Soil salinity is a major concern in the Uzbekistan. Fergana valleys agricultural lands, it negatively affects plant growth, crop yields, whereas in central part of the valley is semi-desert and desert affects agricultural areas due to subsidence, corrosion and ground water quality, leading to further soil erosion and land degradation. Traditional soil salinity assessments have been doing by collecting of soil samples and laboratory analyzing of collected samples for determining totally dissolved soils (TDS) and electro conductivity, but, Geo-informatic systems (GIS) and Remote Sensing (RS) technologies provides more efficient, economic and rapid tools and techniques for soil salinity assessment and soil salinity mapping. Main goals of this research are to map soil salinity of Fergana valley, to show relation of its result with traditional analysing and analysing withGIS technology As a source of satellite images has been used Landsat-8 OLI. Research areas every arable land validity point of different locations were measured by Traditional soil salinity assessments by Soil composition and Repository, Quality analysis center was compared to our research conducted on satellite sensor and it can be said that the study have done correctly.

The Aral Sea was the fourth largest inland lake on the globe until 1960, with a surface area of about 68,000 km2. Mainly, the huge irrigation projects in many parts of its transboundary catchment were responsible for the catastrophic desiccation and ecological crises of the Aral Sea after second part of 20th century. Ecological crisis surrounding the Aral Sea (lake) regions is one of the critical environmental problems of Central Asia. As a result, monitoring of desertification processes and determining the aerosol concentration in the atmosphere are highly relevant for any attempts to mitigate environmental changes in the Aral Sea basin. Remote sensing is the most appropriate method for studying desertification and dust storms as it easily covers large areas with a high spatial and temporal resolution. Satellite images provide detailed multispectral information about the earth’s surface features, which proves invaluable for the characterization of vegetation, soil, water, and landforms at different scales. Vegetation cover, biomass, and soil properties were analyzed with remote sensing methods (NDVI, SDVI). It is emphasized that vegetation indices have little sensitivity at low leaf area which is common to all desert ecosystems.

Analysis of lithodynamic flows and soil-reclamation studies, based on the plastic relief map, allowed for a systematic analysis of the main components of the natural environment. The ways of migration of chemical elements in the soil are established. For the first time, causal relationships of spatial differentiation of the degree and chemical composition of saline soils in the Zarafshan river valley were revealed. The Zarafshan river basin has a clearly defined border, as we can judge from the map of plastic relief made up in 1: 100 000 scale. Here three cascade systems are well distinguished, which is very important for the formation of the reclamation state of the territory. In this area, that is, the subsystem, on the proluvial-alluvial deposits is the main volume of groundwater, which is closely related to the surface. This subsystem is part of the catchment area of the Zarafshan river basin, which is the main source of removal from the territory of a huge mass of dissolved and solid substances.

Land use and land cover (LULC) change are one of the most important signals of regional environmental monitoring and study. Recently, the pull of capital cities has snowballed, an increasing number of people moving to the cities, especially in developing countries. Consequently, as more people arrive at cities, the more pressure will be on land. Land price getting high and constructions try using open green areas. A wide variety of green areas of different sizes will be solve many urban diseases and ecological problems at the same time improve the quality and life of urban residents, as urban green area provides various ecosystem services. The green area includes parks, woodlands, nature reserves and bare lands. With the population increase and expansion of cities, an increasing amount of open area, woodland and bare land has been converted into construction land, buildings due to the increasing demands and residential land. For the accuracy assessment, we applied an automatically supervised classification using the software QGIS 3.18. The reference values were based on ground truth data and visual interpretation.