ASSESSMENT OF VEGETATION COVER DYNAMICS AND ECOSYSTEM DEGRADATION IN THE ARAL SEA REGION USING GIS AND SATELLITE DATA
Keywords:
Aral Sea region, Karakalpakstan, GIS, satellite data, NDVI, NDWI, ecosystem degradation, vegetation cover, environmental monitoring, land degradation.Abstract
This study assesses vegetation cover dynamics and ecosystem degradation in the Aral Sea region of the Republic of Karakalpakstan, Uzbekistan, during 2021–2025 using Geographic Information System (GIS) technologies and satellite remote sensing data. The main objective was to identify spatial and temporal changes in vegetation cover, map environmentally degraded areas, and identify zones with potential for ecological recovery. Landsat and Sentinel-2 satellite imagery were considered for the analysis, together with the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI). GIS-based thematic mapping and multi-year comparison were used to characterize changes in vegetation and surface-water conditions. NDVI provides an indicator of vegetation condition, while NDWI supports the assessment of water availability and surface moisture. The proposed approach is particularly relevant to the Aral Sea region, where water scarcity, soil salinization, climate variability, desertification, and anthropogenic pressure interact. The results and methodological framework can support environmental monitoring, sustainable land management, ecosystem restoration planning, and the identification of priority areas for ecological rehabilitation in the Aral Sea region.
References
1. Rouse, J. W., Haas, R. H., Schell, J. A., & Deering, D. W. (1974). Monitoring vegetation systems in the Great Plains with ERTS. Third Earth Resources Technology Satellite-1 Symposium, NASA.
2. Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8(2), 127–150.
3. Huete, A. R. (1988). A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, 25(3), 295–309.
4. Gao, B. C. (1996). NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58(3), 257–266.
5. Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202, 18–27.
6. Pettorelli, N., Laurance, W. F., O'Brien, T. G., et al. (2014). Satellite remote sensing for applied ecologists: opportunities and challenges. Journal of Applied Ecology, 51, 839–848.
7. Reynolds, J. F., Stafford Smith, D. M., Lambin, E. F., et al. (2007). Global desertification: Building a science for dryland development. Science, 316, 847–851.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Ideal Journal of Multidisciplinary Research

This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation.
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.






