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    HE Peng, GUO Zhaocheng, WANG Bin, LIU Bin, GE Daqing, WANG Haochen, BIAN Haoran. Identification of landslide hazards based on LuTan-1 satellite data and its application: A case study of representative districts and counties in Guangdong Province, ChinaJ. Remote Sensing for Natural Resources, 2026, 38(2): 168-180. DOI: 10.6046/zrzyyg.2025072
    Citation: HE Peng, GUO Zhaocheng, WANG Bin, LIU Bin, GE Daqing, WANG Haochen, BIAN Haoran. Identification of landslide hazards based on LuTan-1 satellite data and its application: A case study of representative districts and counties in Guangdong Province, ChinaJ. Remote Sensing for Natural Resources, 2026, 38(2): 168-180. DOI: 10.6046/zrzyyg.2025072

    Identification of landslide hazards based on LuTan-1 satellite data and its application: A case study of representative districts and counties in Guangdong Province, China

    • In recent years, extreme weather events have become increasingly frequent due to global climate change, causing severe disasters in South China. Particularly, Guangdong Province faces severe challenges in the prevention and control of such disasters. Hazard identification, as a primary component of China's integrated geological hazard prevention and control system, plays a crucial role in enhancing disaster prevention and mitigation capabilities. Based on the characteristics of the LuTan-1 (LT-1) satellite data and the occurrence patterns of landslides in Guangdong Province, this study systematically developed a technical methodology for identifying medium- to small- scale landslide hazards in the province. This methodology was applied for the comprehensive identification of geological hazards in nine representative districts and counties of the province. The results demonstrate that the LT-1 satellites exhibited excellent performance in monitoring surface deformation in medium- to small-scale landslide hazard areas. Third-party verification confirms their significant improvement in identification accuracy compared to previous methods. The technical methodology developed in this study can play a significant role in the pre-event warning, in-event detection, and post-event monitoring stages, providing empirical evidence and necessary confidence for its applicability to similar regions in South China.
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