The quality and uncertainty of training samples are a critical bottleneck constraining the performance of machine learning in landslide susceptibility mapping (LSM). To address this, this study introduces a sample purity optimization framework based on state-process consistency (SPC). The framework utilizes two indices, SWCFD and CF-BE-HMD, combined with a mutually exclusive stratified purity strategy (MESPS), to systematicall...

Oceanic water quality monitoring is essential for environmental protection, resource management, and ecosystem vitality. Optical remote sensing from space plays a pivotal role in global surveillance of oceanic water quality. However, the spatial resolution of current ocean color data products falls short of scrutinizing intricate small-scale marine features. This study introduces a hybrid model that fuses MODIS (Moderate Resol...