Photogrammetric rockfall monitoring in Alpine environments using M3C2 and tracked motion vectors
This paper introduces methods for monitoring rock slope movements in Alpine environments based on terrestrial images. The first method is a photogrammtric point cloud-based deformation analysis, relying on M3C2. Although effective in identifying large changes, the method has a tendency to underestim...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-04-01
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| Series: | ISPRS Open Journal of Photogrammetry and Remote Sensing |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667393224000012 |
| _version_ | 1831888153806372864 |
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| author | Lukas Lucks Uwe Stilla Ludwig Hoegner Christoph Holst |
| author_facet | Lukas Lucks Uwe Stilla Ludwig Hoegner Christoph Holst |
| author_sort | Lukas Lucks |
| collection | DOAJ |
| description | This paper introduces methods for monitoring rock slope movements in Alpine environments based on terrestrial images. The first method is a photogrammtric point cloud-based deformation analysis, relying on M3C2. Although effective in identifying large changes, the method has a tendency to underestimate smaller-scale movements. A feature-based method is presented to address this limitation, using SIFT features to track keypoints in images from different epochs. These automatically detected 3D vectors offer high spatial density and enable small-scale movement detection in the order of a few millimeters. The results are incorporated into a deformation analysis that allows statistically based conclusions about the ongoing movements. The workflow relies on georegistration using Ground Control Points. To investigate the possibility of avoiding these points, a registration method based on the ICP algorithm and M3C2 is tested. The study utilizes data from an active landslide site at Hochvogel Mountain in the Alps, analyzing changes and deformations from 2018 to 2021, revealing an average motion of 75 mm. |
| first_indexed | 2024-03-07T23:38:26Z |
| format | Article |
| id | doaj.art-8b7fd4ce039d4856b163d72c077940b5 |
| institution | Directory Open Access Journal |
| issn | 2667-3932 |
| language | English |
| last_indexed | 2025-03-22T00:13:24Z |
| publishDate | 2024-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | ISPRS Open Journal of Photogrammetry and Remote Sensing |
| spelling | doaj.art-8b7fd4ce039d4856b163d72c077940b52024-05-16T04:38:28ZengElsevierISPRS Open Journal of Photogrammetry and Remote Sensing2667-39322024-04-0112100058Photogrammetric rockfall monitoring in Alpine environments using M3C2 and tracked motion vectorsLukas Lucks0Uwe Stilla1Ludwig Hoegner2Christoph Holst3Photogrammetry and Remote Sensing, TUM School of Engineering and Design, Arcisstr. 21, Munich, 80333, Germany; Corresponding author.Photogrammetry and Remote Sensing, TUM School of Engineering and Design, Arcisstr. 21, Munich, 80333, GermanyDepartment of Geoinformatics, Hochschule München, Lothstr. 34, Munich, 80335, GermanyPhotogrammetry and Remote Sensing, TUM School of Engineering and Design, Arcisstr. 21, Munich, 80333, GermanyThis paper introduces methods for monitoring rock slope movements in Alpine environments based on terrestrial images. The first method is a photogrammtric point cloud-based deformation analysis, relying on M3C2. Although effective in identifying large changes, the method has a tendency to underestimate smaller-scale movements. A feature-based method is presented to address this limitation, using SIFT features to track keypoints in images from different epochs. These automatically detected 3D vectors offer high spatial density and enable small-scale movement detection in the order of a few millimeters. The results are incorporated into a deformation analysis that allows statistically based conclusions about the ongoing movements. The workflow relies on georegistration using Ground Control Points. To investigate the possibility of avoiding these points, a registration method based on the ICP algorithm and M3C2 is tested. The study utilizes data from an active landslide site at Hochvogel Mountain in the Alps, analyzing changes and deformations from 2018 to 2021, revealing an average motion of 75 mm.http://www.sciencedirect.com/science/article/pii/S2667393224000012Deformation analysisPoint cloudICP algorithmSIFT featuresSfMRock slope failure |
| spellingShingle | Lukas Lucks Uwe Stilla Ludwig Hoegner Christoph Holst Photogrammetric rockfall monitoring in Alpine environments using M3C2 and tracked motion vectors ISPRS Open Journal of Photogrammetry and Remote Sensing Deformation analysis Point cloud ICP algorithm SIFT features SfM Rock slope failure |
| title | Photogrammetric rockfall monitoring in Alpine environments using M3C2 and tracked motion vectors |
| title_full | Photogrammetric rockfall monitoring in Alpine environments using M3C2 and tracked motion vectors |
| title_fullStr | Photogrammetric rockfall monitoring in Alpine environments using M3C2 and tracked motion vectors |
| title_full_unstemmed | Photogrammetric rockfall monitoring in Alpine environments using M3C2 and tracked motion vectors |
| title_short | Photogrammetric rockfall monitoring in Alpine environments using M3C2 and tracked motion vectors |
| title_sort | photogrammetric rockfall monitoring in alpine environments using m3c2 and tracked motion vectors |
| topic | Deformation analysis Point cloud ICP algorithm SIFT features SfM Rock slope failure |
| url | http://www.sciencedirect.com/science/article/pii/S2667393224000012 |
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