Forest dynamics and afforestation efficacy in the south-western Aral Sea Basin: a multi-decadal satellite observation approach
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Abstract
This study analyzes the transformation of forest ecosystems in the Republic of Karakalpakstan during 2000-2024 using modern information technologies — remote sensing, geographic information systems (GIS), and artificial intelligence algorithms.
The study employs the Google Earth Engine (GEE) cloud platform, the Python programming language, QGIS, and ArcGIS Pro. Land cover classification was performed using the Random Forest algorithm on Landsat 7/8/9 and Sentinel-2 satellite imagery. Transfer matrix and intensity analysis methods were used to quantify forest-land cover transitions. Forecast maps for 2030–2040 were generated using the CA-Markov model.
Results show that tugai forests decreased by 32% and saxaul forests by 19% during 2000–2024, while saline areas expanded by 50%. Classification accuracy reached 91.3% (Kappa = 0.88). Under the BAU scenario, tugai forests are projected to decline by an additional 38% by 2040.
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