Talks and Poster Presentations (with Proceedings-Entry):

G. Mandlburger:
"A Case Study on Through-Water Dense Image Matching";
Talk: ISPRS Technical Commission II Symposium 2018, Riva del Garda, Italy; 2018-06-03 - 2018-06-07; in: "ISPRS TC II Mid-term Symposium Towards Photogrammetry 2020", The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-2 (2018), ISSN: 1682-1750; 659 - 666.

English abstract:
In the last years, the tremendous progress in image processing and camera technology has reactivated the interest in photogrammetrybased surface mapping. With the advent of Dense Image Matching (DIM), the derivation of height values on a per-pixel basis became feasible, allowing the derivation of Digital Elevation Models (DEM) with a spatial resolution in the range of the ground sampling distance of the aerial images, which is often below 10 cm today. While mapping topography and vegetation constitutes the primary field of application for image based surface reconstruction, multi-spectral images also allow to see through the water surface to the bottom underneath provided sufficient water clarity. In this contribution, the feasibility of through-water dense image matching for mapping shallow water bathymetry using off-the-shelf software is evaluated. In a case study, the SURE software is applied to three different coastal and inland water bodies. After refraction correction, the DIM point clouds and the DEMs derived thereof are compared to concurrently acquired laser bathymetry data. The results confirm the general suitability of through-water dense image matching, but sufficient bottom texture and favorable environmental conditions (clear water, calm water surface) are a preconditions for achieving accurate results. Water depths of up to 5 m could be mapped with a mean deviation between laser and trough-water DIM in the dm-range. Image based water depth estimates, however, become unreliable in case of turbid or wavy water and poor bottom texture.

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Created from the Publication Database of the Vienna University of Technology.