Use of LIDAR‐derived images for mapping old landslides under forest |
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| Authors: | M Van Den Eeckhaut J Poesen G Verstraeten V Vanacker J Nyssen J Moeyersons L P H van Beek L Vandekerckhove |
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| Institution: | 1. Physical and Regional Geography Research Group, K.U. Leuven, Belgium;2. Fund for Scientific Research, Flanders, Belgium;3. Geography Department, U.C.L., Belgium;4. Royal Museum for Central Africa, Tervuren, Belgium;5. Department of Physical Geography, Utrecht University, The Netherlands;6. Land Division, Ministry of Flanders, Belgium |
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| Abstract: | Large, deep‐seated landslides are common features in the Flemish Ardennes (Belgium). As most of these old (>100 years) landslides are located under forest in this hilly region, aerial photograph interpretation is not an appropriate landslide mapping method. This study tested the potential of LIDAR (Light Detection and Ranging) images for mapping old landslides under forest. Landslide inventory maps were created for a 125 km2 area by applying the expert knowledge of seven geomorphologists to LIDAR‐derived hillshade, slope and contour line maps in a GIS environment. Each of the seven LIDAR‐based landslide inventories was compared (i) with the other six, (ii) with a detailed field survey‐based inventory, and (iii) with a comparable study in which topographic data were extracted from a topographical map. The combination of the percentage of field landslides indicated by an expert and the percentage of positional discrepancies (expressed in terms of positional mismatch) were used to evaluate the quality of the LIDAR‐based inventory maps. High‐quality LIDAR‐derived landslide inventory maps contain more than 70 per cent of the landslides mapped during the field survey, and have positional discrepancies smaller than 70 per cent when compared with the field survey‐based inventory map. Four experts and the combination map of all experts satisfied these criteria. Together the seven experts indicated all landslides mapped in the field. Importantly, LIDAR enabled the experts to find ten new landslides and to correct the boundaries of eleven (of the 77) landslides mapped during the field survey. Hence, this study showed that large‐scale LIDAR‐derived maps analysed by experienced geomorphologists can significantly improve field survey‐based inventories of landslides with a subdued morphology in hilly regions. Copyright © 2006 John Wiley & Sons, Ltd. |
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| Keywords: | old deep‐seated landslides landslide inventory map LIDAR expert know‐ledge hillshade map |
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