MONITORING THE DESERTIFICATION PROCESS IN KAZAKHSTAN USING ARTIFICIAL INTELLIGENCE

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Authors: M.N. Musabaeva, G.B. Abiyeva, Sharbet Mussabayeva, Daiana T.
Cited by: 0
References: 2

Abstract

Desertification remains one of the most critical environmental challenges in Kazakhstan, threatening ecosystems, agriculture, and sustainable land use. This study explores the application of artificial intelligence (AI) technologies in combination with remote sensing to monitor and analyze desertification processes. Using the Google Earth Engine (GEE) platform, satellite images from Landsat and Sentinel missions were processed to identify changes in vegetation cover and soil condition. The study applies AI algorithms to classify land areas, detect patterns of degradation, and assess their spatial extent. Artificial intelligence makes it possible to automate image interpretation, improve accuracy, and accelerate data analysis. The integration of AI with satellite monitoring provides a reliable and cost-effective approach to identifying regions most at risk of land degradation. The findings of this research demonstrate the potential of AI tools for long-term ecological monitoring, helping to create an effective decision-making system for land management and environmental protection. This approach contributes to developing sustainable land-use policies and supports Kazakhstan’s efforts to mitigate the impact of climate change and desertification.

Fields of Study & Subjects

Remote-Sensing Image Classification Remote Sensing in Agriculture Remote Sensing and Land Use

Publication details

Journal / source
Geography and Sustainable Development
Volume
1
Issue
1
Pages
49–56
Publication date
12 January 2026