摘要：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.
其他摘要：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.
其他关键词：Aral Sea ; Water shrinkage ; Land-Cover ; Remote Sensing ; GIS ; Central Asia ; NDVI
