Evaluation of a New Lightweight UAV-Borne Topo-Bathymetric LiDAR for Shallow Water Bathymetry and Object Detection
Airborne LiDAR bathymetry (ALB) has proven to be an effective technology for shallow water mapping. To collect data with a high point density, a lightweight dual-wavelength LiDAR system mounted on unmanned aerial vehicles (UAVs) was developed. This study presents and evaluates the system using the f...
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MDPI AG
2022-02-01
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Online Access: | https://www.mdpi.com/1424-8220/22/4/1379 |
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author | Dandi Wang Shuai Xing Yan He Jiayong Yu Qing Xu Pengcheng Li |
author_facet | Dandi Wang Shuai Xing Yan He Jiayong Yu Qing Xu Pengcheng Li |
author_sort | Dandi Wang |
collection | DOAJ |
description | Airborne LiDAR bathymetry (ALB) has proven to be an effective technology for shallow water mapping. To collect data with a high point density, a lightweight dual-wavelength LiDAR system mounted on unmanned aerial vehicles (UAVs) was developed. This study presents and evaluates the system using the field data acquired from a flight test in Dazhou Island, China. In the precision and accuracy assessment, the local fitted planes extracted from the water surface points and the multibeam echosounder data are used as a reference for water surface and bottom measurements, respectively. For the bathymetric performance comparison, the study area is also measured with an ALB system installed on the manned aerial platform. The object detection capability of the system is examined with placed small cubes. Results show that the fitting precision of the water surface is 0.1227 m, and the absolute accuracy of the water bottom is 0.1268 m, both of which reach a decimeter level. Compared to the manned ALB system, the UAV-borne system provides higher resolution data with an average point density of 42 points/m<sup>2</sup> and maximum detectable depth of 1.7–1.9 Secchi depths. In the point cloud of the water bottom, the existence of a 1-m target cube and the rough shape of a 2-m target cube are clearly observed at a depth of 12 m. The system shows great potential for flexible shallow water mapping and underwater object detection with promising results. |
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institution | Directory Open Access Journal |
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language | English |
last_indexed | 2024-03-09T21:07:26Z |
publishDate | 2022-02-01 |
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spelling | doaj.art-bf49f159e8a44c98aeffa1010b025aef2023-11-23T21:58:32ZengMDPI AGSensors1424-82202022-02-01224137910.3390/s22041379Evaluation of a New Lightweight UAV-Borne Topo-Bathymetric LiDAR for Shallow Water Bathymetry and Object DetectionDandi Wang0Shuai Xing1Yan He2Jiayong Yu3Qing Xu4Pengcheng Li5The Institute of Geospatial Information, Strategic Support Force Information Engineering University, 62 Science Road, Zhengzhou 450001, ChinaThe Institute of Geospatial Information, Strategic Support Force Information Engineering University, 62 Science Road, Zhengzhou 450001, ChinaShanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, 390 Qinghe Road, Shanghai 201800, ChinaThe School of Civil Engineering, Anhui Jianzhu University, 292 Ziyun Road, Hefei 230601, ChinaThe Institute of Geospatial Information, Strategic Support Force Information Engineering University, 62 Science Road, Zhengzhou 450001, ChinaThe Institute of Geospatial Information, Strategic Support Force Information Engineering University, 62 Science Road, Zhengzhou 450001, ChinaAirborne LiDAR bathymetry (ALB) has proven to be an effective technology for shallow water mapping. To collect data with a high point density, a lightweight dual-wavelength LiDAR system mounted on unmanned aerial vehicles (UAVs) was developed. This study presents and evaluates the system using the field data acquired from a flight test in Dazhou Island, China. In the precision and accuracy assessment, the local fitted planes extracted from the water surface points and the multibeam echosounder data are used as a reference for water surface and bottom measurements, respectively. For the bathymetric performance comparison, the study area is also measured with an ALB system installed on the manned aerial platform. The object detection capability of the system is examined with placed small cubes. Results show that the fitting precision of the water surface is 0.1227 m, and the absolute accuracy of the water bottom is 0.1268 m, both of which reach a decimeter level. Compared to the manned ALB system, the UAV-borne system provides higher resolution data with an average point density of 42 points/m<sup>2</sup> and maximum detectable depth of 1.7–1.9 Secchi depths. In the point cloud of the water bottom, the existence of a 1-m target cube and the rough shape of a 2-m target cube are clearly observed at a depth of 12 m. The system shows great potential for flexible shallow water mapping and underwater object detection with promising results.https://www.mdpi.com/1424-8220/22/4/1379LiDARbathymetryunmanned aerial vehiclesobject detectioncoastal mappingfull-waveform |
spellingShingle | Dandi Wang Shuai Xing Yan He Jiayong Yu Qing Xu Pengcheng Li Evaluation of a New Lightweight UAV-Borne Topo-Bathymetric LiDAR for Shallow Water Bathymetry and Object Detection Sensors LiDAR bathymetry unmanned aerial vehicles object detection coastal mapping full-waveform |
title | Evaluation of a New Lightweight UAV-Borne Topo-Bathymetric LiDAR for Shallow Water Bathymetry and Object Detection |
title_full | Evaluation of a New Lightweight UAV-Borne Topo-Bathymetric LiDAR for Shallow Water Bathymetry and Object Detection |
title_fullStr | Evaluation of a New Lightweight UAV-Borne Topo-Bathymetric LiDAR for Shallow Water Bathymetry and Object Detection |
title_full_unstemmed | Evaluation of a New Lightweight UAV-Borne Topo-Bathymetric LiDAR for Shallow Water Bathymetry and Object Detection |
title_short | Evaluation of a New Lightweight UAV-Borne Topo-Bathymetric LiDAR for Shallow Water Bathymetry and Object Detection |
title_sort | evaluation of a new lightweight uav borne topo bathymetric lidar for shallow water bathymetry and object detection |
topic | LiDAR bathymetry unmanned aerial vehicles object detection coastal mapping full-waveform |
url | https://www.mdpi.com/1424-8220/22/4/1379 |
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