TL;DR
A Recursive Bayesian Classification framework is applied to Sentinel-2 time-series imagery to leverage temporal context for improved water detection in the Mekong River Basin, highlighting the potential value of temporal context for surface-water mapping in human-altered and dynamic riverine environments such as the MRB.
River discharge estimation (RDE) methods are traditionally prone to high costs, vulnerability to extreme events, and are constrained by real‐time data availability. Current remote sensing‐based RDE approaches mainly extract basic river features such as width and water surface elevation, but rarely exploit the full spec...
Deltaic regions have undergone rapid ecosystem restructuring under urbanization, agricultural intensification, and hydrological regulation. Existing land-cover datasets, however, often lack the thematic resolution and temporal coherence needed to capture ecosystem type units and transitions in these regions. Here, we d...
A spectral-spatial enhanced hierarchical network is proposed, improving river extraction robustness and accuracy and providing a robust solution for intelligent river monitoring and dynamic analysis using remote sensing imagery.
Satellite-derived reservoir area is useful where continuous in situ records are unavailable, but reported extent can depend on source product, compositing, threshold, and post-processing. This study compared five water-mapping rules for Yamula Dam Lake, Türkiye, using 16 spring and late-summer periods from 2017 to 2024...
Wetlands monitoring is essential for sustainable watershed biodiversity conservation, and climate resilience. This study performs a spatiotemporal wetland change analysis for the Sangamon River Watershed, Illinois between 2000 and 2025, using Landsat 5 Thematic Mapper (TM), Sentinel–2 Surface Reflectance (SR), Syntheti...
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