https://topjournals.uz/index.php/jgnr/issue/feedJournal of Geography and Natural Resources2026-10-10T06:21:03+00:00Supportscience LLCinfo@topjournals.uzOpen Journal Systems<p><strong>SJIF 2021-5.899, 2022-6.037</strong></p> <p><strong>Journal of Geography and Natural Resources" </strong>is a journal specialized in geography, providing comprehensive and effective coverage of scientific and practical innovations in the field of geography, such as natural geography, socio-economic geography, soil science, mineral fertilizers. One of the most important tasks in the field of geography and natural resources is the publication of up-to-date, novel scientific research with verified results and information.</p> <p>This scientific journal is published in electronic version, 6 times in a year in Uzbek, English and Russian.</p> <p>The best scientific and journalistic works of authors, as well as foreign authors in the field of world geography, are published in the journal.</p> <p><strong> </strong></p>https://topjournals.uz/index.php/jgnr/article/view/508ASSESSMENT OF THE ECOLOGICAL STATUS OF GEOSYSTEMS IN THE SYRDARYA REGION USING GIS TECHNOLOGIES AND ARTIFICIAL INTELLIGENCE2026-10-10T06:21:03+00:00Mansur Egamberdiyevich Djurayev admin@topjournals.uzJahongir Husenovadmin@topjournals.uz<p>The article presents a methodology for the comprehensive assessment of the ecological status of geosystems in the Syrdarya Region using remote sensing, Geographic Information Systems (GIS), and machine learning methods. In the study, Sentinel-2 and Landsat 8/9 data, along with terrain, climate, and soil layers, are processed using Google Earth Engine and QGIS. The ecological status is assessed using the Remote Sensing-based Ecological Index (RSEI) and Analytic Hierarchy Process (AHP)-weighted indices based on vegetation cover, moisture, soil salinity, land surface temperature, and dryness indicators. Random Forest, XGBoost, and U-Net models are employed for classification and prediction, and their performance is evaluated using Overall Accuracy (OA), Kappa, F1-score, Root Mean Square Error (RMSE), and the coefficient of determination (R²).</p>2026-10-07T00:00:00+00:00Copyright (c) 2026 Mansur Egamberdiyevich Djurayev