Detection of Levee Damage Based on UAS Data—Optical Imagery and LiDAR Point Clouds
This paper presents a methodology for levee damage detection based on Unmanned Aerial System (UAS) data. In this experiment, the data were acquired from the UAS platform, which was equipped with a laser scanner and a digital RGB (Red, Green, Blue) camera. Airborne laser scanning (ALS) point clouds w...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-04-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/9/4/248 |
| _version_ | 1797570290371264512 |
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| author | Krzysztof Bakuła Magdalena Pilarska Adam Salach Zdzisław Kurczyński |
| author_facet | Krzysztof Bakuła Magdalena Pilarska Adam Salach Zdzisław Kurczyński |
| author_sort | Krzysztof Bakuła |
| collection | DOAJ |
| description | This paper presents a methodology for levee damage detection based on Unmanned Aerial System (UAS) data. In this experiment, the data were acquired from the UAS platform, which was equipped with a laser scanner and a digital RGB (Red, Green, Blue) camera. Airborne laser scanning (ALS) point clouds were used for the generation of the Digital Terrain Model (DTM), and images were used to produce the RGB orthophoto. The main aim of the paper was to present a methodology based on ALS and vegetation index from RGB orthophoto which helps in finding potential places of levee failure. Both types of multi-temporal data collected from the UAS platform are applied separately: elevation and optical data. Two DTM models from different time periods were compared: the first one was generated from the ALS point cloud and the second DTM was delivered from the UAS Laser Scanning (ULS) data. Archival and new orthophotos were converted to Green-Red Vegetation Index (GRVI) raster datasets. From the GRVI raster, change detection for unvegetation ground areas was analysed using a dynamically indicated threshold. The result of this approach is the localisation of places, for which the change in height correlates with the appearance of unvegetation ground. This simple, automatic method provides a tool for specialist monitoring of levees, the critical objects protecting against floods. |
| first_indexed | 2024-03-10T20:23:49Z |
| format | Article |
| id | doaj.art-086783f71d784bf9b26c2185073e070f |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-10T20:23:49Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-086783f71d784bf9b26c2185073e070f2023-11-19T21:57:40ZengMDPI AGISPRS International Journal of Geo-Information2220-99642020-04-019424810.3390/ijgi9040248Detection of Levee Damage Based on UAS Data—Optical Imagery and LiDAR Point CloudsKrzysztof Bakuła0Magdalena Pilarska1Adam Salach2Zdzisław Kurczyński3Department of Photogrammetry, Remote Sensing and Spatial Information Systems, Faculty of Geodesy and Cartography, Warsaw University of Technology, Pl. Politechniki 1, 00-661 Warsaw, PolandDepartment of Photogrammetry, Remote Sensing and Spatial Information Systems, Faculty of Geodesy and Cartography, Warsaw University of Technology, Pl. Politechniki 1, 00-661 Warsaw, PolandDepartment of Photogrammetry, Remote Sensing and Spatial Information Systems, Faculty of Geodesy and Cartography, Warsaw University of Technology, Pl. Politechniki 1, 00-661 Warsaw, PolandDepartment of Photogrammetry, Remote Sensing and Spatial Information Systems, Faculty of Geodesy and Cartography, Warsaw University of Technology, Pl. Politechniki 1, 00-661 Warsaw, PolandThis paper presents a methodology for levee damage detection based on Unmanned Aerial System (UAS) data. In this experiment, the data were acquired from the UAS platform, which was equipped with a laser scanner and a digital RGB (Red, Green, Blue) camera. Airborne laser scanning (ALS) point clouds were used for the generation of the Digital Terrain Model (DTM), and images were used to produce the RGB orthophoto. The main aim of the paper was to present a methodology based on ALS and vegetation index from RGB orthophoto which helps in finding potential places of levee failure. Both types of multi-temporal data collected from the UAS platform are applied separately: elevation and optical data. Two DTM models from different time periods were compared: the first one was generated from the ALS point cloud and the second DTM was delivered from the UAS Laser Scanning (ULS) data. Archival and new orthophotos were converted to Green-Red Vegetation Index (GRVI) raster datasets. From the GRVI raster, change detection for unvegetation ground areas was analysed using a dynamically indicated threshold. The result of this approach is the localisation of places, for which the change in height correlates with the appearance of unvegetation ground. This simple, automatic method provides a tool for specialist monitoring of levees, the critical objects protecting against floods.https://www.mdpi.com/2220-9964/9/4/248UASLiDARphotogrammetrylevee monitoringlevee damagedamage detection |
| spellingShingle | Krzysztof Bakuła Magdalena Pilarska Adam Salach Zdzisław Kurczyński Detection of Levee Damage Based on UAS Data—Optical Imagery and LiDAR Point Clouds ISPRS International Journal of Geo-Information UAS LiDAR photogrammetry levee monitoring levee damage damage detection |
| title | Detection of Levee Damage Based on UAS Data—Optical Imagery and LiDAR Point Clouds |
| title_full | Detection of Levee Damage Based on UAS Data—Optical Imagery and LiDAR Point Clouds |
| title_fullStr | Detection of Levee Damage Based on UAS Data—Optical Imagery and LiDAR Point Clouds |
| title_full_unstemmed | Detection of Levee Damage Based on UAS Data—Optical Imagery and LiDAR Point Clouds |
| title_short | Detection of Levee Damage Based on UAS Data—Optical Imagery and LiDAR Point Clouds |
| title_sort | detection of levee damage based on uas data optical imagery and lidar point clouds |
| topic | UAS LiDAR photogrammetry levee monitoring levee damage damage detection |
| url | https://www.mdpi.com/2220-9964/9/4/248 |
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