A Potential Landslide Hazard Benchmark Dataset for Geological Disaster Detection of Remote Sensing

Rongfang Wang, Haojiang Wei, Yuhui Kong, Peng Zhang, Xiaokai Wang, Weibin Li

Abstract: The research about potential landslide hazards is of great significance for early detection and prevention of geological disasters. However, the existing datasets for the landslide detection visual mainly focus on historical landslides that have already occurred. In this paper, we construct a Ningxia potential landslide hazard benchmark dataset named NXPLH for geological disaster detection of remote sensing. Specifically, it contains 315 potential landslide hazards and 1039 without landslide samples. We have released the dataset at https://github.com/Dataset-RFGroup/NXPLH-Dataset.