[Back]


Talks and Poster Presentations (with Proceedings-Entry):

R. Sailer, B. Höfle, E. Bollmann, M. Vetter, J. Stötter, N. Pfeifer, M. Rutzinger, T. Geist:
"Multitemporal Error Analysis of LiDAR Data for Geomorphological Feature Detection";
Talk: EGU 2009, Vienna; 2009-04-19 - 2009-04-24; in: "Geophysical Research Abstracts", 11 (2009), Paper ID EGU2009-4799-2, 1 pages.



English abstract:
Since 2001 airborne LiDAR measurements have been carried out regularly at the Hintereisferner region (Ötztal,
Tyrol, Austria). This results in a worldwide unique data set, which is primarily used for multitemporal glacial
and periglacial analyses. Several methods and tools i) to delineate the glacier boundary, ii) to derive standard
glaciological mass balance parameters (e.g. volume changes), iii) to excerpt crevasse zones or iv) to classify glacier
surface features (e.g. snow, firn, glacier ice, debris covered glacier ice) have been developed as yet. Furthermore,
the available multitemporal LiDAR data set offers the opportunity to identify surface changes occurring outside
the glacier boundary, which have not been recognized until now. The respective areas are characterized by small
variations of the surface topography from year to year. These changes of the surface topography are primarily
caused by periglacial processes further initiating secondary gravitative mass movements. The present study aims
at quantifying the error range of LiDAR measurements. The error analysis, which is based on (at least) 66 crosscombinations
of the single LiDAR measurement campaigns, excluding areas which are obviously related to glacial
surface changes, results in statistically derived error margins. Hence, surface changes which exceed these error
margins have to be assigned to periglacial or gravitative process activities. The study further aims at identifying
areas which are explicitly related to those periglacial and gravitative processes.


Electronic version of the publication:
http://publik.tuwien.ac.at/files/PubDat_175560.pdf


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