The Indochina Peninsula (ICP) is a hydrologically diverse and climate-sensitive region, where human activities and climate change are reshaping local surface-water patterns, challenging sustainable and transboundary management. To achieve high-precision, long-term surface water monitoring across the cloud-prone ICP, this study develops an AI-assisted framework that integrates Landsat-8 and Sentinel-2 optical imagery on the GEE. The framework generated seasonal 10 m resolution surface water maps from 2015 to 2024, distinguishing permanent, seasonal, and intermittent water bodies with an overall accuracy exceeding 98.2%. Spatiotemporal trend analysis and Geographical Detector modeling were subsequently applied to quantify the drivers of the observed changes. The resulting dataset and analytical approach provide a robust foundation for understanding surface water dynamics and supporting transboundary water management in this climate-sensitive region. Results reveal pronounced spatial heterogeneity and an east-west gradient in ICP surface water dynamics. Surface water covers an average annual extent of 335,118.47 km 2 , with 82.52% intermittent. Country-level patterns diverge markedly: Cambodia and Laos show natural climatic controls with seasonal variability; Thailand exhibits reservoir-mediated storage; Vietnam's Mekong Delta faces persistent recession. Attribution analysis quantitatively confirms this east-west transition in driving mechanisms. These findings underscore the value of integrating multi-source optical data with AI-assisted classification for year-round monitoring in cloud-prone tropical regions, providing critical insights for spatially tailored, transboundary water management strategies. • Developed an AI-assisted framework to monitor surface water for Indochina Peninsula. • Generated 10-m spatiotemporal surface water maps with overall accuracies above 92%. • Identified that most surface water bodies are intermittent in Indochina Peninsula. • Revealed the obvious heterogeneity in surface water changes across local countries. • Climate-Human interactions are predominantly driving the surface water dynamics.
Li et al. (Tue,) studied this question.