HR: 10:35h
AN: H52E-02    [Abstracts]
TI: Integration of Airborne Laser Scanning Altimetry Data in Alpine Geomorphological and Hazard Studies
AU: * Seijmonsbergen, A C
EM: a.c.seijmonsbergen@science.uva.nl
AB: A digital terrain and surface model derived from an airborne laser scanning (ALS) altimetry dataset was used in the Austrian Alps for the preparation, improvement and the evaluation of a digital geomorphological hazard map. The geomorphology in the study area consists of a wide variety of landforms, which include glacial landforms such as cirques, hanging valleys, and moraine deposits, of pre- and postglacial mass movement landforms and processes, such as deep seated slope failures, rock fall, debris flows and solifluction. The area includes naked and covered gypsum karst, collapse dolines and fluvial landforms and deposits such as river terraces, incisions, alluvial fans and gullies. A detailed symbol based paper geomorphological map served as a basis for the digitalization of basic morphogenetic landform and process units. These units were assigned a `geomorphological unit type`, `hazard type` and `activity` code in the attribute table, according to a morphogenetic classification scheme. Selected zonal statistical attributes - mean height, aspect and slope angle - were calculated in a GIS using the vector based morphogenetic landform and process units and the underlying 1m resolution laser altimetry raster dataset. This statistical information was added to the attribute table of the `geomorphological hazard map`. Interpretation of the zonal statistical information shows that indicative topographic signatures exist for the various geomorphological and hazard units in this region of the Alps. Based on this experience a further step is made towards semi-automated geomorphological hazard classification of segmented laser altimetry data using expert knowledge rules. The first results indicate a classification accuracy of 50-70 percent for most landform associations. Areas affected by slide processes resulted in less accurate classification, probably because of their polygenetic history in this area. It is concluded that the use of lidar data improves visual recognition of landslides, especially in combination with high resolution 3D air-photo information. The zonal statistical information helps to more realistically delineate, identify and classify landscape units and promotes consistent data extraction. This leads to efficient and time saving (semi-automated) classification procedures in alpine areas. For future developments it seems promising to further integrate lidar in automated landscape classification tools and in hazard mapping strategies. If high resolution satellite borne laser data becomes available on a regular base a further step towards monitoring of landscape evolution in geomorphological hazard studies can be made.
DE: 1819 Geographic Information Systems (GIS)
DE: 1824 Geomorphology: general (1625)
DE: 1826 Geomorphology: hillslope (1625)
DE: 1847 Modeling
SC: Hydrology [H]
MN: 2007 Fall Meeting