“天-空-地”协同滑坡监测技术进展

doi:10.11947/j.AGCS.2022.20220320

摘要/Abstract

摘要： 滑坡灾害是全球范围内发生频率最高、分布范围最广、造成损失最重的自然灾害之一,严重威胁着人类生命财产和重大工程设施的安全。科学监测是实现滑坡预警预报与主动防范的重要技术前提,经过多年的技术攻关,融合高分辨率光学遥感、卫星InSAR、无人机摄影测量、无线传感网络(WSN)等多种新技术方法,滑坡监测已从传统点式人工监测逐步发展到“天-空-地”多维协同监测,在我国地质灾害风险识别与监测预警方面取得显著成效。本文结合多年来对滑坡发生机理与变形破坏过程的研究认识,从天(光学遥感和InSAR)、空(无人机摄影测量)、地(全球导航卫星系统、裂缝计等专业监测)三维立体角度对我国滑坡监测技术的最新研究进展进行了系统总结,分析讨论了不同技术在工程实践中的技术优势和适用性,构建了滑坡变形破坏全过程的“天-空-地”协同监测技术体系,为滑坡地质灾害的科学防范提供一种新的思维范式和经验指导。

关键词: 滑坡, 光学遥感, InSAR, 无人机摄影测量, 无线传感网络, “天-空-地”协同监测

Abstract: Landslide disaster is one of the natural disasters with the highest frequency, largest distribution, and highest losses worldwide, endangering human life and property as well as important engineering facilities. Scientific monitoring is one of the most significant measures for monitoring and early warning of landslide, as well as active prevention. Landslide monitoring has gradually evolved from traditional manual ground monitoring on specific site to multi-dimensional collaborative monitoring after years of technical research and integration of high-resolution optical remote sensing, satellite InSAR, UAV photogrammetry, wireless sensor network (WSN), and other new technology methods, allowing China to achieve remarkable results in geological disaster risk identification, monitoring, and early warning. Based on a professional understanding of the landslide occurrence mechanism and deformation damage process, this paper summarizes the most recent research progress in landslide monitoring technology in China from the three-dimensional perspectives of spaceborne (optical remote sensing and InSAR), airborne (UAV photogrammetry), and ground-based (global satellite navigation system, crack-meter, and other ground surface and internal monitoring of slope), analyzes, and discusses the technical advantages and disadvantages. The technical advantages and applicability of each in engineering practice are analyzed and discussed, and a new cooperative monitoring mode for the entire process of landslide deformation and damage is proposed, providing a new paradigm of thinking and experience guidance for the scientific prevention of landslide disasters.

Key words: landslide, optical remote sensing, InSAR, UAV photogrammetry, wireless sensor network, "Space-air-ground" cooperative monitoring

中图分类号:

P237

许强, 朱星, 李为乐, 董秀军, 戴可人, 蒋亚楠, 陆会燕, 郭晨. “天-空-地”协同滑坡监测技术进展[J]. 测绘学报, 2022, 51(7): 1416-1436.

XU Qiang, ZHU Xing, LI Weile, DONG Xiujun, DAI Keren, JIANG Yanan, LU Huiyan, GUO Chen. Technical progress of space-air-ground collaborative monitoring of landslide[J]. Acta Geodaetica et Cartographica Sinica, 2022, 51(7): 1416-1436.

参考文献

[1] 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. 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.
[2] 何满潮,任树林,陶志刚.滑坡地质灾害牛顿力远程监测预警系统及工程应用[J].岩石力学与工程学报, 2021, 40(11):2161-2172. HE Manchao, REN Shulin, TAO Zhigang. Remote monitoring and forecasting system of Newton force for landslide geological hazards and its engineering application[J]. Chinese Journal of Rock Mechanics and Engineering, 2021, 40(11):2161-2172.
[3] 许强.对滑坡监测预警相关问题的认识与思考[J].工程地质学报, 2020, 28(2):360-374. XU Qiang. Understanding the landslide monitoring and early warning:consideration to practical issues[J]. Journal of Engineering Geology, 2020, 28(2):360-374.
[4] 白正伟,张勤,黄观文,等."轻终端+行业云"的实时北斗滑坡监测技术[J].测绘学报, 2019, 48(11):1424-1429. DOI:10.11947/j.AGCS.2019.20190167. BAI Zhengwei, ZHANG Qin, HUANG Guanwen, et al. Real-time BeiDou landslide monitoring technology of "light terminal plus industry cloud"[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(11):1424-1429. DOI:10.11947/j.AGCS.2019.20190167.
[5] 廖明生,董杰,李梦华,等.雷达遥感滑坡隐患识别与形变监测[J].遥感学报, 2021, 25(1):332-341. LIAO Mingsheng, DONG Jie, LI Menghua, et al. Radar remote sensing for potential landslides detection and deformation monitoring[J]. National Remote Sensing Bulletin, 2021, 25(1):332-341.
[6] 李为乐,许强,陆会燕,等.大型岩质滑坡形变历史回溯及其启示[J].武汉大学学报(信息科学版), 2019, 44(7):1043-1053. LI Weile, XU Qiang, LU Huiyan, et al. Tracking the deformation history of large-scale rocky landslides and its enlightenment[J]. Geomatics and Information Science of Wuhan University, 2019, 44(7):1043-1053.
[7] 郭晨,许强,董秀军,等.无人机在重大地质灾害应急调查中的应用[J].测绘通报, 2020(10):6-11, 73. DOI:10.13474/j.cnki.11-2246.2020.0309. GUO Chen, XU Qiang, DONG Xiujun, et al. Application of UAV photogrammetry technology in the emergency rescue of catastrophic geohazards[J]. Bulletin of Surveying and Mapping, 2020(10):6-11, 73. DOI:10.13474/j.cnki.11-2246.2020.0309.
[8] 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. 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.
[9] COLESANTI C, WASOWSKI J. Investigating landslides with space-borne synthetic aperture radar (SAR) interferometry[J]. Engineering Geology, 2006, 88(3-4):173-199.
[10] CARLÀ T, INTRIERI E, RASPINI F, et al. Perspectives on the prediction of catastrophic slope failures from satellite InSAR[J]. Scientific Reports, 2019, 9(1):14137.
[11] 李振洪,宋闯,余琛,等.卫星雷达遥感在滑坡灾害探测和监测中的应用:挑战与对策[J].武汉大学学报(信息科学版), 2019, 44(7):967-979. LI Zhenhong, SONG Chuang, YU Chen, et al. Application of satellite radar remote sensing to landslide detection and monitoring:challenges and solutions[J]. Geomatics and Information Science of Wuhan University, 2019, 44(7):967-979.
[12] WANG Xiaowen, LIU Guoxiang, YU Bing, et al. 3D coseismic deformations and source parameters of the 2010 Yushu earthquake (China) inferred from DInSAR and multiple-aperture InSAR measurements[J]. Remote Sensing of Environment, 2014, 152:174-189.
[13] HU Leyin, DAI Keren, XING Chengqi, et al. Land subsidence in Beijing and its relationship with geological faults revealed by Sentinel-1 InSAR observations[J]. International Journal of Applied Earth Observation and Geoinformation, 2019, 82:101886.
[14] BOVENGA F, WASOWSKI J, NITTI D O, et al. Using COSMO/SKYMED X-band and ENVISAT C-band SAR interferometry for landslides analysis[J]. Remote Sensing of Environment, 2012, 119:272-285.
[15] TOFANI V, RASPINI F, CATANI F, et al. Persistent scatterer interferometry (PSI) technique for landslide characterization and monitoring[J]. Remote Sensing, 2013, 5(3):1045-1065.
[16] SUN Qian, ZHANG Lei, DING Xiaoli, et al. Investigation of slow-moving landslides from ALOS/PALSAR images with TCPInSAR:a case study of Oso, USA[J]. Remote Sensing, 2014, 7(1):72-88.
[17] AMITRANO D, GUIDA R, DELL'AGLIO D, et al. Long-term satellite monitoring of the slumgullion landslide using space-borne synthetic aperture radar sub-pixel offset tracking[J]. Remote Sensing, 2019, 11(3):369.
[18] BRU G, GONZÁLEZ P J, MATEOS R M, et al. A-DInSAR monitoring of landslide and subsidence activity:a case of urban damage in Arcos de la Frontera, Spain[J]. Remote Sensing, 2017, 9(8):787.
[19] YE Xia, KAUFMANN H, GUO X F. Landslide monitoring in the Three Gorges area using D-INSAR and corner reflectors[J]. Photogrammetric Engineering&Remote Sensing, 2004, 70(10):1167-1172.
[20] SHI Xuguo, LIAO Mingsheng, LI Menghua, et al. Wide-area landslide deformation mapping with multi-path ALOS PALSAR data stacks:a case study of Three Gorges Area, China[J]. Remote Sensing, 2016, 8(2):136.
[21] 张路,廖明生,董杰,等.基于时间序列InSAR分析的西部山区滑坡灾害隐患早期识别——以四川丹巴为例[J].武汉大学学报(信息科学版), 2018, 43(12):2039-2049. ZHANG Lu, LIAO Mingsheng, DONG Jie, et al. Early detection of landslide hazards in mountainous areas of West China using time series SAR interferometry-a case study of Danba, Sichuan[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12):2039-2049.
[22] DAI Keren, LI Zhenhong, TOMÁS R, et al. Monitoring activity at the Daguangbao mega-landslide (China) using Sentinel-1 TOPS time series interferometry[J]. Remote Sensing of Environment, 2016, 186:501-513.
[23] LIU Xiaojie, ZHAO Chaoying, ZHANG Qin, et al. Heifangtai loess landslide type and failure mode analysis with ascending and descending Spot-mode TerraSAR-X datasets[J]. Landslides, 2020, 17(1):205-215.
[24] KANG Ya, ZHAO Chaoying, ZHANG Qin, et al. Application of InSAR techniques to an analysis of the Guanling landslide[J]. Remote Sensing, 2017, 9(10):1046.
[25] CIGNA F, BATESON L B, JORDAN C J, et al. Simulating SAR geometric distortions and predicting Persistent Scatterer densities for ERS-1/2 and ENVISAT C-band SAR and InSAR applications:nationwide feasibility assessment to monitor the landmass of Great Britain with SAR imagery[J]. Remote Sensing of Environment, 2014, 152:441-466.
[26] COSTANTINI M, FERRETTI A, MINATI F, et al. Analysis of surface deformations over the whole Italian territory by interferometric processing of ERS, Envisat and COSMO-SkyMed radar data[J]. Remote Sensing of Environment, 2017, 202:250-275.
[27] DONG Jie, LIAO Mingsheng, XU Qiang, et al. Detection and displacement characterization of landslides using multi-temporal satellite SAR interferometry:a case study of Danba County in the Dadu River Basin[J]. Engineering Geology, 2018, 240:95-109.
[28] 陆会燕,李为乐,许强,等.光学遥感与InSAR结合的金沙江白格滑坡上下游滑坡隐患早期识别[J].武汉大学学报(信息科学版), 2019, 44(9):1342-1354. LU Huiyan, LI Weile, XU Qiang, et al. Early detection of landslides in the upstream and downstream areas of the Baige landslide, the Jinsha River based on optical remote sensing and InSAR technologies[J]. Geomatics and Information Science of Wuhan University, 2019, 44(9):1342-1354.
[29] DAI Keren, LI Zhenhong, XU Qiang, et al. Entering the era of earth observation-based landslide warning systems:a novel and exciting framework[J]. IEEE Geoscience and Remote Sensing Magazine, 2020, 8(1):136-153.
[30] ZHANG Lele, DAI Keren, DENG Jin, et al. Identifying potential landslides by Stacking-InSAR in southwestern China and its performance comparison with SBAS-InSAR[J]. Remote Sensing, 2021, 13(18):3662.
[31] 冯文凯,顿佳伟,易小宇,等.基于SBAS-InSAR技术的金沙江流域沃达村巨型老滑坡形变分析[J].工程地质学报, 2020, 28(2):384-393. FENG Wenkai, DUN Jiawei, YI Xiaoyu, et al. Deformation analysis of Woda village old landslide in Jinsha river basin using SBAS-InSAR technology[J]. Journal of Engineering Geology, 2020, 28(2):384-393.
[32] DONG Jie, ZHANG Lu, LI Menghua, et al. Measuring precursory movements of the recent Xinmo landslide in Mao County, China with Sentinel-1 and ALOS-2 PALSAR-2 datasets[J]. Landslides, 2018, 15(1):135-144.
[33] KANG Ya, LU Zhong, ZHAO Chaoying, et al. Diagnosis of Xinmo (China) landslide based on interferometric synthetic aperture radar observation and modeling[J]. Remote Sensing, 2019, 11(16):1846.
[34] LIU Xiaojie, ZHAO Chaoying, ZHANG Qin, et al. Deformation of the Baige landslide, Tibet, China, revealed through the integration of cross-platform ALOS/PALSAR-1 and ALOS/PALSAR-2 SAR observations[J]. Geophysical Research Letters, 2020, 47(3):e2019GL086142.
[35] LI Menghua, ZHANG Lu, DING Chao, et al. Retrieval of historical surface displacements of the Baige landslide from time-series SAR observations for retrospective analysis of the collapse event[J]. Remote Sensing of Environment, 2020, 240:111695.
[36] SHI Xuguo, ZHANG Lu, TANG Minggao, et al. Investigating a reservoir bank slope displacement history with multi-frequency satellite SAR data[J]. Landslides, 2017, 14(6):1961-1973.
[37] JIANG Yanan, LIAO Mingsheng, ZHOU Zhiwei, et al. Landslide deformation analysis by coupling deformation time series from SAR data with hydrological factors through data assimilation[J]. Remote Sensing, 2016, 8(3):179.
[38] GAGNON H. Remote sensing of landslide hazards on quick clays of eastern Canada[C]//Proceedings of the 10th International Symposium Remote Sensing of Environment. Michigan, USA:AnnArbor, 1975:803-810.
[39] HUANG S L, CHEN B K. Integration of Landsat and terrain information for landslide study[C]//Proceedings of the 8th Thematic Conference on Geological Remote Sensing. Denver, Colorado:ERIM International, 1991:743-754.
[40] ZHOU C H, LEE C F, LI J, et al. On the spatial relationship between landslides and causative factors on Lantau Island, Hong Kong[J]. Geomorphology, 2002, 43(3-4):197-207.
[41] YAMAGUCHI Y, TANAKA S, ODAJIMA T, et al. Detection of a landslide movement as geometric misregistration in image matching of SPOT HRV data of two different dates[J]. International Journal of Remote Sensing, 2003, 24(18):3523-3534.
[42] GUZZETTI F, MONDINI A C, CARDINALI M, et al. Landslide inventory maps:new tools for an old problem[J]. Earth-Science Reviews, 2012, 112(1-2):42-66.
[43] SCAIONI M, LONGONI L, MELILLO V, et al. Remote sensing for landslide investigations:an overview of recent achievements and perspectives[J]. Remote Sensing, 2014, 6(10):9600-9652.
[44] 李为乐.典型强震同震地质灾害分布规律及后效应研究[D].成都:成都理工大学, 2019. LI Weile. Distribution pattern and post-earthquake effect of coseismic landslides of strong earthquakes[D]. Chengdu:Chengdu University of Technology, 2019.
[45] 于明山.古滑坡堆积体复活形变与堵江机理研究-以甘肃省南峪乡江顶崖滑坡为例[D].成都:成都理工大学, 2020. YU Mingshan. Study on reactivation deformation of ancient landslide accumulation body and mechanism of blocking river-a case study of Jiangdingya Landslide in Nanyu Town, Zhouqu County Gansu Province, China[D]. Chengdu:Chengdu University of Technology, 2020.
[46] TURNER D, LUCIEER A, DE JONG S M. Time series analysis of landslide dynamics using an unmanned aerial vehicle (UAV)[J]. Remote Sensing, 2015, 7(2):1736-1757.
[47] BRIDEAU M A, STURZENEGGER M, STEAD D, et al. Stability analysis of the 2007 Chehalis lake landslide based on long-range terrestrial photogrammetry and airborne LiDAR data[J]. Landslides, 2012, 9(1):75-91.
[48] 喜文飞.滇东北山区无人机遥感影像预处理方法及滑坡特征识别研究[J].测绘学报, 2020, 49(8):1071. DOI:10.11947/j.AGCS.2020.20200081. XI Wenfei. Study on remote sensing image preprocessing method and landslide feature identification of UAV in northeast Yunnan mountain area[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(8):1071. DOI:10.11947/j.AGCS.2020.20200081.
[49] FERNÁNDEZ T, PÉREZ J L, CARDENAL J, et al. Analysis of landslide evolution affecting olive groves using UAV and photogrammetric techniques[J]. Remote Sensing, 2016, 8(10):837.
[50] 许强,郑光,李为乐,等. 2018年10月和11月金沙江白格两次滑坡-堰塞堵江事件分析研究[J].工程地质学报, 2018, 26(6):1534-1551. XU Qiang, ZHENG Guang, LI Weile, et al. Study on successive landslide damming events of Jinsha river in Baige village on Octorber 11 and November 3, 2018[J]. Journal of Engineering Geology, 2018, 26(6):1534-1551.
[51] XU Qiang, LI Weile, JU Yuanzhen, et al. Multitemporal UAV-based photogrammetry for landslide detection and monitoring in a large area:a case study in the Heifangtai terrace in the Loess Plateau of China[J]. Journal of Mountain Science, 2020, 17(8):1826-1839.
[52] 巨袁臻.基于无人机摄影测量技术的黄土滑坡早期识别研究——以黑方台为例[D].成都:成都理工大学, 2017. JU Yuanzhen. Early recognition of loess landslide based on UAV photogrammetry-a case study of Heifang terrace[D]. Chengdu:Chengdu University of Technology, 2017.
[53] MALET J P, MAQUAIRE O, CALAIS E. The use of global positioning system techniques for the continuous monitoring of landslides:application to the Super-Sauze earthflow (Alpes-de-Haute-Provence, France)[J]. Geomorphology, 2002, 43(1-2):33-54.
[54] 韩军强.高精度GNSS实时滑坡变形监测技术及环境建模分析研究[J].测绘学报, 2020, 49(3):397. DOI:10.11947/j.AGCS.2020.20190177. HAN Junqiang. Research on high precision GNSS real time landslide deformation monitoring technology and environmental modeling[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(3):397. DOI:10.11947/j.AGCS.2020.20190177.
[55] 王进,杨元喜,张勤,等.多模GNSS融合PPP系统间偏差特性分析[J].武汉大学学报(信息科学版), 2019, 44(4):475-481. WANG Jin, YANG Yuanxi, ZHANG Qin, et al. Analysis of inter-system bias in Multi-GNSS precise point positioning[J]. Geomatics and Information Science of Wuhan University, 2019, 44(4):475-481.
[56] ZHU Xing, XU Qiang, ZHOU Jianbin, et al. Remote landslide observation system with differential GPS[J]. Procedia Earth and Planetary Science, 2012, 5:70-75.
[57] BENOIT L, BRIOLE P, MARTIN O, et al. Monitoring landslide displacements with the Geocube wireless network of low-cost GPS[J]. Engineering Geology, 2015, 195:111-121.
[58] ZHU Xing, XU Qiang, QI Xing, et al. A self-adaptive data acquisition technique and its application in landslide monitoring[M]//MIKOŠ M, ARBANAS Ž, YIN Yueping, et al. Advancing Culture of Living with Landslides. Cham:Springer, 2017.
[59] ZHU Xing, XI Hewei, HE Zhaoqing, et al. An intelligent wireless displacement sensor for landslide monitoring and early warning[J]. IOP Conference Series:Earth and Environmental Science, 2021, 861(7):072038.
[60] XU Qiang, PENG Dalei, ZHANG Shuai, et al. Successful implementations of a real-time and intelligent early warning system for loess landslides on the Heifangtai Terrace, China[J]. Engineering Geology, 2020, 278:105817.
[61] FAN Xuanmei, XU Qiang, LIU Jie, et al. Successful early warning and emergency response of a disastrous rockslide in Guizhou province, China[J]. Landslides, 2019, 16(12):2445-2457.
[62] ZHU Xing, XU Qiang, ZHAO Zhiye, et al. Low frequency acoustic signals associated with rock falls, thunderstorms, and wind turbulences in field environment[J]. Applied Acoustics, 2016, 112:131-139.
[63] ZHU Xing, XU Qiang ZHOU Jianbin, et al. Experimental study of infrasonic signal generation during rock fracture under uniaxial compression[J]. International Journal of Rock Mechanics and Mining Sciences, 2013, 60:37-46.
[64] 盛敏汉,储日升,曾求,等.地震学方法在滑坡体结构及破裂过程的应用研究进展[J].地球物理学进展, 2019, 34(6):2188-2195. SHENG Minhan, CHU Risheng, ZENG Qiu, et al. Application of seismological methods in landslide structure and rupture process[J]. Progress in Geophysics, 2019, 34(6):2188-2195.
[65] SCHÖPA A, CHAO Weian, LIPOVSKY B P, et al. Dynamics of the Askja caldera July 2014 landslide, Iceland, from seismic signal analysis:precursor, motion and aftermath[J]. Earth Surface Dynamics, 2018, 6(2):467-485.
[66] DAMMEIER F, MOORE J R, HAMMER C, et al. Automatic detection of alpine rockslides in continuous seismic data using hidden Markov models[J]. Journal of Geophysical Research:Earth Surface, 2016, 121(2):351-371.
[67] YANG Zongji, SHAO Wei, QIAO Jianping, et al. A multi-source early warning system of MEMS based wireless monitoring for rainfall-induced landslides[J]. Applied Sciences, 2017, 7(12):1234.
[68] 许强,汤明高,徐开祥,等.滑坡时空演化规律及预警预报研究[J].岩石力学与工程学报, 2008, 27(6):1104-1112. XU Qiang, TANG Minggao, XU Kaixiang, et al. Research on space-time evolution laws and early warning-prediction of landslides[J]. Chinese Journal of Rock Mechanics and Engineering, 2008, 27(6):1104-1112.