Detection of levee damage based on UAS data-optical imagery and LiDAR point clouds

Krzysztof Bakuła , Magdalena Pilarska , Adam Salach , Zdzisław Kurczyński


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.

Author Krzysztof Bakuła (FGC / DPTSIS)
Krzysztof Bakuła,,
- Department of Photogrammetry, Teledetection and Spatial Information Systems
, Magdalena Pilarska (FGC / DPTSIS)
Magdalena Pilarska,,
- Department of Photogrammetry, Teledetection and Spatial Information Systems
, Adam Salach (FGC / DPTSIS)
Adam Salach,,
- Department of Photogrammetry, Teledetection and Spatial Information Systems
, Zdzisław Kurczyński (FGC / DPTSIS)
Zdzisław Kurczyński,,
- Department of Photogrammetry, Teledetection and Spatial Information Systems
Journal seriesISPRS International Journal of Geo-Information, ISSN 2220-9964
Issue year2020
Vol9 (4)
Publication size in sheets0.7
Keywords in EnglishUAS; LiDAR; photogrammetry; levee monitoring; levee damage; damage detection
ASJC Classification3305 Geography, Planning and Development; 1901 Earth and Planetary Sciences (miscellaneous); 1903 Computers in Earth Sciences
Internal identifier25/2020
Languageen angielski
Score (nominal)70
Score sourcejournalList
ScoreMinisterial score = 70.0, 20-07-2020, ArticleFromJournal
Publication indicators Scopus Citations = 0; WoS Citations = 0; Scopus SNIP (Source Normalised Impact per Paper): 2018 = 1.229; WoS Impact Factor: 2018 = 1.84 (2) - 2018=2.022 (5)
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