Abstract
This study aims to create a terrain classification of Japan that allows both geomorphological and geoengineering classifications coexist without large contradictions and to distinguish landform elements even in urban plains which include noise associated with digital elevation models (DEMs). Because Japan is susceptible to natural disasters, we designed the classification to reflect the ground vulnerability of both alluvial plains and mountains through the application of terrain classification data to landslide susceptibility and seismic zoning. We updated an existing DEM-based terrain classification method for application in the high-resolution 30 m DEM. We used topographic measurements that do not amplify manmade unevenness or noise, which are usually the main problems associated with the use of high-resolution DEMs with high vertical accuracies. We selected the height above the nearest drainage (HAND), slope gradient, surface texture, and local convexity as geometric signatures, which were devised so as not to detect noise. Segment polygon data of terrain units were derived from the raster data of slope and HAND. The polygon data were classified into 40 clusters using the attributes of slope, HAND, and surface texture; then they were grouped into 16 legends following comparisons with the existing geological and geomorphological maps and supplementary reclassification by HAND and local convexity. The derived terrain classification, except for manmade cuts and fills, showed similarities with the existing expert-driven maps and some association with areas where shallow landslides or floods frequently occur. Based on a trial in California using a 30 m DEM, we concluded that the proposed method can be adopted in other regions outside of Japan.
Highlights
1 Introduction Geomorphological maps that delineate the topography of similar shapes and similar formation processes have been produced in many countries to estimate the ground strength and establish plans for flood and sediment disaster prevention and regional development
Many geomorphological classification methods ranging from landform elements of mountain slopes (MacMillan et al 2000, 2003; Reuter et al 2006; Jasiewicz and Stepinski 2013) to landform patterns (Prima et al 2006; Saadat et al 2008) have been developed, and geomorphological mapping of global physiography at various scales has been proposed for several applications (Meybeck et al 2001; Iwahashi and Pike 2007; Drăguţ and Eisank 2012; Sayre et al 2014; Iwahashi et al 2018a)
Compared to the previous cellbased study (Iwahashi and Pike 2007), the approach in this study significantly improved the extraction of landform elements in the plains in 30 m Digital elevation model (DEM), even in areas with a large population and manmade cuts and fills, such as the capital area (Fig. 15a)
Summary
Geomorphological maps that delineate the topography of similar shapes and similar formation processes have been produced in many countries to estimate the ground strength and establish plans for flood and sediment disaster prevention and regional development. To create a geomorphological map, experts classify the topography by interpolating aerial photographs and other data such as satellite imagery and clarify the differences in causes, constituent materials, and time of formation using field surveys and other references This type of labor-intensive work is not feasible over a wide area. Iwahashi and Pike (2007) classified the terrains by threshold processing using the raster data of the three geometric signatures (Fig. 1) Applications of this pixelbased terrain classification are mainly proxy for site classes of earthquake shaking (Yong et al 2012; Irsyam et al 2017; Parker et al 2017), or for soil type estimation (European Commission – DG JRC 2008)
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