Remote Sensing · 2016 · 118 citations · 48 references
ComputingEarth SciencesGeoinformaticsDigital Elevation ModelingRemote SensingTerrain AnalysisDigital Terrain ModelingPhotogrammetric Elevation ModelingPhotogrammetric SurveyingPhotogrammetryTerrain MorphometryTopographic AnalysisAerial TriangulationBundle AdjustmentChange Detection In Elevation ModelsLandslide Deformation MeasurementLandslide EvolutionLandslide MonitoringPhotogrammetric Terrain ModelingUnmanned Aerial Vehicle Photogrammetry
UAV technology has become increasingly used in environmental studies, including landslide research, over the past decade. The study applies UAV and high‑resolution photogrammetry to monitor the evolution of a landslide impacting olive groves. UAV flights captured very high‑resolution images that were processed with aerial triangulation, bundle block adjustment, and Structure from Motion to generate DSMs and orthophotos, and differential models and point‑based displacements were computed, and a semi‑automatic method identified horizontal shifts between olive tree centroids. Vertical and horizontal displacements ranged from a few decimeters to several meters, and the monitoring achieved an accuracy of 0.10–0.15 m, demonstrating that UAV‑based photogrammetry and GIS can effectively track landslide movement.
This paper deals with the application of Unmanned Aerial Vehicles (UAV) techniques and high resolution photogrammetry to study the evolution of a landslide affecting olive groves. The last decade has seen an extensive use of UAV, a technology in clear progression in many environmental applications like landslide research. The methodology starts with the execution of UAV flights to acquire very high resolution images, which are oriented and georeferenced by means of aerial triangulation, bundle block adjustment and Structure from Motion (SfM) techniques, using ground control points (GCPs) as well as points transferred between flights. After Digital Surface Models (DSMs) and orthophotographs were obtained, both differential models and displacements at DSM check points between campaigns were calculated. Vertical and horizontal displacements in the range of a few decimeters to several meters were respectively measured. Finally, as the landslide occurred in an olive grove which presents a regular pattern, a semi-automatic approach to identifying and determining horizontal displacements between olive tree centroids was also developed. In conclusion, the study shows that landslide monitoring can be carried out with the required accuracy—in the order of 0.10 to 0.15 m—by means of the combination of non-invasive techniques such as UAV, photogrammetry and geographic information system (GIS).
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The Varnes classification of landslide types, an update
Oldrich Hungr, Serge Leroueil, Luciano Picarelli · Landslides · 2013 · 3.4K citations
José A. Jiménez-Berni, Pablo J. Zarco‐Tejada, Lola Suárez et al. · IEEE Transactions on Geoscience and Remote Sensing · 2009 · 1.3K citations