Abstract
With high spatial resolution, on-demand-flying ability, and the capacity for obtaining three-dimensional measurements, unmanned aerial vehicle (UAV) photogrammetry is widely used for detailed investigations of single landslides, but its effectiveness for landslide detection and monitoring in a large area needs to be investigated. The Heifangtai terrace in the Loess Plateau of China is a loess terrace that is extremely susceptible to irrigation-induced loess landslides. This paper used UAV-based photogrammetry for a series of highresolution images spanning over 30 months for landslide detection and monitoring of the terrace with an area of 32 km2. Dense and evenly distributed ground control points were established and measured to ensure the high accuracy of the photogrammetry results. The structure-from-motion (SfM) technique was used to convert overlapping images into orthographic images, 3D point clouds, digital surface models (DSMs) and mesh models. Using multitemporal differential mesh models, landslide vertical movements and potential landslides were detected and monitored. The results indicate that a combination of UAV-based orthophotos and differential mesh models can be used for flexible and accurate detection and monitoring of potential loess landslides in a large area.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Al-Rawabdeh A, He F, Moussa A, et al. (2016) Using an unmanned aerial vehicle-based digital imaging system to derive a 3D point cloud for landslide scarp recognition. Remote Sensing 8(2):95. https://doi.org/10.3390/rs8020095
Bardi F, Frodella W, Ciampalini A, et al. (2014) Integration between ground based and satellite SAR data in landslide mapping: the san Fratello case study. Geomorphology 223:45–60. https://doi.org/10.1016/j.geomorph.2014.06.025
Brideau MA, Sturzenegger M, Stead D, et al. (2012) Stability analysis of the 2007 Chehalis lake landslide based on longrange terrestrial photogrammetry and airborne LiDAR data. Landslides 9(1):75–91. https://doi.org/10.1007/s10346-011-0286-4
Brückl E, Brunner FK, Kraus K (2006) Kinematics of a deep-seated landslide derived from photogrammetric, GPS and geophysical data. Engineering Geology 88(3):149–159. https://doi.org/10.1016/j.enggeo.2006.09.004
Buckley SJ, Howell JS, Enge HD, et al. (2008) Terrestrial laser scanning in geology: data acq-uisition, processing and accuracy considerations. Journal of the Geological Society 165(3):625–638. https://doi.org/10.1144/0016-76492007-100
Chen ZC, Zhang B, Han YS, et al. (2014) Modeling accumulated volume of landslides using remote sensing and DTM data. Remote Sensing 6(2):1514–1537. https://doi.org/10.3390/rs6021514
Cigna F, Bianchini S, Casagli N (2013) How to assess landslide activity and intensity with persistent Scatterer interferometry (PSI): the PSI-based matrix approach. Landslides 10(3):267–283. https://doi.org/10.1007/s10346-012-0335-7
Derbyshire E, Meng XM, Kemp RA (1998) Provenance, transport and characteristics of modern aeolian dust in western Gansu Province, China, and interpretation of the Quaternary loess record. Journal of Arid Environments 39(3):497–516. https://doi.org/10.1006/jare.1997.0369
Derbyshire E (2001) Geological hazards in loess terrain, with particular reference to the loess re-gions of China. Earth-Science Reviews 54(1):231–260. https://doi.org/10.1016/S0012-8252(01)00050-2
Hsieh YC, Chan YC, Hu JC (2016) Digital elevation model differencing and error estimation from multipl-e sources: A case study from the Meiyuan Shan landslide in Taiwan. Remote Sensing 8(3):199. https://doi.org/10.3390/rs8030199
Dewitte O, Jasselette JC, Cornet Y, et al. (2008) Tracking landslide displacements by multi-temporal DTMs: A combined aerial stereophotogrammetric and LIDAR approach in western Belgium. Engineering Geology 99:11–22. https://doi.org/10.1016/j.enggeo.2008.02.006
Demoulin A (2006) Monitoring and mapping landslide displacements: a combined DGPS-stereophotogrammetric approach for detailed short- and long-term rate estimates. Terra Nova 18(4):290–298. https://doi.org/10.1111/j.1365-3121.2006.00692.x
Sebastian O, Irene M, Klaus DP, et al.(2012) Unmanned aerial vehicle (UAV) for monitoring soil erosion in Morocco. Remote Sensing 4(111:3390–3416. https://doi.org/10.3390/rs4113390
Fernández T, Pérez J, Cardenal J, et al. (2016) Analysis of Landslide Evolution Affecting Olive Groves Using UAV and Photogrammetric Techniques. Remote Sensing 8(10):837. https://doi.org/10.3390/rs8100837
Harwin S, Lucieer A (2012) Assessing the accuracy of Georeferenced point clouds produced via multi-view stereopsis from unmanned aerial vehicle (UAV) imagery. Remote Sensing 4(6):1573–1599. https://doi.org/10.3390/rs4061573
Kenner R, Bühler Y, Delaloye R, et al. (2014) Monitoring of high alpine mass movements combining laser scanning with digital airborne photogrammetry. Geomorphology 206(2):492–504. https://doi.org/10.1016/j.geomorph.2013.10.020
Jaboyedoff M, Oppikofer T, Abellán A, et al. (2012) Use of LIDAR in landslide investigations: a review. Nature Hazards 61:5–28. https://doi.org/10.1007/s11069-010-9634-2
Lucieer A, de Jong SM, Turner D (2014) Mapping landslide displacements using Structure from Motion (SfM) and image correlation of multi-temporal UAV photography. Progress in Physical Geography: Earth and Environment 38(1):97–116. https://doi.org/10.1177/0309133313515293
Mateos RM, Azañón JM, Roldán FJ, et al. (2016) The combined use of PSInSAR and UAV photogrammetry techniques for the analysis of the kinematics of a coastal landslide affecting an urban area (SE Spain). Landslides 14(2)743–754. https://doi.org/10.1007/s10346-016-0723-5
Malet JP, Maquaire O, Calais E (2002) The use of Global Positioning System techniques for the continuous monitoring of landslides: application to the Super-Sauze earthflow (Alpes-de-Haute-Provence, France). Geomorphology 43(1–2):33–54. https://doi.org/10.1016/S0169-555X(01)00098-8
Monserrat O, Moya J, Luzi G, et al. (2013) Non-interferometric GB- SAR measurement: application to the Vallcebre landslide (eastern Pyrenees, Spain). Nature Hazards and Earth System Science 13(7):1873–1887. https://doi.org/10.5194/nhess-13-1873-2013
Niethammer U, James MR, Rothmund S, et al. (2012) UAV-based remote sensing of the super-Sauze landslide: evaluation and results. Engineering Geology 128(11):2–11. https://doi.org/10.1016/j.enggeo.2011.03.012
Peng DL, Xu Q, Qi X, et al. (2016) Study on Early Recognition of Loess Landslides Based on Field Investigation. International Journal of Geohazards and Environment 2(2):35–52. https://doi.org/10.15273/ijge.2016.02.006
Peng DL, Xu Q, Liu FZ, et al. (2018) Distribution and failure modes of the landslides in Heitai terrace, China. Engineering Geology 236:97–110. https://doi.org/10.1016/j.enggeo.2017.09.016
Peng DL, Xu Q, Zhang XL, et al. (2019) Hydrological response of loess slopes with reference to widespread landslide events in the Heifangtai terrace, NW China. Journal of Asian Earth Sciences 171:259–276. https://doi.org/10.1016/jjseaes.2018.12.003
Peng JB, Zhang FY, Wang GH (2017) Rapid loess flow slides in Heifangtai terrace, Gansu, China. Quarterly Journal of Engineering Geology and Hydrogeology 50(2):106–110. https://doi.org/10.1144/qjegh2016-065
Peternel T, Kumelj Š, Oštir K, et al. (2017) Monitoring the Potoška planina landslide (NW Slovenia) using UAV photogrammetry and tachymetric measurements. Landslides 14:395–406. https://doi.org/10.1007/s10346-016-0759-6
Prokešová R, Kardoš M, Medved’ová A (2010) Landslide dynamics from high-resolution aerial p-hotographs: a case study from the Western Carpathians, Slovakia. Geomorphology 115(1–2):90–101. https://doi.org/10.1016/j.geomorph.2009.09.033
Prokop A, Panholzer H (2009) Assessing the capability of terrestrial laser scanning for monitoring slow moving landslides. Nature Hazards and Earth System Science 9(6):1921–1928. https://doi.org/10.5194/nhess-9-1921-2009
Qi X, Xu Q, Liu FZ (2018) Analysis of retrogressive loess flowslides in Heifangtai, China. Engineering Geology 236: 119–128. https://doi.org/10.1016/j.enggeo.2017.08.028
Qin RJ (2014) An object-based hierarchical method for change detection using unmanned aerial vehicle images. Remote Sensing 6(9):7911–7932. https://doi.org/10.3390/rs6097911
Federico R, Andrea C, Sara DC, et al. (2015) Exploitation of amplitude and phase of satellite SAR images for landslide mapping: the case of Montescaglioso (South Italy). Remote Sensing 7(11):14576–14596. https://doi.org/10.3390/rs71114576
Scaioni M, Longoni L, Melillo V, et al. (2014) Remote sensing for landslide investigations: An overview of recent achievements and perspectives. Remote Sensing 6(10):9600–9652. https://doi.org/10.3390/rs6109600
Squarzoni C, Delacourt C, Allemand P (2005) Differential single-frequency GPS monitoring of the La Valette landslide (French Alps). Engineering Geology 79(3–4):215–229. https://doi.org/10.1016/j.enggeo.2005.01.015
Stöcker C, Eltner A, Karrasch P (2015) Measuring gullies by synergetic application of UAV and close range photogrammetry - A case study from Andalusia, Spain. Catena 132:1–11. https://doi.org/10.1016/j.catena.2015.04.004
Tofani V, Raspini F, Catani F, et al. (2013) Persistent Scatterer interferometry (PSI) technique for landslide characterization and monitoring. Remote Sensing 5(3):1045–1065. https://doi.org/10.3390/rs5031045
Turner D, Lucieer A, de Jong SM (2015) Time series analysis of landslide dynamics using an Unmanned Aerial Vehicle (UAV). Remote Sensing 7(2):1736–1757. https://doi.org/10.3390/rs70201736
Xu L, Dai FC, Gong QM, et al. (2012) Irrigation-induced loess flow failure in Heifangtai Platform, North-West China. Environmental Earth Sciences 66(6):1707–1713.
Xu L, Dai FC, Tu XB, et al. (2014) Landslides in a loess platform, North-West China. Landslides 66(11):993–1005. https://doi.org/10.1007/s10346-013-0445-x
Yamagishi H, Marui H, Ayalew L, et al. (2004) Estimation of the sequence and size of the Tozawagawa landslide, Niigata, Japan, using aerial photographs. Landslides 1(4):299–303. https://doi.org/10.1007/s10346-004-0032-2
Yang IT, Park JK, Dong MK (2007) Monitoring the symptoms of landslide using the non-prism total station. KSCE Journal of Civil Engineering 11(6):293–301. https://doi.org/10.1007/BF02885900
Zhang M, Liu J (2010) Controlling factors of loess landslides in western China. Environmental Earth Sciences 59(8):1671–1680. https://doi.org/10.1007/s12665-009-0149-7
Acknowledgments
The work was financially supported by the National Natural Science Foundation of China (Grant Nos. 41521002, 41941019, 41630640), the Major R & D projects of Sichuan Science and Technology Plan (Grant No. 2018SZ0339) and the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project (Grant No. SKLGP2014Z004). The authors thank Dr. Fangzhou LIU from the Georgia Institute of Technology for the support on the collaboration.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Xu, Q., Li, Wl., Ju, Yz. 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. Mt. Sci. 17, 1826–1839 (2020). https://doi.org/10.1007/s11629-020-6064-9
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11629-020-6064-9