Abstract
Wetlands on the Qinghai–Xizang Plateau are crucial for ecosystem services and ecological security but are increasingly threatened by climate change and human activities. Previous studies have typically treated wetlands as homogeneous entities and relied on coarse-resolution data, overlooking the distinct responses of water and vegetation-soil components. To address this gap, we proposed a remote sensing-based assessment framework based on a dual water-vegetation structure to evaluate wetland dynamics from 2018 to 2023. By integrating landscape patterns, ecological states, and ecological functions, we constructed Wetland Health Index (WHI) using parallel unsupervised autoencoders. Geodetector and GeoShapley were further applied to identify the driving factors and quantify their spatial effects. Results showed the WHI fluctuated around a mean value of 0.42 at a moderate level during study period, with water components consistently exhibiting higher health scores than vegetated areas. Geodetector identified precipitation and livestock grazing as the dominant natural and anthropogenic drivers, respectively. GeoShapley further revealed geographic location inherently partly shaped the baseline ecological status, while external driving factors exert spatially heterogeneous impacts across geographic zones. These findings provide a spatially explicit perspective on recent alpine wetland health dynamics and support spatially differentiated wetland conservation and management on the plateau.