Use of LIDAR‐derived images for mapping old landslides under forest

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 km 2 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. Figure 1. Location of the study area. The field survey-based landslides (n = 77) are shown on the LIDAR-derived hillshade map with sun elevation angle of 30° and sun azimuth angle of 315°. White arrow indicates landslide given to the experts as an example. 756 M. Van Den Eeckhaut et al.

Relationship between man-made environment and slope stability: the case of 2014 rainfall events in the terraced landscape of the Liguria region (northwestern Italy)

“…Due to the great extent and the complexity of the involved areas, we prevalently operated by exploiting LiDAR data. This procedure is confirmed by several authors who analysed ground surface processes by means of high-resolution DTMs (Glenn et al 2006;Ardizzone et al 2007;Haneberg et al 2009;Tarolli 2014;Pirasteh and Li 2016), also in forested areas (Eeckhaut et al 2007;Razak et al 2013;Chen et al 2014) and for large territories (Eeckhaut et al 2007). We employed a visual analysis methodology combining the highresolution DTM and orthoimages.…”

Use of LIDAR in landslide investigations: a review

“…The ALS-DEM allows a detailed delimitation of the landslides on the topographical surface (van den Eeckhaut et al 2007;Corsini et al 2009). Using these limits and the DEM, it is possible to infer the failure surface in 3D.…”

Review article: the use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management

“…The identification and mapping of landslides can be organized into landslide event maps. Landslide event mapping is a wellknown activity obtained through field surveys (Yoon et al, 2012;Santangelo et al, 2010), visual interpretation of aerial or satellite images (Brardinoni et al, 2003;Ardizzone et al, 2013) and combined analysis of lidar DTM and images (Van Den Eeckhaut et al, 2007;Haneberg et al, 2008;Giordan et al, 2013;Razak et al, 2013;Niculiţa, 2016). The use of RPASs for the identification and mapping of a landslide has been described by several authors (Niethammer et al, , 2010(Niethammer et al, , 2011Rau et al, 2011;Carvajal et al, 2011;Travelletti et al, 2012;Torrero et al, 2015;Casagli et al, 2017).…”