Dynamic monitoring of ecological security patterns in arid zone oases: a remote sensing-based ecological index evolution analysis.

As vital biological hubs in delicate ecosystems, oasis in arid zones provide vital ecosystem services that include resource availability, biodiversity preservation, and temperature management. The quantitative contributions of human and climatic causes to the dynamics of eco-environmental quality are still not well understood, despite their importance. This study evaluates the evolution of EEQ in three dry irrigation oasis in China (Hetao, Ningxia, and Minqin) between 2000 and 2022 by utilizing Google Earth Engine to create a Remote Sensing Ecological Index that integrates multi-dimensional indicators. We determine that precipitation is the primary driver using Shapley additive explanations (SHAP) in conjunction with interpretable machine learning; the corresponding SHAP values are 0.031, 0.063, and 0.30. Critical thresholds that signaled a change from ecosystem suppression to enhancement appeared at 164 mm/yr for PRE and 1218 mm/yr for irrigation volume (IV). In terms of geography, 99% of RSEI values were in the medium-to-poor range, exhibiting varying patterns: stability in Minqin, improvement in Ningxia, and slight decline in Hetao. RSEI is positively impacted by ecological water replenishment, but urbanization and grassland degradation have negative impacts. A decision framework for ecological restoration project optimization is established by these threshold-driven insights, which are especially pertinent to attaining land degradation neutrality in drylands across the world.