Analysis of Elevation Changes Detected from Multi-Temporal LiDAR Surveys in Forested Landslide Terrain in Western Oregon

Abstract

Research Article| November 01, 2010 Analysis of Elevation Changes Detected from Multi-Temporal LiDAR Surveys in Forested Landslide Terrain in Western Oregon WILLIAM J BURNS; WILLIAM J BURNS 1Oregon Department of Geology and Mineral Industries, 800 NE Oregon Street, Portland, OR 97232 Search for other works by this author on: GSW Google Scholar JEFFREY A COE; JEFFREY A COE 2U.S. Geological Survey, Denver Federal Center, Mail Stop 966, Denver, CO 80225 Search for other works by this author on: GSW Google Scholar BASAK SENER KAYA; BASAK SENER KAYA 3Colorado School of Mines, Division of Engineering, Golden, CO 80401 Search for other works by this author on: GSW Google Scholar LINA MA LINA MA 4Oregon Department of Geology and Mineral Industries, 800 NE Oregon Street, Portland, OR 97232 Search for other works by this author on: GSW Google Scholar Author and Article Information WILLIAM J BURNS 1Oregon Department of Geology and Mineral Industries, 800 NE Oregon Street, Portland, OR 97232 JEFFREY A COE 2U.S. Geological Survey, Denver Federal Center, Mail Stop 966, Denver, CO 80225 BASAK SENER KAYA 3Colorado School of Mines, Division of Engineering, Golden, CO 80401 LINA MA 4Oregon Department of Geology and Mineral Industries, 800 NE Oregon Street, Portland, OR 97232 Publisher: Association of Environmental & Engineering Geologists First Online: 02 Mar 2017 Online ISSN: 1558-9161 Print ISSN: 1078-7275 Copyright © 2010 EEGS Environmental & Engineering Geoscience (2010) 16 (4): 315–341. https://doi.org/10.2113/gseegeosci.16.4.315 Article history First Online: 02 Mar 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation WILLIAM J BURNS, JEFFREY A COE, BASAK SENER KAYA, LINA MA; Analysis of Elevation Changes Detected from Multi-Temporal LiDAR Surveys in Forested Landslide Terrain in Western Oregon. Environmental & Engineering Geoscience 2010;; 16 (4): 315–341. doi: https://doi.org/10.2113/gseegeosci.16.4.315 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyEnvironmental & Engineering Geoscience Search Advanced Search Abstract We examined elevation changes detected from two successive sets of Light Detection and Ranging (LiDAR) data in the northern Coast Range of Oregon. The first set of LiDAR data was acquired during leaf-on conditions and the second set during leaf-off conditions. We were able to successfully identify and map active landslides using a differential digital elevation model (DEM) created from the two LiDAR data sets, but this required the use of thresholds (0.50 and 0.75 m) to remove noise from the differential elevation data, visual pattern recognition of landslide-induced elevation changes, and supplemental QuickBird satellite imagery. After mapping, we field-verified 88 percent of the landslides that we had mapped with high confidence, but we could not detect active landslides with elevation changes of less than 0.50 m. Volumetric calculations showed that a total of about 18,100 m3 of material was missing from landslide areas, probably as a result of systematic negative elevation errors in the differential DEM and as a result of removal of material by erosion and transport. We also examined the accuracies of 285 leaf-off LiDAR elevations at four landslide sites using Global Positioning System and total station surveys. A comparison of LiDAR and survey data indicated an overall root mean square error of 0.50 m, a maximum error of 2.21 m, and a systematic error of 0.09 m. LiDAR ground-point densities were lowest in areas with young conifer forests and deciduous vegetation, which resulted in extensive interpolations of elevations in the leaf-on, bare-earth DEM. For optimal use of multi-temporal LiDAR data in forested areas, we recommend that all data sets be flown during leaf-off seasons. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.