Spatiotemporal dynamics and drivers of ecological quality in Shaanxi (Yellow River Basin, China) based on optimized RSEI and SHAP

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Authors: Chan Ma, Chi Zhang, Hongqiang Chen, Ming Ma, Siyu Wang
Cited by: 2
References: 42

Abstract

The Yellow River Basin serves as a crucial ecological barrier in China, necessitating an understanding of its ecological quality dynamics and drivers. Utilizing Moderate Resolution Imaging Spectroradiometer (MODIS) data (2000–2023), we developed an enhanced Remote Sensing Ecological Index (RSEI) for the Shaanxi section of the Yellow River Basin by applying the entropy weight method (EWM). Spatiotemporal variations were assessed using Sen’s slope and the Mann–Kendall (MK) test (Sen–MK) and the Hurst exponent (H), while driving forces were interpreted using SHapley Additive exPlanations (SHAP). The mean RSEI was 0.51, indicating ecological quality above medium with a slight upward trend. Improvement was predominant, following a “south-high, north-low” pattern; slightly and significantly improved areas comprised 45.05% and 11.17%, while significant degradation covered 6.20%. Hurst analysis showed 56.96% of areas had significant increases, with 56.64% likely to improve further. Land use changes and natural factors jointly influenced RSEI, with cropland/grassland conversion to forest enhancing ecological quality. Soil moisture emerged as the dominant climatic factor, while interactions among wind speed, precipitation, and SOIL moisture bolstered ecosystem stability. These findings offer a scientific basis for ecological management and sustainable development in the Shaanxi section of the Yellow River Basin.

Fields of Study & Subjects

Remote Sensing in Agriculture Soil Geostatistics and Mapping Soil Moisture and Remote Sensing

Publication details

Journal / source
Frontiers in Environmental Science
Publisher
Frontiers Media SA
Volume
14
Publication date
9 February 2026
Language
EN