Semiautomatic Detection and Validation of Geomorphic Seafloor Features Using Laser Airborne Depth Sounding (LADS)

• Published in: Journal of coastal research 2009-01, Vol.SI (56), p.1464-1468
• Main Authors: Achatz, V., Finkl, C. W., Paulus, G.
• Format: Article
• Language: English
• Subjects: Airborne lasers; Bathymetry; Classification; Classification schemes; Coasts; Curvature; Digital elevation models; Digitization; Feature based; Geomorphology; GIS and Remote Sensing Applications; Lasers; Mathematical analysis; Ocean floor; Open source software; Pipelines; Remote sensing; Sea beds; Sounding; Source code; Terrain analysis; Topographical elevation; Topography
• ISSN: 0749-0208; 1551-5036

The paper is based on the diploma thesis of Achatz (2008) and deals with the development of a method that provides semiautomatic detection and validation of geomorphic seafloor features using Laser Airborne Depth Sounding (LADS) Bathymetry. A Digital Elevation Model (DEM) is derived from the LADS digital data files. Geomorphic features are detected using standard terrain analysis attributes such as slope, aspect and curvature from the Open Source Software SAGA GIS, a product of the Göttingen University and Scilands GmbH Göttingen. Equations that combine the different topographic attributes are set up to define the individual geomorphic seafloor features based on their topographic character. A geomorphic map of the seafloor is created by incorporating the resulting individual geomorphic features. The map so produced is compared with expert interpretations of Finkl et al. (2008) to validate these findings. This cartographic interpretation is performed in the same study area and provides necessary information on the spatial location of each geomorphic feature. Based on this comparison, the hypothesis of the thesis, which states that it is possible to define a classification system to semiautomatically detect geomorphic features of the seafloor, is approved. Geomorphic features can be uniquely detected in the study area by using the topographic equations and restrictions represented in the developed classification scheme. For this analysis, areas of the continental shelf offshore Palm Beach and Miami-Dade counties along the southeast coast of Florida are chosen to serve as its study areas. In sum, the semiautomatic approach described in this paper is an alternative solution that complements manual expert interpretation. It is recommended to incorporate the classification process as part of expert interpretation procedures. The interpretation and visualization process is facilitated and enhanced by using the equations. Time and thus costs can be saved in this way.