Abstract
Identification and calculation of debris flow sources constitute the foundation for scientifically assessing the scale, hazard level, and comprehensive management of debris flows. However, traditional ground surveys and optical remote sensing methods struggle to effectively identify debris flow sources beneath dense vegetation cover in mountainous regions. Airborne Light Detection and Ranging (LiDAR) technology can effectively remove vegetation to obtain true surface morphology, providing a novel solution for debris flow source identification. Taking the debris flow in Rize Gully, Jiuzhaigou earthquake-affected area as a case study, this research conducts debris flow source identification based on high-resolution airborne LiDAR data combined with pre-earthquake satellite imagery. According to the location of sources and their color and texture differences on hillshade images, the sources are classified into collapse-slide sources, slope surface sources, and channel sources, and identification criteria and remote sensing interpretation methods for each source type using airborne LiDAR are established. A total of 155 debris flow sources in Rize Gully were interpreted, with a total area of 1.06 km², accounting for 31.56% of the total watershed area. Based on this, the development and distribution patterns of each source type are analyzed. This study provides theoretical reference and data support for accurate calculation of debris flow sources, further serving the prevention and risk assessment of debris flows in the Jiuzhaigou earthquake-affected area.
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Preamble
Airborne LiDAR-based Debris Flow Material Sources Remote Sensing Recognition in Lush Mountainous Area
LIU Xiaosha¹,², DONG Xiujun¹, QIAN Jiren³, GUO Chen¹,², ZHAO Juncheng³, ZHAN Jiaqi³
¹ State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059
² China Railway Eryuan Engineering Group Co. Ltd, Chengdu 610031
³ Zhejiang Zhenergy Natural Gas Operation Co. Ltd, Hangzhou 310052
Abstract
Identification and quantification of debris flow material sources form the foundation for scientifically assessing debris flow magnitude, hazard levels, and comprehensive mitigation strategies. However, traditional ground surveys and optical remote sensing methods struggle to effectively identify debris flow material sources in mountainous areas covered by dense vegetation. Airborne Light Detection and Ranging (LiDAR) technology can effectively remove vegetation to reveal true surface morphology, providing a novel solution for identifying debris flow material sources.
Taking the Rizegou debris flow in the Jiuzhaigou earthquake-affected area as a case study, this research investigates debris flow material source identification based on high-resolution airborne LiDAR data combined with pre-earthquake satellite imagery. Material sources are classified into three types based on their location and differences in color and texture on hillshade images: collapse-slide sources, slope sources, and channel sources. Airborne LiDAR identification markers and remote sensing interpretation methods are established for each source type. A total of 155 debris flow material sources were interpreted in Rizegou, covering a combined area of 1.06 km² and accounting for 31.56% of the total watershed area. The development and distribution patterns of each source type are analyzed based on these results.
This study provides theoretical reference and data support for the accurate calculation of debris flow material sources, further serving debris flow prevention and risk assessment efforts in the Jiuzhaigou earthquake-affected region.
Keywords: airborne LiDAR; debris flow; material source identification; remote sensing interpretation; Jiuzhaigou earthquake