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Qualitative and quantitative assessments of input LiDAR data for landslide inventory mapping

An innovative technique for detailed landslide inventory mapping is airborne laser scanning and LiDAR-derived DTMs in high resolution. LiDAR data used in this study was obtained in the framework of the “Methodology development for landslide susceptibility assessment for land use planning based on LiDAR technology (LandSlidePlan IP-2019- 04-9900)” project fully supported by the Croatian Science Foundation. To select the optimal digital terrain model (DTM) for landslide delineation, quantitative and qualitative assessments were done individually for three landslides. The quantitative assessment included a comparison of minimum, maximum, mean, and standard deviation values of DTMs derived by using four interpolation methods (Kriging, IDW, Natural Neighbor, and ANUDEM) in six raster resolutions (0.15, 0.3, 0.5, 1, 2, and 5 m). Furthermore, by comparing point cloud LiDAR data and interpolated DTMs elevation values, the mean-absolute-error difference (MAE) and root-mean-square-error (RMSE) were calculated. Hillshade, roughness, and curvature morphometric maps were derived for 24 DTMs per landslide, resulting in the qualitative assessment of 216 different morphometric maps. The quantitative assessment showed minimum and negligible differences between DTMs for landslide areas ; therefore, the qualitative assessment prioritised determining the optimal DTM for deriving morphometric maps needed for landslide delineation. Based on visual interpretability of landslide parts (i.e. crown, ridges, and toe) and the terrain quality (i.e. expressed details, irregularities, and blurriness) on the derived morphometric maps, the LiDAR DTM derived using the Kriging method in 0.3 m resolution was selected for landslide inventory mapping in further studies.

landslide mapping ; landslide inventory map ; LiDAR ; qualitative assessment ; quantitative assessment

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