期刊
XXIII ISPRS CONGRESS, COMMISSION V
卷 41, 期 B5, 页码 805-811出版社
COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/isprsarchives-XLI-B5-805-2016
关键词
UAV; 3D point clouds; photogrammetry; cliff collapse hazard; Normandy; France
类别
资金
- ANR-Carnot-Investissement d'Avenir Captiven project
- Institut Carnot BRGM
Cliff collapse poses a serious hazard to infrastructure and passers-by. Obtaining information such as magnitude-frequency relationship for a specific site is of great help to adapt appropriate mitigation measures. While it is possible to monitor hundreds-ofmeter- long cliff sites with ground based techniques (e. g. lidar or photogrammetry), it is both time consuming and scientifically limiting to focus on short cliff sections. In the project SUAVE, we sought to investigate whether an octocopter UAV photogrammetric survey would perform sufficiently well in order to repeatedly survey cliff face geometry and derive rock fall inventories amenable to probabilistic rock fall hazard computation. An experiment was therefore run on a well-studied site of the chalk coast of Normandy, in Mesnil Val, along the English Channel (Northern France). Two campaigns were organized in January and June 2015 which surveyed about 60 ha of coastline, including the 80-m-high cliff face, the chalk platform at its foot, and the hinterland in a matter of 4 hours from start to finish. To conform with UAV regulations, the flight was flown in 3 legs for a total of about 30 minutes in the air. A total of 868 and 1106 photos were respectively shot with a Sony NEX 7 with fixed focal 16mm. Three lines of sight were combined: horizontal shots for cliff face imaging, 45 degrees-oblique views to tie plateau/platform photos with cliff face images, and regular vertical shots. Photogrammetrically derived dense point clouds were produced with Agisoft Photoscan at ultrahigh density (median density is 1 point every 1.7cm). Point cloud density proved a critical parameter to reproduce faithfully the chalk face's geometry. Tuning down the density parameter to high or medium, though efficient from a computational point of view, generated artefacts along chalk bed edges (i. e. smoothing the sharp gradient) and ultimately creating ghost volumes when computing cloud to cloud differences. Yet, from a hazard point of view, this is where small rock fall will most likely occur. Absolute orientation of both point clouds proved unsufficient despite the 30 black and white quadrants ground control point DGPS surveyed. Additional ICP was necessary to reach centimeter-level accuracy and segment rock fall scars corresponding to the expected average daily rock fall volume (ca. 0.013 m3).
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