Records of shallow landslides triggered by extreme rainfall in July 2024 in Zixing, China

Global climate change has led to the frequent extreme meteorological events in recent years, triggering severe clustered landslides in mountainous regions. Records of these clustered landslides not only provide post-disaster statistics but also play a crucial role in advancing data-driven regional landslide research and intelligent landslide detection. The Rainfall-induced Landslide in Zixing (RLZX) datasets consist of a landslide inventory map (LIM) and a landslide detection dataset (LDD). RLZX-LIM was created through visual interpretation of 3D scenes before and after the rainfall event, containing 19,403 shallow landslides triggered by extreme rainfall in Zixing City, China, between July 26 and July 28, 2024. We have provided quantitative evaluations of the quality of RLZX-LIM based on reference data obtained from road-aligned surveys and unmanned aerial vehicle (UAV) mapping in the field. RLZX-LDD is further developed using both UAV and satellite images, offering higher quality and robustness, effectively filling the gap in rainfall-induced LDDs. The RLZX datasets have been publicly released for free use to promote related landslide research.近年来，全球气候变化引发极端气象事件频发，进而导致山区出现严重的群发性滑坡灾害。此类群发性滑坡的记录不仅可为灾后统计提供数据支撑，同时对推动数据驱动型区域滑坡研究与智能滑坡检测工作具有关键意义。资兴降雨滑坡（RLZX）数据集包含滑坡编目图（Landslide Inventory Map, LIM）与滑坡检测数据集（Landslide Detection Dataset, LDD）两个子数据集。其中，RLZX-LIM通过对2024年7月26日至28日降雨事件前后的三维场景开展目视解译构建而成，收录了中国资兴市在此极端降雨过程中触发的19403处浅层滑坡。本研究基于野外道路沿线调查与无人机（Unmanned Aerial Vehicle, UAV）测绘获取的参考数据，对RLZX-LIM的质量进行了定量评估。RLZX-LDD则结合无人机与卫星影像进一步开发，具备更优异的质量与鲁棒性，有效填补了降雨诱发型滑坡检测数据集的空白。目前RLZX数据集已公开免费发布，旨在推动相关滑坡领域的研究进展。