Accurate Interpretation of Four-Dimensional Characteristics of RedBed Rock Landslide by Comprehensive Remote Sensing — Taking Kualiangzi Landslide as an Example
-
摘要: 针对红层滑坡隐蔽性强、突发性高、成因机理复杂等特点,人工地面调查或单一遥感手段难以实现滑坡的精准解译。以垮梁子特大型红层岩质滑坡为例,采用机载激光雷达(Light Detection and Ranging,LiDAR)、光学遥感、合成孔径雷达干涉测量(Interferometric Synthetic Aperture Radar,InSAR)综合遥感技术,对滑坡标志三维空间形态、滑坡水平方向及沿雷达视线方向时空变形演化规律的综合四维特征展开精准解译。结果表明,LiDAR成果解译出滑坡边界与裂缝33条,鼓丘5处、垮塌3处;多时相光学影像数据结合高分辨率数字高程模型山体阴影图,进行捕捉典型特征点变形位移,解译了研究区53年内时空演化规律,最大水平位移量为40 m,位于滑坡中部;小基线集、干涉图堆叠时序InSAR技术破译滑坡中部近年来持续抬升,最大抬升速率为55 mm/a;研究成果可实现对红层岩质滑坡四维特征的精准解译,为红层地区滑坡灾害识别与防治提供指导。Abstract: Objectives: Due to the characteristics of red-bed landslide, such as strong concealment, high suddenness and complex formation mechanism, it is difficult to accurately interpret the landslide by artificial ground survey or single remote sensing method. Methods: Taking Kualiangzi super-large red-bed rock landslide as an example, light detection and ranging (LiDAR), optical remote sensing and Interferometric synthetic aperture radar(InSAR) comprehensive remote sensing technologies are used to accurately interpret the comprehensive four-dimensional characteristics of the three-dimensional spatial form of landslide signs, the horizontal direction of landslide and the spatiotemporal deformation evolution law in the line of sight direction. Results: LiDAR results have interpreted 33 landslide boundaries and cracks, 5 drums and 3 collapses. Multi-temporal optical image data were combined with high-resolution digital elevation model hillshade map to capture the deformation and displacement of typical feature points, and interpret the spatiotemporal evolution law of the study area in 53 years. The maximum horizontal displacement is 40 m, which is located in the middle of the landslide. The InSAR technique of small baseline subsets and interferometer Stacking shows that the central part of the landslide has been continuously uplifted in recent years, and the maximum uplifting rate is 55 mm/a. Conclusions: The research results can accurately interpret the fourdimensional characteristics of red-bed rock landslide, and provide guidance for the identification and prevention of landslide disasters in red-bed areas.
-
-
[1] Xu Qiang, Tang Ran. Study on Red Beds and its Geological Hazards[J].Chinese Journal of Rock Mechanics and Engineering, 2023, 42(1):28-50(许强,唐然.红层及其地质灾害研究[J].岩石力学与工程学报, 2023, 42(1):28-50) [2] Xu Qiang, Lu Huiyan, Li Weile, et al. Types of Potential Landslide and Corresponding Identification Technologies[J]. Geomatics and Information Science of Wuhan University, 2022, 47(3):377-387(许强,陆会燕,李为乐等.滑坡隐患类型与对应识别方法[J].武汉大学学报(信息科学版), 2022, 47(3):377-387) [3] Xu Qiang, Dong Xiujun, Li Weile. Integrated Space-Air-Ground Early Detection, Monitoring and Warning System for Potential Catastrophic Geohazards[J]. Geomatics and Information Science of Wuhan University, 2019, 44(7):957-966(许强,董秀军,李为乐.基于天-空-地一体化的重大地质灾害隐患早期识别与监测预警[J].武汉大学学报(信息科学版), 2019, 44(7):957-966) [4] GE Daqing.Comprehensive Applicat-ion of Remote Sensing in Early Identification, Monitoring and Early warning in Geological Disasters[J].City and Disaster Reduction, 2018(6):53-60(葛大庆.地质灾害早期识别与监测预警中的综合遥感应用[J].城市与减灾, 2018(6):53-60) [5] He Peng, Yan Yuyan, Wen Yan, et al. Application of the airborne LiDAR technology in the identification of flat landsli-des and their crack grooves[J]. Remote Sensi-ng for Land&Resources, 2022, 34(4):307-316(贺鹏,颜瑜严,文艳等.机载LiDAR技术在缓倾地层滑坡及其拉裂槽识别中的应用[J].自然资源遥感, 2022, 34(4):307-316) [6] Zhang Qin, Zhao Chaoying, Chen Xuerong. Technical Progress and Develop-ment Trend of Geological Hazards Early Iden-tification with Multisource Remote Sensing[J]. Acta Geodaetica et Cartographica Sinica, 2022, 51(6):885-896(张勤,赵超英,陈雪蓉.多源遥感地质灾害早期识别技术进展与发展趋势[J].测绘学报, 2022, 51(6):885-896) [7] Guo Chen, Xu Qiang, Dong Xiujun, et al. Geohazard Recognition by Airborne LiDAR Technology in Complex Mountain Areas[J]. Geomatics and Information Science of Wuhan University, 2021, 46(10):1538-1547(郭晨,许强,董秀军,等.复杂山区地质灾害机载激光雷达识别研究[J].武汉大学学报(信息科学版), 2021, 46(10):1538-1547) [8] Wang Xuan, Fan Xuanmei, Yang Fan, et al. Remote Sensing Interpretation Method of Geological Hazards in Lush Mountainous Area[J]. Geomatics and Information Science of Wuhan University, 2020, 45(11):1771-1781(王绚,范宣梅,杨帆等.植被茂密山区地质灾害遥感解译方法研究[J].武汉大学学报(信息科学版), 2020, 45(11):1771-1781) [9] Dong Xiujun, Xu Qiang, She Jinxing, et al. Preliminary Study on Interpretat-ion of Geological Hazards in Jiuzhaigou Based on Multisource Remote Sensing Data[J]. Geomatics and Information Science of Wuhan University, 2020, 45(3):432-441(董秀军,许强,佘金星等.九寨沟核心景区多源遥感数据地质灾害解译初探[J].武汉大学学报(信息科学版), 2020, 45(3):432-441) [10] Ding Yonghui, Zhang Qing, Yang Chengsheng, et al. Landslide identification in Jinsha River basin based on high resolution remote sensing:taking Wangdalong village of Batang county as an example[J]. Bulletin of Surveying and Mapping, 2022(4):51-55(丁永辉,张勤,杨成生等.基于高分遥感的金沙江流域滑坡识别--以巴塘县王大龙村为例[J].测绘通报, 2022(4):51-55) [11] Tang Yao, Wang Lijuan, Ma Guochao, et al. Disaster Monitoring and Application Prospect Analysis of the Jinsha River Landslide Based on "Gaofen+" [J]. Geomatics and Information Science of Wuhan University, 2019, 44(7):1082-1092(唐尧,王立娟,马国超等.基于"高分+"的金沙江滑坡灾情监测与应用前景分析[J].武汉大学学报(信息科学版), 2019, 44(7):1082-1092) [12] Dai Lanxin, Xu Qiang, Fan Xuanmei, et al. 2017:A Preliminary Study on Spatial Distribution Patterns of Landslides Triggered by Jiuzhaigou Earthquake in Sichuan on August 8th, 2017 and Their Susceptibility Assessment. Journal of Engineering Geology, 2017, 25(4):1151-1164(戴岚欣,许强,范宣梅等. 2017年8月8日四川九寨沟地震诱发地质灾害空间分布规律及易发性评价初步研究[J].工程地质学报, 2017, 25(4):1151-1164) [13] Xie Mingli, Zhao Jianjun, Ju Nengpan, et al. Research on Temporal and Spatial Evolution of Landslide Based on Multisource Data:A Case Study of Huangnibazi Landslide[J]. Geomatics and Information Science of Wuhan University, 2020, 45(6):923-932(解明礼,赵建军,巨能攀,等.多源数据滑坡时空演化规律研究--以黄泥坝子滑坡为例[J].武汉大学学报(信息科学版), 2020, 45(6):923-932) [14] Zhang Jingfa, Li Qiang, Zhang Qingyun, et al. Intensity Zone of the 1976 Ms7.8 Tangshan Earthquake Based on Multisource Remote Sen-sing Images[J]. Journal of Remote Sensing, 2018, 22(S1):173(张景发,李强,张庆云,等.多源遥感图像的1976年Ms7.8唐山大地震等烈度区判定[J].遥感学报, 2018, 22(S1):162-173) [15] Lu Lejun, Zhou Yu. Extracting Surface Displacements of Historical Earthquakes Using KH-9 Satellite Images:A Case Example of 1976 Chaldiran Earthquake, Turkey[J]. Geomatics and Information Science of Wuhan University, 2021,46(2):289-295(卢乐浚,周宇.利用锁眼卫星影像提取历史地震同震位移--以1976年土耳其Chaldiran地震为例[J].武汉大学学报(信息科学版), 2021, 46(2):289-295) [16] Wang Zhe, Zhao Chaoying, Liu Xiaojie, et al.Evolution Analysis and Deformation Monitoring of Yigong Landslide in Tibet with Optical Remote Sensing and InSAR[J]. Geomatics and Information Science of Wuhan University, 2021, 46(10):1569-157(王哲,赵超英,刘晓杰等.西藏易贡滑坡演化光学遥感分析与InSAR形变监测[J].武汉大学学报(信息科学版), 2021, 46(10):1569-1578) [17] Xiang Qiwen, Guo Jincheng, Wang Juan, et al. Application of time series InSAR in recognition of hidden dangers of geological hazards in Guizhou Area[J].Science of Surveying and Mapping,2022,47(9):112-119(向淇文,郭金城,汪娟等.时序InSAR在贵州区域地质灾害隐患识别的应用[J].测绘科学,2022,47(9):112-119) [18] Zhuo Guanchen, Dai Keren, Zhou Fujun, Shen Yue, Chen Chen, Xu Qiang. Moni-toring Typical Construction Sites of Sichuan-Tibet Traffic Corridor by InSAR and Intensive Distortion Analysis[J]. Earth Science, 2022, 47(6):2031-2047(卓冠晨,戴可人,周福军等.川藏交通廊道典型工点InSAR监测及几何畸变精细判识[J].地球科学, 2022, 47(6):2031-2047) [19] WU Lüchuan, WANG Jianhui, FU Yan. Early Identifying and Monitoring Landslides in Guizhou Province with InSAR and Optical Remote Sensing[J]. Bulletin of Surveying and Mapping, 2021(7):98-102(吴绿川,王剑辉,符彦.基于InSAR技术和光学遥感的贵州省滑坡早期识别与监测[J].测绘通报, 2021(7):98-102) [20] Yu Xiangwei, Xue Dongjian, Chen Fengjiao.Analysis of Influence of Vegetat-ion Coverage and Slope on SAR Interferom-etric Coherence[J].Mountain Research, 2020, 38(6):926-934(余祥伟,薛东剑,陈凤娇.植被及坡度对SAR干涉相干性的影响分析[J].山地学报, 2020, 38(6):926-934) [21] Zhai Guojun. Analysis of the Basic Characteristics and Deformation mechanism of Kualiangzi Landslide in ZhongJiang[D]. Chengdu:Chengdu University of Technology,2011(翟国军.中江冯店垮梁子滑坡基本特征与变形机理研究[D].成都:成都理工大学, 2011) [22] Guo Xiaoguang, Huang Runqiu, Deng Hui, et al. Formation and Mechanism Analysis of Multilevel Rift Trough in Translational Sliding Landslide[J]. Journal of Engineering Geology, 2013:21(5):770-77(郭晓光,黄润秋,邓辉等.平推式滑坡多级拉陷槽形成过程及成因机理分析[J].工程地质学报, 2013, 21(5):770-778) [23] Liu Xiaosha, Dong Xiujun, Qian Jiren, et al. A Weighted Radial Basis Function Interpolation Method for High Accuracy DEM Modeling[J].Geomatics and Information Science of Wuhan University, 2021, DOI:10.13203/j.whugis20210486.(刘小莎,董秀军,钱济人,等.高植被山区泥石流物源LiDAR遥感精细识别方法研究[J].武汉大学学报(信息科学版), 2021, DOI:10.13203/j.whugis20210486.) [24] Massimo C, Michele M, Luigi B. Morphological Changes Detection of a Large Earthflow Using Archived Images, LiDAR-Derived DTM, and UAVBased Remote Sensing[J]. Remote Sensing, 2020, 13(1).
[25] Sha Yonglian. Deformation Field Monitoring in Mining Area and Parameter Inversion of Fullymechanized Face Based on Multi-temporal InSAR[D].Chengdu:Southwest Jiaotong University, 2020(沙永莲.基于多时相In-SAR的矿区形变场监测与综采面参数反演[D].成都:西南交通大学, 2020)
计量
- 文章访问数: 288
- HTML全文浏览量: 27
- PDF下载量: 63