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航空遥感在地质灾害领域的应用:现状与展望

董秀军 邓博 袁飞云 付霞 张文居 巨袁臻 任晓虎

董秀军, 邓博, 袁飞云, 付霞, 张文居, 巨袁臻, 任晓虎. 航空遥感在地质灾害领域的应用:现状与展望[J]. 武汉大学学报 ● 信息科学版. doi: 10.13203/j.whugis20220151
引用本文: 董秀军, 邓博, 袁飞云, 付霞, 张文居, 巨袁臻, 任晓虎. 航空遥感在地质灾害领域的应用:现状与展望[J]. 武汉大学学报 ● 信息科学版. doi: 10.13203/j.whugis20220151
Dong Xiujun, Deng Bo, Yuan Feiyun, Fu Xia, Zhang Wenju, Ju Yuanzhen, Ren Xiaohu. Application of Aerial Remote Sensing in Geological Hazards: Current Situation and Prospects[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20220151
Citation: Dong Xiujun, Deng Bo, Yuan Feiyun, Fu Xia, Zhang Wenju, Ju Yuanzhen, Ren Xiaohu. Application of Aerial Remote Sensing in Geological Hazards: Current Situation and Prospects[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20220151

航空遥感在地质灾害领域的应用:现状与展望

doi: 10.13203/j.whugis20220151
基金项目: 

国家自然科学基金(42072306,41941019),重庆市规划和自然资源局科技项目(KJ-2021015)。

详细信息
    作者简介:

    董秀军,博士,高级实验师,博士生导师,主要从事地质灾害空间数据处理与分析研究。dongxiujun@cdut.cn

  • 中图分类号: P237

Application of Aerial Remote Sensing in Geological Hazards: Current Situation and Prospects

Funds: 

The National Natural Science Foundation of China (42072306, 41941019), Chongqing Municipal Bureau of Planning and Natural Resources Science and Technology Project (KJ-2021015).

  • 摘要:

    地质灾害影响到每一个人口众多的大陆,特别是在多山地国家或地区,其灾害具有明显的高位性、隐蔽性和突发性,通过地质调查提前了解灾害发生历史和现状,对最终实现潜在灾害的识别和预警具有重要意义。目前,传统人工地面调查手段难以发现并查明茂密植被覆盖或地形高陡等复杂山区的重大地质灾害及隐患,而航空遥感作为一种多功能综合性探测技术,因其独特视场角、不受地面条件限制等优势可高效地获取地质灾害发育分布特征和时空演化规律。首先,本文概述了地质灾害领域常用的航空遥感平台类型及发展趋势,分析了不同荷载传感器信息处理技术优势及主要解决的地质灾害问题。其次,综述了航空遥感技术在地质灾害基础地形测绘、早期识别、调查评价、中长期监测、应急处置5个应用阶段的重点研究成果,并论述了不同阶段的各类技术方法要求及优劣性。最后,总结航空遥感技术在地质灾害领域应用研究的不足之处,并阐明了未来发展趋势和建议。

  • [1] Tofani V, Segoni S, Agostini A, et al.Technical note:Use of remote sensing for landslide studies in Europe[J].Natural Hazards and Earth System Science, 2013, 13(2):299-309.
    [2] G.Sithole, G.V osselman/ISPRS Journal of Photogrammetry&Remote Sensing 59(2004)85-101
    [3] Bisson M, Spinetti C, Andronico D, et al.Ten years of volcanic activity at Mt Etna:High-resolution mapping and accurate quantification of the morphological changes by Pleiades and Lidar data[J].International Journal of Applied Earth Observation and Geoinformation, 2021, 102:102369.
    [4] Samar R, Rehman A.Autonomous terrainfollowing for unmanned air vehicles[J].Mechatronics, 2011, 21(5):844-860.
    [5] Kosari A, Maghsoudi H, Lavaei A, et al.Optimal online trajectory generation for a flying robot for terrain following purposes using neural network[J].Proceedings of the Institution of Mechanical Engineers, Part G:Journal of Aerospace Engineering, 2015, 229(6):1124-1141.
    [6] Li X, Cheng X, Chen W, et al.Identification of forested landslides using LiDar data, object-based image analysis, and machine learning algorithms[J].Remote Sensing, Multidisciplinary Digital Publishing Institute, 2015, 7(8):9705-9726.
    [7] Görüm T.Landslide recognition and mapping in a mixed forest environment from airborne LiDAR data[J].Engineering Geology, 2019, 258:105155.
    [8] Gorum T, Fan X, Van Westen C J, et al.Distribution pattern of earthquake-induced landslides triggered by the 12 May 2008 Wenchuan earthquake[J].Geomorphology, 2011, 133(3-4):152-167.
    [9] Valkaniotis S, Papathanassiou G, Ganas A.Mapping an earthquake-induced landslide based on UAV imagery; case study of the 2015 Okeanos landslide, Lefkada, Greece[J].Engineering Geology, 2018, 245:141-152.
    [10] Firpo G, Salvini R, Francioni M, et al.Use of Digital Terrestrial Photogrammetry in rocky slope stability analysis by Distinct Elements Numerical Methods[J].International Journal of Rock Mechanics and Mining Sciences, 2011, 48(7):1045-1054.
    [11] Lucieer A, Jong S M d., Turner D.Mapping landslide displacements using Structure from Motion (SfM) and image correlation of multitemporal UAV photography[J].Progress in Physical Geography, 2014, 38(1):97-116.
    [12] McKean J, Roering J.Objective landslide detection and surface morphology mapping using high-resolution airborne laser altimetry[J].Geomorphology, 2004, 57(3-4):331-351.
    [13] Comert R, Avdan U, Gorum T, et al.Mapping of shallow landslides with object-based image analysis from unmanned aerial vehicle data[J].INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE.Engineering Geology, Cambridge:2019, 260(1):105264.
    [14] Jebur M N, Pradhan B, Tehrany M S.Optimization of landslide conditioning factors using very high-resolution airborne laser scanning (LiDAR) data at catchment scale[J].Remote Sensing of Environment, 2014, 152:150-165.
    [15] So, Anthony&Ho, Tony&Wong, Jeff&Lai, Alice&Leung, Wai Kin&Kwan, Julian.(2021).Advancing the Use of LiDAR in Geotechnical Applications in Hong Kong-A 10-year Overview.The 42nd Asian Conference on Remote Sensing (ACRS2021)
    [16] Wang H, Zhang L, Luo H, et al.AI-powered landslide susceptibility assessment in Hong Kong[J].Engineering Geology, 2021, 288:106103.
    [17] Guo, C., Xu, Q., Dong, X.J., et al., 2021.Geohazard Recognition and Inventory Mapping Using Airborne LiDAR Data in Complex Mountainous Areas.Journal of Earth Science, 32(5):1079-1091.
    [18] Baltsavias E P.Airborne laser scanning:basic relations and formulas[J].ISPRS Journal of Photogrammetry and Remote Sensing, 1999, 54(2):199-214.
    [19] Peternel T, Kumelj Š, Oštir K, et al.Monitoring the Potoška planina landslide (NW Slovenia) using UAV photogrammetry and tachymetric measurements[J].Landslides, 2017, 14(1):395-406.
    [20] Zakšek K, Oštir K, Kokalj Ž.Sky-view factor as a relief visualization technique[J].Remote sensing, 2011, 3(2):398-415.
    [21] Yokoyama, R., Shirasawa, M., Pike, R.J., 2002.Visualizing topography by openness:a new application of image processing to digital elevation models.Photogramm.Eng.Remote.Sens.68, 251-266.
    [22] Chiba, T., Kaneta, S.I., Suzuki, Y., 2008.Red relief image map:new visualization method for three dimensional data.Int.Arch.Photogramm.Remote.Sens.Spat.Inf.Sci.37, 1071-1076.
    [23] Qiang Xu, Chen Guo, Xiujun Dong, Weile Li, Huiyan Lu, Hao Fu and Xiaosha Liu.Mapping and Characterizing Displacements of Landslides with InSAR and Airborne LiDAR Technologies:A Case Study of Danba County, Southwest China.Remote Sens.2021, 13, 4234.
    [24] Favalli M, Fornaciai A.Visualization and comparison of DEM-derived parameters.Application to volcanic areas[J].Geomorphology, 2017, 290:69-84.
    [25] Jaboyedoff M, Metzger R, Oppikofer T, et al.New insight techniques to analyze rock-slope relief using DEM and 3D-imaging cloud points:COLTOP-3D software[J].Proceedings of the 1st Canada-US Rock Mechanics Symposium-Rock Mechanics Meeting Society's Challenges and Demands, 2007, 1(November 2015):61-68.
    [26] T.J.B.Dewez, J.Leroux, S.Morelli.Cliff collapse hazard from repeated multicopter uav acquisitions:return on experience.The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLI-B5, 2016
    [27] Efstratios Karantanellis, Vassilis Marinos, and George Papathanassiou.Multitemporal Landslide Mapping and Quantification of Mass Movement in Red Beach, Santorini Island Using Lidar and UAV Platform.Springer Nature Switzerland AG 2019.
    [28] Al-Rawabdeh, A.;He, F.;Moussa, A.;El-Sheimy, N.;Habib, A.Using an unmanned aerial vehicle based digital imaging system to derive a 3D point cloud for landslide scarp recognition.Remote Sens.2016, 8, 95.
    [29] Li W, Zhao B, Xu Q, et al.Deformation characteristics and failure mechanism of a reactivated landslide in Leidashi, Sichuan, China, on August 6, 2019:an emergency investigation report[J].Landslides, 2020(January).
    [30] Zhan C A, Wg A, Ht A, et al.UAV photogrammetry-based remote sensing and preliminary assessment of the behavior of a landslide in Guizhou, China[J].Engineering Geology, 2021.
    [31] Van Westen C J, Lulie Getahun F.Analyzing the evolution of the Tessina landslide using aerial photographs and digital elevation models[J].Geomorphology, 2003, 54(1-2):77-89.
    [32] 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.
    [33] Liu Q, Kaufmann V.Integrated assessment of cliff rockfall hazards by means of rock structure modelling applied to TLS data:new developments[C]//ISRM Regional SymposiumEUROCK 2015.OnePetro, 2015.
    [34] Zhang F, Hu Z, Yang K, et al.The Surface Crack Extraction Method Based on Machine Learning of Image and Quantitative Feature Information Acquisition Method[J].Remote Sensing, 2021, 13(8):1534.
    [35] A.Riquelme, A.Abellán, R.Tomás, M.Jaboyedoff, A new approach for semi-automatic rock mass joints recognition from 3D point clouds[J], Computers&Geosciences, 2014, 68:38-52.
    [36] Iris Bostjancic, Marina Filipovic, Vlatko Gulam and Davor Pollak.Regional-Scale Landslide Susceptibility Mapping Using Limited LiDARBased Landslide Inventories for Sisak-Moslavina County, Croatia.Sustainability 2021, 13, 4543.
    [37] Pece V.Gorsevski.An evolutionary approach for spatial prediction of landslide susceptibility using LiDAR and symbolic classification with genetic programming.Natural Hazards (2021)108:2283-2307
    [38] Gorsevski P V, Brown M K, Panter K, et al.Landslide detection and susceptibility mapping using LiDAR and an artificial neural network approach:a case study in the Cuyahoga Valley National Park, Ohio[J].Landslides, 2016, 13(3):467-484.
    [39] Abdulwahid W M, Pradhan B.Landslide vulnerability and risk assessment for multi-hazard scenarios using airborne laser scanning data (LiDAR)[J].Landslides, Landslides, 2017, 14(3):1057-1076.
    [40] Stoll J, Moritz D.Unmanned aircraft systems for rapid near surface geophysical measurements[C]//75th EAGE Conference&Exhibition-Workshops.European Association of Geoscientists&Engineers, 2013:cp-349-00062.
    [41] Frodella W, Gigli G, Morelli S, et al.Landslide mapping and characterization through infrared thermography (IRT):suggestions for a methodological approach from some case studies[J].Remote Sensing, 2017, 9(12):1281.
    [42] Supper R, Baroň I, Ottowitz D, et al.Airborne geophysical mapping as an innovative methodology for landslide investigation:evaluation of results from the Gschliefgraben landslide, Austria[J].Natural Hazards and Earth System Sciences, 2013, 13(12):3313-3328.
    [43] Booth A M, McCarley J C, Nelson J.Multi-year, three-dimensional landslide surface deformation from repeat lidar and response to precipitation:Mill Gulch earthflow, California[J].Landslides, Springer, 2020:1-14.
    [44] Fey C, Rutzinger M, Wichmann V, et al.Deriving 3D displacement vectors from multi-temporal airborne laser scanning data for landslide activity analyses[J].GIScience&Remote Sensing, 2015, 52(4):437-461.
    [45] Dewitte O, Jasselette J C, Cornet Y, et al.Tracking landslide displacements by multitemporal DTMs:A combined aerial stereophotogrammetric and LIDAR approach in western Belgium[J].Engineering Geology, 2008, 99(1-2):11-22.
    [46] Lato M J, Anderson S, Porter M J.Reducing Landslide Risk Using Airborne Lidar Scanning Data[J].Journal of Geotechnical and Geoenvironmental Engineering, 2019, 145(9):1-8.
    [47] Ekaso D, Nex F, Kerle N.Accuracy assessment of real-time kinematics (RTK) measurements on unmanned aerial vehicles (UAV) for direct georeferencing[J].Geo-spatial information science, 2020, 23(2):165-181.
    [48] Zhao W, Wang R, Liu X, et al.Field survey of a catastrophic high-speed long-runout landslide in Jichang Town, Shuicheng County, Guizhou, China, on July 23, 2019[J].Landslides, 2020.
    [49] (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 Oiang, Zheng Guang, Li Weile, et al.Sudy on successive landslidle damming events of Jinsha River in Baige Village on Octorber 11 and November 3, 2018[J] Journal of Engineering Geology, 26(6):1534-1551.
    [50] Travelletti J, Delacourt C, Allemand P, et al.Correlation of multi-temporal ground-based optical images for landslide monitoring:Application, potential and limitations[J].ISPRS Journal of Photogrammetry and Remote Sensing, 2012, 70:39-55.
    [51] Pellicani R, Argentiero I, Manzari P, et al.UAV and airborne LiDAR data for interpreting kinematic evolution of landslide movements:The case study of the montescaglioso landslide (Southern Italy)[J].Geosciences (Switzerland), 2019, 9(6).
    [52] Ji S, Yu D, Shen C, et al.Landslide detection from an open satellite imagery and digital elevation model dataset using attention boosted convolutional neural networks[J].Landslides, 2020, 17(6):1337-1352.
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航空遥感在地质灾害领域的应用:现状与展望

doi: 10.13203/j.whugis20220151
    基金项目:

    国家自然科学基金(42072306,41941019),重庆市规划和自然资源局科技项目(KJ-2021015)。

    作者简介:

    董秀军,博士,高级实验师,博士生导师,主要从事地质灾害空间数据处理与分析研究。dongxiujun@cdut.cn

  • 中图分类号: P237

摘要: 

地质灾害影响到每一个人口众多的大陆,特别是在多山地国家或地区,其灾害具有明显的高位性、隐蔽性和突发性,通过地质调查提前了解灾害发生历史和现状,对最终实现潜在灾害的识别和预警具有重要意义。目前,传统人工地面调查手段难以发现并查明茂密植被覆盖或地形高陡等复杂山区的重大地质灾害及隐患,而航空遥感作为一种多功能综合性探测技术,因其独特视场角、不受地面条件限制等优势可高效地获取地质灾害发育分布特征和时空演化规律。首先,本文概述了地质灾害领域常用的航空遥感平台类型及发展趋势,分析了不同荷载传感器信息处理技术优势及主要解决的地质灾害问题。其次,综述了航空遥感技术在地质灾害基础地形测绘、早期识别、调查评价、中长期监测、应急处置5个应用阶段的重点研究成果,并论述了不同阶段的各类技术方法要求及优劣性。最后,总结航空遥感技术在地质灾害领域应用研究的不足之处,并阐明了未来发展趋势和建议。

English Abstract

董秀军, 邓博, 袁飞云, 付霞, 张文居, 巨袁臻, 任晓虎. 航空遥感在地质灾害领域的应用:现状与展望[J]. 武汉大学学报 ● 信息科学版. doi: 10.13203/j.whugis20220151
引用本文: 董秀军, 邓博, 袁飞云, 付霞, 张文居, 巨袁臻, 任晓虎. 航空遥感在地质灾害领域的应用:现状与展望[J]. 武汉大学学报 ● 信息科学版. doi: 10.13203/j.whugis20220151
Dong Xiujun, Deng Bo, Yuan Feiyun, Fu Xia, Zhang Wenju, Ju Yuanzhen, Ren Xiaohu. Application of Aerial Remote Sensing in Geological Hazards: Current Situation and Prospects[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20220151
Citation: Dong Xiujun, Deng Bo, Yuan Feiyun, Fu Xia, Zhang Wenju, Ju Yuanzhen, Ren Xiaohu. Application of Aerial Remote Sensing in Geological Hazards: Current Situation and Prospects[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20220151
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