白鹤滩库区象鼻岭—野猪塘段地质灾害综合遥感识别

doi:10.11988/ckyyb.20211219

院报 ›› 2023, Vol. 40 ›› Issue (4): 155-163.DOI: 10.11988/ckyyb.20211219

白鹤滩库区象鼻岭—野猪塘段地质灾害综合遥感识别

吴明堂¹, 崔振华¹, 易小宇², 冯文凯², 尹保国², 薛正海², 韩靖楠²

1.浙江华东建设工程有限公司,杭州 310014;
2.成都理工大学地质灾害防治与地质环境保护国家重点实验室,成都 610059

收稿日期:2021-11-19 修回日期:2022-04-12 发布日期:2023-04-26
通讯作者: 冯文凯(1974-),男,河南原阳人,教授,博士,博士研究生导师,研究方向为地质灾害评价与防治。E-mail:fengwenkai@cdut.cn
作者简介:吴明堂(1988-),男,河南商丘人,工程师,主要从事地质灾害防治工作。 E-mail:wu_mt@hdec.com
基金资助:
国家自然科学基金项目(41977252);四川省科技计划项目(2023NSFSC0376);浙江华东建设工程有限公司科研项目(KY2020-HDJS-19)

Identification of Geohazards in Xiangbiling-Yezhutang Section of Baihetan Reservoir Area Using Multi-source Remote Sensing Data

WU Ming-tang¹, CUI Zhen-hua¹, YI Xiao-yu², FENG Wen-kai², YIN Bao-guo², XUE Zheng-hai², HAN Jing-nan²

1. Zhejiang Huadong Construction Engineering Co., Ltd., Hangzhou 310014, China;
2. State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China

Received:2021-11-19 Revised:2022-04-12 Published:2023-04-26

摘要/Abstract

摘要： 在蓄水前查清库岸地质灾害数量和位置是大型水库区地质灾害防治的重要工作之一,人工或单一技术手段的调查方式往往会遗漏许多地质灾害。采用合成孔径雷达干涉测量(Interferometry Synthetic Aperture Radar,InSAR)和无人机光学遥感技术对白鹤滩库区象鼻岭—野猪塘段崩滑库岸地质灾害进行了综合遥感识别工作。通过对识别结果的复核和综合分析,结果表明:①通过综合遥感技术识别地质灾害114处,其中无人机光学遥感和InSAR技术分别识别89处、39处,相比人工排查新增72处;②通过联合升降轨影像的方法有利于改善SAR数据的几何畸变效应,增加SAR可视性区域面积,提高地质灾害识别成果的有效性;③对于新近发生缓慢变形地质灾害可以通过InSAR技术识别,限于光学影像精度和时效性则难以通过光学遥感识别;④过去发生变形的地质灾害可从无人机光学遥感和InSAR识别其宏细观特征,对于SAR数据周期内出现可探测形变,亦可同时被InSAR技术识别;⑤对于面积较大的地质灾害,InSAR技术和光学遥感手段均能有效识别,限于数据精度,InSAR技术对于较小面积的地质灾害难以有效识别。利用InSAR与无人机光学遥感等技术开展地质灾害综合遥感识别,可以获得地质灾害的地表变形信息,了解地质灾害的特征要素信息,克服星载光学遥感解译的局限性,有效避免高山峡谷地区人工或单一技术方法地质灾害识别遗漏。

关键词: 地质灾害, 合成孔径雷达干涉测量, 无人机, 综合遥感, 白鹤滩库区

Abstract: One of the most important tasks in the prevention and control of geohazards in large reservoir areas is to identify the amount and location of geohazards on the reservoir banks before impoundment. Many geohazards are typically missed by manual or single-technique survey methods. Interferometry synthetic aperture radar (InSAR) and unmanned aerial vehicle (UAV) optical remote sensing techniques were used to identify geohazards on the reservoir banks in the Xiangbiling-Yezhutang section of the Baihetan reservoir area. Comprehensive remote sensing technology identified 114 geohazards, with 89 and 39 geohazards identified by UAV optical remote sensing and InSAR technology, respectively, an increase of 72 beyond manual investigation. Combining ascending and descending images helps alleviate the geometric distortion of SAR data, increases the visible area of SAR, and improves the effectiveness of geohazard identification results. Due to image precision and timeliness, InSAR technology can detect newly deformed geohazards. But optical remote sensing has a tough time detecting them. In terms of macroscopic features, geohazards that have been deformed in the past can be recognized using both UAV optical remote sensing and InSAR, and observable deformations that occur within the SAR data cycle can also be identified using InSAR technology. Due to data accuracy limits, InSAR technology and optical remote sensing are both successful in recognizing geohazards over broad areas, while InSAR technology is not useful in identifying geohazards over smaller areas. By using multi-source remote sensing including InSAR and UAV optical remote sensing and other technologies, we can obtain information of the surface deformation of geohazards, understand the characteristics of geohazards, overcome the limitations posed by satellite optical remote sensing interpretation, and effectively avoid the missing error of manual investigation or single technical method for geohazard identification in high mountain and canyon areas.

Key words: geohazards, Interferometry Synthetic Aperture Radar (InSAR), Unmanned Aerial Vehicle (UAV), multi-source remote sensing, Baihetan reservoir area

中图分类号:

P694

吴明堂, 崔振华, 易小宇, 冯文凯, 尹保国, 薛正海, 韩靖楠. 白鹤滩库区象鼻岭—野猪塘段地质灾害综合遥感识别[J]. 院报, 2023, 40(4): 155-163.

WU Ming-tang, CUI Zhen-hua, YI Xiao-yu, FENG Wen-kai, YIN Bao-guo, XUE Zheng-hai, HAN Jing-nan. Identification of Geohazards in Xiangbiling-Yezhutang Section of Baihetan Reservoir Area Using Multi-source Remote Sensing Data[J]. Journal of Yangtze River Scientific Research Institute, 2023, 40(4): 155-163.

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白鹤滩库区象鼻岭—野猪塘段地质灾害综合遥感识别

Identification of Geohazards in Xiangbiling-Yezhutang Section of Baihetan Reservoir Area Using Multi-source Remote Sensing Data

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