摘要
To mitigate the damage caused by debris flows resulting from heavy precipitation and to aid in evacuation plan preparation, areas at risk should be mapped on a scale appropriate for affected individuals and communities. We tested the effectiveness of simply identifying debris-flow hazards through automated derivation of surface curvatures using LiDAR digital elevation models. We achieved useful correspondence between plan curvatures and areas of existing debris-flow damage in two localities in Japan using the analysis of digital elevation models(DEMs). We found that plan curvatures derived from 10 m DEMs may be useful to indicate areas that are susceptible to debris flow in mountainous areas. In residential areas located on gentle sloping debris flow fans, the greatest damage to houses was found to be located in the elongated depressions that are connected to mountain stream valleys. Plan curvaturederived from 5 m DEM was the most sensitive indicators for susceptibility to debris flows.
To mitigate the damage caused by debris flows resulting from heavy precipitation and to aid in evacuation plan preparation, areas at risk should be mapped on a scale appropriate for affected individuals and communities. We tested the effectiveness of simply identifying debris-flow hazards through automated derivation of surface curvatures using LiDAR digital elevation models. We achieved useful correspondence between plan curvatures and areas of existing debris-flow damage in two localities in Japan using the analysis of digital elevation models(DEMs). We found that plan curvatures derived from 10 m DEMs may be useful to indicate areas that are susceptible to debris flow in mountainous areas. In residential areas located on gentle sloping debris flow fans, the greatest damage to houses was found to be located in the elongated depressions that are connected to mountain stream valleys. Plan curvaturederived from 5 m DEM was the most sensitive indicators for susceptibility to debris flows.
基金
supported by the Crisis Management division of Toho village, and JSPS KAKENHI Grant Number (18K04660)