GIS-Based Integration of Landsat-Derived Indicators for Environmental Assessment of the Shurtan Gas Field, Uzbekistan

Abstract

Arid hydrocarbon landscapes are challenging to assess because surface temperatures, sparse vegetation, and exposed soils may reflect natural dryland conditions and local surface modification. This study applied a reproducible, sensitivity-tested Landsat-based framework to characterize surface environmental conditions within and around the Shurtan gas field, Uzbekistan, during 2014–2025. Annual June–September composites were generated from 484 Landsat 8 and Landsat 9 Collection 2 Level-2 scenes in Google Earth Engine (GEE). Land-surface temperature (LST), the Modified Soil Adjusted Vegetation Index (MSAVI), and the Bare Soil Index (BSI) were normalized and integrated into the Surface Environmental Condition Index (SECI), a relative composite in which higher values indicate warmer surfaces, lower soil-adjusted vegetation signal, and stronger bare-surface expression. Indicator weights were derived using the CRiteria Importance Through Intercriteria Correlation (CRITIC) method. Patterns were evaluated through zon