Next Article in Journal
Comparison of Relief Shading Techniques Applied to Landforms
Previous Article in Journal
Machine Learning for Gully Feature Extraction Based on a Pan-Sharpened Multispectral Image: Multiclass vs. Binary Approach
Previous Article in Special Issue
The Measurement of Mobility-Based Accessibility—The Impact of Floods on Trips of Various Length and Motivation
Open AccessEditor’s ChoiceArticle

Detection of Levee Damage Based on UAS Data—Optical Imagery and LiDAR Point Clouds

Department of Photogrammetry, Remote Sensing and Spatial Information Systems, Faculty of Geodesy and Cartography, Warsaw University of Technology, Pl. Politechniki 1, 00-661 Warsaw, Poland
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(4), 248; https://doi.org/10.3390/ijgi9040248
Received: 19 March 2020 / Revised: 15 April 2020 / Accepted: 16 April 2020 / Published: 17 April 2020
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. View Full-Text
Keywords: UAS; LiDAR; photogrammetry; levee monitoring; levee damage; damage detection UAS; LiDAR; photogrammetry; levee monitoring; levee damage; damage detection
Show Figures

Graphical abstract

MDPI and ACS Style

Bakuła, K.; Pilarska, M.; Salach, A.; Kurczyński, Z. Detection of Levee Damage Based on UAS Data—Optical Imagery and LiDAR Point Clouds. ISPRS Int. J. Geo-Inf. 2020, 9, 248.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop