research-focus Research Focus International Scientific Journal Research Focus 2181-3833 Ilm-fan va innovatsiyalar akademiyasi 10.66073/researchfocus.v5i4.2300 REL-A-013427 06.00.00 STUDY OF CLIMATE CHANGE BASED ON SATELLITE IMAGERY AND GOOGLE EARTH ENGINE (IN THE CONTEXT OF THE REPUBLIC OF KARAKALPAKSTAN) ИЗУЧЕНИЕ ИЗМЕНЕНИЯ КЛИМАТА НА ОСНОВЕ СПУТНИКОВЫХ СНИМКОВ И GOOGLE EARTH ENGINE (НА ПРИМЕРЕ РЕСПУБЛИКИ КАРАКАЛПАКСТАН) IQLIM O‘ZGARISHINI SUN‘IY YO‘LDOSH TASVIRLARI VA GOOGLE EARTH ENGINE ASOSIDA O‘RGANISH (QORAQALPOG‘ISTON RESPUBLIKASI MISOLIDA) Tileubergenovich Berdimbetov Timur PhD, Nukus State Technical University; Institute of Agriculture and Agrotechnologies of; Institute of Agriculture and Agrotechnologies of Karakalpakstan; First-year master‘s student, Nukus State Technical University Adilbaevna Kipshakbaeva Gauxar PhD, Nukus State Technical University; Institute of Agriculture and Agrotechnologies of; Institute of Agriculture and Agrotechnologies of Karakalpakstan; First-year master‘s student, Nukus State Technical University ulı Yerejepov Miyratdiyn Sharapatdiyn PhD, Nukus State Technical University; Institute of Agriculture and Agrotechnologies of; Institute of Agriculture and Agrotechnologies of Karakalpakstan; First-year master‘s student, Nukus State Technical University 05 05 2026 2026 5 4 39 43 https://creativecommons.org/licenses/by/4.0 This work is licensed under a Creative Commons Attribution 4.0 International License.

This study investigates the dynamics of climate change in the Republic of Karakalpakstan using multi-temporal satellite imagery and the Google Earth Engine (GEE) cloud platform. By integrating Landsat and MODIS datasets, Land Surface Temperature (LST) and the Normalized Difference Vegetation Index (NDVI) were analyzed to assess regional environmental shifts. The spatio-temporal analysis reveals a significant trend of rising surface temperatures coupled with a progressive decline in vegetation density, signaling intensified aridification and drought processes. These findings provide a robust empirical basis for environmental monitoring and the formulation of sustainable adaptation strategies in the Aral Sea region.

В данном исследовании изучается динамика изменения климата в Республике Каракалпакстан с использованием многовременных спутниковых снимков и облачной платформы Google Earth Engine (GEE). На основе интеграции данных Landsat и MODIS были проанализированы температура поверхности суши (LST) и нормализованный разностный вегетационный индекс (NDVI) для оценки региональных экологических изменений. Пространственно-временной анализ выявил значительный рост температуры поверхности и последовательное снижение плотности растительности, что свидетельствует об усилении процессов аридизации и засухи. Полученные результаты создают надёжную эмпирическую основу для экологического мониторинга и разработки устойчивых адаптационных стратегий в Приаралье.

Ushbu tadqiqot Qoraqalpog‘iston Respublikasida iqlim o‘zgarishi dinamikasini ko‘p vaqtli sun‘iy yo‘ldosh tasvirlari va Google Earth Engine (GEE) bulutli platformasi yordamida o‘rganadi. Landsat va MODIS ma‘lumotlari integratsiyasi asosida Yer sirt harorati (LST) va normallashtirilgan differensial vegetatsiya indeksi (NDVI) tahlil qilinib hududiy ekologik o‘zgarishlar baholandi. Makon-zamon tahlili yer sirt haroratining sezilarli oshishi va vegetatsiya zichligining izchil kamayishini ko‘rsatdi, bu esa aridlanish va qurg‘oqchilik jarayonlarining kuchayganini bildiradi. Olingan natijalar Orolbo‘yi hududida ekologik monitoringni olib borish hamda barqaror moslashuv strategiyalarini ishlab chiqish uchun mustahkam empirik asos yaratadi.

 climate change Karakalpakstan Google Earth Engine Land Surface Temperature (LST) NDVI Aral Sea desertification remote sensing изменение климата Каракалпакстан Google Earth Engine температура поверхности суши (LST) NDVI Аральское море опустынивание дистанционное зондирование iqlim o‘zgarishi Qoraqalpog‘iston Google Earth Engine Yer sirt harorati (LST) NDVI Orol dengizi cho‘llanish masofadan zondlash Hansen, M. C., et al. (2013). High-resolution global maps of 21st-century forest cover change. Science, 342(6160), 850–853. Jiménez-Muñoz, J. C., & Sobrino, J. A. (2010). A generalized single-channel method for retrieving land surface temperature. Remote Sensing of Environment, 114(3), 588–596. Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8(2), 127–150. Gorelick, N., et al. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202, 18–27. Hersbach, H., et al. (2020). The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730), 1999–2049.