R. Arav, C. Ressl, Robert Weiss, Thomas Artz, Gottfried Mandlburger
{"title":"Evaluation of Active and Passive UAV-Based Surveying Systems for Eulittoral Zone Mapping","authors":"R. Arav, C. Ressl, Robert Weiss, Thomas Artz, Gottfried Mandlburger","doi":"10.5194/isprs-archives-xlviii-2-2024-9-2024","DOIUrl":null,"url":null,"abstract":"Abstract. The eulittoral zone, which alternates between being exposed and submerged, presents a challenge for high-resolution characterization. Normally, its mapping is divided between low and high water levels, where each calls for a different type of surveying instrument. This leads to inconsistent mapping products, both in accuracy and resolution. Recently, uncrewed airborne vehicle (UAV) based photogrammetry was suggested as an available and low-cost solution. However, relying on a passive sensor, this approach requires adequate environmental conditions, while its ability to map inundated regions is limited. Alternatively, UAV-based topo-bathymetric laser scanners enable the acquisition of both submerged and exposed regions independent of lighting conditions while maintaining the acquisition flexibility. In this paper, we evaluate the applicability of such systems in the eulittoral zone. To do so, both topographic and topo-bathymetric LiDAR sensors were loaded on UAVs to map a coastal region along the river Rhein. The resulting point clouds were compared to UAV-based photogrammetric ones. Aspects such as point spacing, absolute accuracy, and vertical offsets were analysed. To provide operative recommendations, each LiDAR scan was acquired at different flying altitudes, while the photogrammetric point clouds were georeferenced based on different exterior information configurations. To assess the riverbed modelling, we compared the surface model acquired by the topo-bathymetric LiDAR sensor to multibeam echosounder measurements. Our analysis shows that the accuracies of the LiDAR point clouds are hardly affected by flying altitude. The derived riverbed elevation, on the other hand, shows a bias which is linearly related to water depth.\n","PeriodicalId":505918,"journal":{"name":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"52 12","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5194/isprs-archives-xlviii-2-2024-9-2024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract. The eulittoral zone, which alternates between being exposed and submerged, presents a challenge for high-resolution characterization. Normally, its mapping is divided between low and high water levels, where each calls for a different type of surveying instrument. This leads to inconsistent mapping products, both in accuracy and resolution. Recently, uncrewed airborne vehicle (UAV) based photogrammetry was suggested as an available and low-cost solution. However, relying on a passive sensor, this approach requires adequate environmental conditions, while its ability to map inundated regions is limited. Alternatively, UAV-based topo-bathymetric laser scanners enable the acquisition of both submerged and exposed regions independent of lighting conditions while maintaining the acquisition flexibility. In this paper, we evaluate the applicability of such systems in the eulittoral zone. To do so, both topographic and topo-bathymetric LiDAR sensors were loaded on UAVs to map a coastal region along the river Rhein. The resulting point clouds were compared to UAV-based photogrammetric ones. Aspects such as point spacing, absolute accuracy, and vertical offsets were analysed. To provide operative recommendations, each LiDAR scan was acquired at different flying altitudes, while the photogrammetric point clouds were georeferenced based on different exterior information configurations. To assess the riverbed modelling, we compared the surface model acquired by the topo-bathymetric LiDAR sensor to multibeam echosounder measurements. Our analysis shows that the accuracies of the LiDAR point clouds are hardly affected by flying altitude. The derived riverbed elevation, on the other hand, shows a bias which is linearly related to water depth.