Four-Decade Evolution of Ecological Quality in the Ji River Basin (1986–2024): A Remote Sensing Ecological Index (RSEI) Perspective

Long-term ecological monitoring is essential for sustainable management in fragile regions. This study assessed four decades (1986–2024) of ecological evolution in the Ji River Basin—a transitional loess-gully ecosystem in China's Yellow River Basin—using the Remote Sensing Ecological Index (RSEI). We integrated multi-temporal Landsat images via Google Earth Engine to construct a 40-year RSEI time series, coupling greenness (NDVI), wetness (WET), heat (LST), and dryness (NDBSI) through principal component analysis (PC1 explained >82% variance). Three evolutionary phases emerged: initial degradation (1986–1996) driven by slope cropland expansion; stabilization (1996–2006) coinciding with early Grain for Green policies; and sustained recovery (2006–2024) as high-quality zones expanded 85%. Resilience mapping delineated three functional zones: High-Resilience refugia (16.84%) in highlands with stable RSEI (CV<0.15), Low-Resilience corridors (3.37%) showing chronic degradation, and Moderate-Resilience matrix (79.80%) exhibiting conditional recovery. Mann-Kendall analysis identified relief amplitude (RA>300m) and restoration projects as primary post-2006 drivers, while urbanization constrained lowland recovery. This study demonstrates RSEI's effectiveness for monitoring transitional loess ecosystems and provides a replicable framework for sustainable basin management, contributing to SDG 15 implementation in semi-arid regions globally.