HR: 13:40h
AN: H53K-01    [Abstracts]
TI: Identification of Geologic Contrasts from Landscape Dissection Pattern: an Application to Cascade Range, Oregon
AU: * Luo, W
EM: wluo@niu.edu
AF: Northern Illinois University, Department of Geography Davis Hall 120, DeKalb, IL 60115, United States
AU: Stepinski, T F
EM: tom@lpi.usra.edu
AF: Lunar and Planetary Institute, 3600 Bay Area Boulevard, Houston, TX 77058, United States
AB: In this study we demonstrate the plausibility of inferring the spatial variability of geology from topographically derived landscape dissection patterns. This enables surveying large regions for spatial variability in geology, for which direct remote sensing is not feasible, by studying variability in dissection pattern, a feature extracted straight off from remotely sensed topography. Dissection pattern is obtained automatically by a novel algorithm, especially designed to delineate the valleys with high accuracy in order to reflect spatial variability in dissection density. The dissection pattern is encapsulated by a continuous map of drainage density, a raster variable best suited for showing spatial variability of dissection. Such a map, constructed for the study area in the Cascade Range, Oregon, shows a sharp discontinuity in the dissection pattern, indicating change in underlying geology. We also check for climate and the local and regional slopes as possible factors controlling the dissection pattern, but geology has been found to be the dominant controlling factor on the basis of statistical analysis. As it happens the dissection contrast coincides with the boundary between the Western and High Cascades, two geologic provinces with different ages and rock types. Older and less permeable Western Cascades are associated with denser dissection pattern, whereas the younger and more permeable High Cascades correspond to less dissected pattern. We envision applying our mapping method to locations where remotely sensed topography is the only available data, and the generated map could be used to extract previously unknown geologic or environmental information.
DE: 1805 Computational hydrology
DE: 1819 Geographic Information Systems (GIS)
DE: 1855 Remote sensing (1640)
DE: 1856 River channels (0483, 0744)
DE: 5199 General or miscellaneous
SC: Hydrology [H]
MN: 2007 Fall Meeting