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Using GIS And Remote Sensing in Assessing the Impact of Drought on Forest Cover Changes Around the Aral Sea

PAGE NO. - · Asiya Tureniyazova · Timur Berdimbetov (PhD, Head of Computer Engineering Department, Nukus State Technical University, Uzbekistan) · Karimullaeva Ayzada (PhD, Dean of Computer Science Faculty, Nukus State Technical University, Uzbekistan)

American Journal Of Applied Science And Technology · 05 · 445-453 · 2025

Аннотация

The Aral Sea region has experienced significant ecological changes due to prolonged droughts and unsustainable water use, resulting in the degradation of forest ecosystems. This study utilizes Geographic Information Systems (GIS) and remote sensing techniques to analyze the impact of drought on forest cover changes from 2000 to 2024. Using satellite imagery (Landsat and Sentinel-2) and climate indicators such as the Standardized Precipitation Index (SPI), temporal and spatial trends in vegetation health and forest loss were assessed. The findings reveal a strong correlation between increasing drought severity and the decline of forest cover, particularly in the Amu Darya delta and surrounding areas. The study underscores the importance of integrating high-resolution satellite monitoring with adaptive forest management strategies to mitigate the effects of environmental degradation in arid regions. Keywords: Aral Sea, drought, forest degradation, GIS, remote sensing, NDVI, SPI, vegetation monitoring, environmental change, climate impact.

Доказательный фрагмент

«The Aral Sea region has experienced significant ecological changes due to prolonged droughts and unsustainable water use, resulting in the degradation of forest ecosystems.»

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The Aral Sea region has experienced significant ecological changes due to prolonged droughts and unsustainable water use, resulting in the degradation of forest ecosystems. Полный текст публикации CiteX не хранит — доступ к первоисточнику открывается по DOI согласно лицензии издателя и выбранному плану.

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Узбекистан
Ключевые слова
Aral Sea, drought, forest degradation, GIS, remote sensing, NDVI, SPI, vegetation monitoring
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