on the landscape pattern of Malayer in the twenty years term. In this research, Landsat satellite imagery of 1997, 2007 and 2017, and the RS for producing land use maps and FRAGSTATS software were used to calculating and quantify Landscape metrics.The metrics used include CA, MPS, LSI, LPI, NP and IJI. The results showed that from 1997 to 2017 the area of residential use and water resources decreased and the area of agricultural use and bayer lands increased. So that increased of the residential use of 75373.11 hectares with an area of 14675.04 and water resources with an area of 23918.31 hectares with a total area of 248.76, the water resources of this city have decreased by 32/58 percent over the course of twenty years, and the Bayer lands from 66717150 in 1997 to 1820,86 in 2017, and agricultural use has increased from 13,30029 to 38388 in area. Also, decreased NP, LSI, and IJI in whole landscape.

In general, analysis of the area changes of wetlands and its relationship with changes in surface runoff of catchments can play an important role in the efficiency and success of adaptation programs with climate change and conservation and development of wetlands. Therefore, in this study, changes in the areas of Kaftar wetland of Fars province and its relationship with the change of runoff in catchment were investigated. To this end, satellite images and rainfall data during a 30 year period (1986-2016) and were used and by providing time series of changes of the areas of wetland and runoff values of catchments, the relationship between these two variables were investigated by linear regression method. The results showed that with decreasing rainfall and increasing runoff coefficient and subsequently reducing the amount of runoff in the catchment, the area of wetland was decreased post-1998 relative to pre-1998 so that at the end of the 30-year period it has reached zero. Correspondence between reduction of wetland area and runoff of catchment caused correlation coefficient between these two variables was equal to 0.91. Finally, it can be said that the results of this research by providing accurate information about wetland responses to climate change and human activities play an important role in the efficiency and success of Climate change mitigation programs and the conservation planning of wetlands in Iran.

  Principal land use management requires accurate and timely information in the form of maps. Considering the widespread and unsustainable changes in land use, including the destruction of natural resources in recent years, it is essential to study the changes in land covers over the time using satellite imagery. Because the conservation of natural resources requires continuous monitoring of an area, land-use change models are now used to identify and predict land-change trends and land degradation. One of the most widely used models in predicting land use change is the automated Markov chain model. The purpose of this study is to monitor land use changes in Abu Ghovair Plain in the past years and predict their status in the next 13 years. Material and In this study, in order to detect the changes in the study, TM, ETM+, and OLI images of Landsat satellite were used in the years 1990, 2003 and 2016, respectively. After applying geometric and atmospheric corrections to images, the land use map was created for each year. Then, to predict the changes in 2029 using the Markov chain in the Idrisi Selva software, the mapping of the years 1990 and 2003 were selected as the input to the model. Then, 13 years of forecasting changes were considered until 2016 to get the matrix of the likelihood of user changes. Then, data from the Markov chain method and the map of 2016 were used as input data for the CA-Markov cell method. The results of monitoring satellite images from 1969 to 2016 indicated a gradual increase in sandy areas by 62 km2 and its movement towards poor rangelands and shrubs. The agricultural lands were increased so that at the end of the period their size has increased by 67.68 km2. Residential land has also been expanded over the years, and the size of the shrubland has been reduced. After tracking the changes, the 2016 map was simulated by the model. Evaluating the accordance between the simulated map and the actual map with the Kappa index confirmed the accuracy of the model. Then, the 2029 map was prepared to predict the changes over the coming years. The discovery of changes in 2029 indicated that if the current trend continues, the area of the sand zones will increase to the extent of covering 15% of the area. In this period, the most changes will occur in the middle part of the southeast to the south of the area. The size of the shrubland will decrease by 13 km. The changes in agricultural lands continue to grow and will encompass 10% of the whole region in 2029. Comparison between the simulated map of 2016 generated by the model and actual map with Kappa index showed that Auto-Markov model is a suitable model for predicting land use change and can be used to accurately assess the future status of land use and vegetation.

Land use has always been one of the most important indications of the adverse impact of mankind on their environment. It is an activity that human beings, through using natural resources, contribute to their socio-economic development and at the same time, alter the processes and structures within the environment. One of the most important sources that have been damaged during the past decades through land use change is water resources, especially groundwater. Considering the importance of groundwater resources in supplying drinking water and agriculture, qualitative monitoring and spatial and temporal distribution of the process of its changes are important issues in planning and managing water resources. Therefore, the present research investigates the effects of changing the use of groundwater quality in Kerman Plain. Material and Land maps of Landsat 5, 7 and 8 were used for land use mapping in Kerman Plain. These are TM (1987), ETM + (2002) and OLI (2017) sensors, respectively. Also, in order to investigate the process of qualitative changes of groundwater resources in Kerman Plain, statistical data and information of 2002 and 2017 were used. Then, the maps of quality parameters were mapped to the ArcGIS 9.3 environment. Afterward, these maps were zoned to agricultural classes using Wilcox classification and the critical and contaminated areas were identified. . Spatial zonation maps of groundwater parameters for agricultural purposes were plotted based on Wilcox method. Finally, by coating the SAR and EC layers with ArcGIS9.3 software, the water quality status of the region for agricultural use according to Wilcox classification in 1996 and 2014 the area of each group was calculated. Using satellite images of the studied area, it was divided into three user units. These units included residential areas, agricultural lands, and rangelands. The quality of agricultural water was obtained from a diagram called the Wilcox Diagram. Land use change showed that a decrease has occurred in the pasture user's class. In the course of 30 years, while 1.691 km2 of rangelands have been decreased, the area of agricultural land and residential areas has been increased. The increase was far more in residential areas than agricultural lands. According to the Wilcox classification, the EC and SAR parameters were increased during this period, but the trend of increase in the EC parameter was higher. For the EC parameter, almost the majority of the region had a high level of this element, which is more intense in the western parts of the region than in other regions and has been increasing over time. For the SAR element, studies have shown that the amount of this element was in the good class in all areas of the region in 2002, except for the western parts of the study area which were in the middle class in 2014.

Constructed Earth dams in the watersheds of Ramhormoz and Shadegan have two destructive roles: First, they create new sources of dust production in the dry years, the second; they will activate the sources of dust production of the south and southern parts of Ahwaz by preventing the flow of seasonal flows, in wet years. In this study, regarding to the distribution of hydrological network, the study areas in which earth dams were constructed on the seasonal streams leading to the southern and southeast of the dust resources of Ahvaz, were identified and selected. In order to investigate the effects of Earth dams on the water flow of the rivers, long-term statistic data of the hydrometric and rain gauge stations which are located in Ramhormoz watershed were used. For this purpose, linear trend, slope of variation, significant and change points of climatic and hydrologic parameters of precipitation and flow rate were investigated using Mann- Kendall graphical method. Due to the lack of access to the information in the Shadegan study area, the location of the Earth Dams on the seasonal streams of the northeast of the dust resources was identified through Google Earth and the year of their construction was achieved through the study of Landsat satellite imagery in January. Due to the large number and small sized Earth Dams, variation in their surface water levels were estimated using visual interpretation of 5, 7, and 8 Landsat satellite imagery, and analyzed using Arc GIS software In the study area, based on the drought index, the years of drought and wet were identified and the results showed that the linear trend of time series of the flow rate and rainfall has been decreased both, however, the slope of decreasing trend in the time series of the flow rate has been more and significant. In addition, the results of the study showed that some of the earth dams, especially in Ramhormoz area, were destructed and filled with the sediment and, in other sections, the variation in the level of water collected behind them follow the drought and wet conditions so that the area of the water zone in January 2016 as a wet year, in 21 Earth Dams in the northeast of the dust resources was approximately 21 hectares and, in January 2017, as a dry year, was approximately 21 hectares, which can be a good potential for controlling the dust in this resources. The relationship between the frequency of dust events with the internal origin and the cumulative frequency of constructed Earth Dam showed that the increasing the number of Earth Dams in these two areas could be one of the factors affecting the activation of dust resources in southwest of Ahwaz.