Journal of Spatial Analysis

One of the most important calamities that affect the arid and semi- arid regions and is taken into account as threatening factors for human- life and destroying the natural resources is desertification, so recognizing and forecasting this phenomenon is very important. Desertification is a complex phenomenon, which as environmental, socio-economical, and cultural impacts on natural resources. In recent years, the issues of desertification and desert growth have been stated as important debate on global, regional and national levels and extensive activities have been carried out to control and reduce the its consequences. Desertification is considered as the third important global challenge in the 21th century after two challenges of climate change and scarcity of fresh water. At present, desertification as a problem, involves many countries, especially developing countries and includes some processes that caused by natural factors as well as human incorrect activities. In the other word, Desertification is the ecological and biological reduction of land that maybe occur naturally or unnaturally. The desertification process influences the arid and semiarid regions essentially and decrease the lands efficiency with increment speeds. The study area is located in the east and south of Isfahan. This region has been faced to increasing rate of desertification, because of drought, vegetation removal, change of rangelands to dry farming lands, water and wind erosion and lack of proper land management over previous years. Hence, aim of this research is monitor and forecasting of desertification changes in the east and south of Isfahan during the period of (1986-2016). In this research, the Landsat satellite images used as studies base for studying region desertification. Therefore, at first, satellite images of the study area were extracted from United States geological survey(USGS)website during the period of (1986-2016) and data and satellite images of TM5, ETM+ 7 and LDCM8 sensors of Landsat satellite were used which include thermal and spectral bands. In this relation, for studying the desertification condition in the south and east region of Isfahan, the Landsat satellite images of 4, 7 and 8 during 5 periods of 1986, 1994, 2000, 2008 and 2016 have been utilized. After completing the information data base, first, the soil salinity(S1, S2 and S3) and vegetation NDVI indices exerted on the satellite images. According to Fuzzy ARTMAP method, the land use changes during the period of (1986-2016) recognized in the studied region. In the other word, the vegetation NDVI and soil salinity (S1, S2 and S3) indices have been utilized for identifying vegetation and the desert and salty regions. For preparing the region land use map, the Fuzzy ARTMAP supervised classification method have been utilized and 5 land uses(desert and salty lands, vegetation, city, arid and Gavkhouni) in the region were identified by TerrSet software. The changes calculation in region uses during 5 periods accomplished by LCM model. Also, the Markov chain and Cellular automata synthetic model have been utilized for changes forecasting. This research results indicated that the greatest changes during studied period belonged to vegetation. This volume of change had been during 1986- 1994 that indicate 1062 km2 desertification. In the other hand, the greatest intensity of increasing the salty and desert regions have been occurred during 1994-2000 which indicate 495 km2 increasing. The CA- Markov synthetic method have been utilized for forecasting the land uses changes trend, too. In this relation, for assessing the forecast accuracy, the Kappa coefficient have been utilized which indicate 78%. Finally, it has been specified that the greatest changes during 2016-2024 will be in vegetation which about 60% of region vegetation will disappear and arid lands will be replace them. The salty and desert lands will disappear about 1% of vegetation, 3.3% of arid land and less than 0.01% of city and Gavkhouni. During 2016-2024 about 32% of Gavkhouni lagoon area will disappear and arid lands will be replace them.

Assessment of the Probable Impacts of Land Use Changes on Water Quality in Shadeghan
Wetland Using Remot Senseing Data
 
In this research, the evaluation of possible effects of land use change on water quality in Shadegan wetland has been provided with the help of remote sensing data. The purpose of this research was to evaluate and compare user variations in 2000 and 2015 using Landsat satellite imagery (with ETM and OLI sensors) from the study area and processing them in the ERDAS software environment using the unstructured classification method during a period of 15 years old has been investigated. To determine the cause of the changes occurring in the wetland, the water quality of the wetland was evaluated through the help of modeling. Vegetation in the wetland has been rising rapidly, indicating water pollution, an increase in the nutritional status and the early disappearance of this international wetland. With the help of this article, it can be admitted that the development of agricultural lands around the shadegan wetland from 2000 to 2015had caused an increase in pollution in the region, according to available agricultural wastement containing  quantities of herbicides and pesticides which has led to an increase in the growth of algae in the wetland, which has led to an increase in temperature and eventually the death of wetlands and aquatic animals so after selecting images and assign them in 5 classes, the change wetland  maps were obtained during a 15 year various sources were used to determine the best regression model for determining water quality changes in the following, the images were placed in the models and their mean and standard deviation were obtained. The result of the research showed that the Landsat sensor shows the water quality well and can be used to determine the changes. The development of agricultural lands leads to an increase in the eutrophication phenomenon in the wetland and, in the end, reduces the quality of water indicators. In the end, causes quality loss of water.
Key words: Assessment, Land Use Changes, Water Quality, Shadeghan Wetland, Remot Senseing.