测绘通报 ›› 2024, Vol. 0 ›› Issue (5): 1-6.doi: 10.13474/j.cnki.11-2246.2024.0501

• 滑坡灾害识别 •    下一篇

融合InSAR和机载LiDAR技术的滑坡早期识别与分析

郑威1, 左小清1, 李勇发1, 李正会2, 王志红3, 李德彬1   

  1. 1. 昆明理工大学, 云南 昆明 650093;
    2. 云南省遥感中心, 云南 昆明 650034;
    3. 贵州工程应用技术学院, 贵州 毕节 551700
  • 收稿日期:2023-08-25 发布日期:2024-06-12
  • 通讯作者: 左小清。E-mail:zuoxq@163.com
  • 作者简介:郑威(1997—),男,硕士生,研究方向为合成孔径雷达干涉测量。E-mail:814468440@qq.com
  • 基金资助:
    国家自然科学基金(42161067);云南省重大科技专项计划(202202AD080010);毕科联合([2023]51号)

Integration of InSAR and airborne LiDAR technologies for early landslide identification and analysis

ZHENG Wei1, ZUO Xiaoqing1, LI Yongfa1, LI Zhenghui2, WANG Zhihong3, LI Debin1   

  1. 1. Kunming University of Science and Technology, Kunming 650093, China;
    2. Yunnan Remote Sensing Center, Kunming 650034, China;
    3. Guizhou University of Engineering Science, Bijie 551700, China
  • Received:2023-08-25 Published:2024-06-12

摘要: 针对植被密集的复杂山区单一数据滑坡早期识别准确性与可靠性不足的问题,本文结合激光雷达数据的微地貌特征和InSAR技术的形变特征,提出了一种滑坡早期识别分析方法。首先,利用SBAS-InSAR技术提取该地区的时序形变信息,确认形变速率异常分布范围;然后,结合机载雷达的高精度地形地貌的优势,确认主要区域内的7个潜在滑坡,并划分滑坡地图和潜在滑坡的边界识别;最后,结合光学影像遥感和几何畸变原理,对识别结果进行验证。结果表明,结合InSAR和机载LiDAR技术能提高滑坡识别精度和探测能力,滑坡的发育特征和识别结果可为文山地区地质灾害预防和滑坡的编目提供理论支持和依据。

关键词: 激光雷达, SBAS-InSAR, 滑坡, 早期识别

Abstract: The insufficiency in the accuracy and dependability of early landslide identification in densely vegetated complex mountainous areas is tackled in this paper. A method for early landslide identification analysis is suggested, which combines the micro-topographic features from LiDAR data and the deformation characteristics from InSAR technology. Initially, the SBAS-InSAR technique is used to extract the temporal deformation information of the region, confirming the abnormal distribution range of deformation rates. Subsequently,leveraging the advantages of airborne radar in high-precision terrain and landform data, seven potential landslides within the main area are identified, and landslide maps along with the boundaries of potential landslides are delineated. Finally, the identification results are validated through optical image remote sensing and geometric distortion principles. The results demonstrate that the combination of InSAR and airborne LiDAR technologies can enhance the accuracy and detection capabilities of landslide identification. The developmental characteristics of landslides and the identification results provide theoretical support and a basis for the prevention of geological disasters and the cataloging of landslides in the Wenshan region.

Key words: LiDAR, SBAS-InSAR, landslide, early identification

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