2026-10-11T03:33:41Z https://www.scidb.cn/oai

10.57760/sciencedb.j00240.00148 2026-04-01T09:56:52Z

2026-04-01 The Global Very-High-Resolution Remote Sensing Landslide Mapping (GVLM) dataset doi:10.57760/sciencedb.j00240.00148 en GVLM is a large-scale benchmark dataset designed for the intelligent interpretation of landslide disasters in remote sensing. It covers 24 representative landslide events across 17 countries on five continents, encompassing diverse triggering mechanisms, landslide morphologies, and land-cover types. The dataset includes multi-temporal high-resolution optical imagery, multispectral data, and SAR imagery, along with fine-grained pixel-level annotations, supporting a wide range of tasks such as change detection, semantic segmentation, and landslide extraction. The total image coverage is approximately 860.8 square kilometers. Addressing challenges such as the scarcity of landslide remote sensing data, difficulties in spatiotemporal localization of landslide events, and the high cost of precise annotation, GVLM systematically tackles the long-standing issue of the limited availability of high-quality landslide samples for disaster monitoring and assessment. It provides a high-precision dataset spanning multiple regions and diverse landslide types, and is currently the largest, highest-resolution, and most event-rich benchmark dataset for landslide remote sensing monitoring. 遥感影像样本; 遥感解译; 高分辨率遥感影像; 多源遥感 张效康 庞超 夏桂松 PUBLIC https://creativecommons.org/licenses/by-nc-nd/4.0/ dataset http://www.doi.org/10.1016/j.isprsjprs.2023.01.018 Science Data Bank