Factors that contribute to the occurrence of shallow landslides due to rainfall include slope topography, the thickness of the ground surface soil layer, the geology of the soil layer, and the moisture conditions within it. In this study, the distribution of the canopy surface temperature as measured by a thermal infrared sensor was analyzed, and an efficient method to analyze the spatial distribution of moisture conditions in the soil layer was studied at the Sumiyoshi River basin in the Rokko Mountain Range, and the applicability of the method was evaluated. First, the data on the canopy surface temperature measured with a thermal infrared sensor was corrected using data on elevation and amount of solar radiation. The mean for the corrected surface temperatures were calculated for each subbasin area, covering from 0.03-0.15 km2 on the slope surface, and areas with decreased temperatures were determined using deviation values, which were obtained by subtracting the mean from the corrected value for each sub-area. The soil moisture was measured on-site, and it was found that the decreased temperature areas were determined based on deviation values coincided with the areas with high levels of measured soil moisture and lower slope surface adjacent to the areas. Next, a spatial correlation between the areas with decreased surface temperatures, landslide sites, and faults was analyzed. The results showed that new landslide sites caused by rainfall tended to coincide with areas with decreased surface temperatures. Within such areas, areas with smaller catchment areas tended to be concentrated near faults. These results suggest the possibility that areas identified as having lower canopy temperatures represent areas susceptible to landslides due to a concentration of groundwater and areas where groundwater gathers because of the geological structure there.
The prediction of location of deep catastrophic landslide is important to reduce such sediment disasters. Long-lasting, small-scale mass movements called gravitational mass rock creeps sometimes lead to deep catastrophic sliding. However, surface geometry of mass rock creep has not been fully clarified. Here we used LiDAR data to clarify the surface geometry of both the mass rock creep slope and non-mass rock creep slope quantitatively. We used slope angle and eigenvalue ratio for quantifying surface geometry. Moreover, we examined roles of window size to calculate slope angle and eigenvalue ratio. We showed optimal window size on characterize difference of surface geometry between mass rock creep and non-mass rock creep slope. At the mass rock creep, even if window size changed, the median value of slope gradient did not change. On the contrary, at the non-mass rock creep slope, the median value of slope gradient became small with the increase of window size. The hollows and steep slope around the mass rock creep is clear only when window size was smaller than１０m. Moreover, the eigenvalue ratio was the smallest, when the window size set as one-fourth to half of the intervals of convex at the mass rock creep.
In Japan, wide-scale measurement forsabo works was conducted from 2008 to 2010 using laser profilers (LPs) with a standard data format. These LP data provide detailed topographic information on areas prone to sediment-related disaster. Therefore, widespread use of these data is expected in crisis management and sabo work research. However, because software applications for LP data are lacking, these data are not effectively used at present. In this paper, we used LP topographic data to improve the accuracy of Kanako 2 D, GUI equipped debris flow simulations. We focused on a method to easily produce appropriate landform data for the simulation using the standard LP data maintained for current sabo works. We also concentrated on constructing a comprehensive debris flow simulation system based on a geographical information system (GIS) to enable visualization of the results. The use of accurate topographical data produced reasonable analytical results. This is a very useful tool for debris flow prediction and sabo planning. We refer to the system we developed as “Hyper KANAKO.”.
For accurate predictions of shallow landslide occurrences, it is essential to develop techniques which can efficiently detect locations of rainwater convergence within natural hillslopes. As one of such techniques, this study evaluated applicability of thermal infrared remote sensing. We studied a hillslope covered with a plantation of 40-year-old Japanese cedars, which showed relatively flat and homogeneous canopy surfaces. A thermal image of the forest canopy was taken during hot and dry daytime, by using an infrared thermography from a location 100-250 m distant from the studied hillslope. The image clearly detected some areas which showed lower canopy surface temperatures than surrounding areas. Along a line transecting both high-and low-canopy temperature areas, distributions of soil thickness and soil water content were measured by using a combined-penetrometer-moisture probe, and an electrical resistivity survey, which employed a dipole-dipole electrode arrangement, was conducted. As a result, the lower canopy temperature area showed higher soil water content and lower electrical resistivity than the high canopy temperature area, indicating that the thermal infrared remote sensing can be effectively used to detect locations of rainwater convergence within hillslopes, and, consequently, can be an efficient technique for locating slopes with high landslide-vulnerability. The result was supported by occurrences of two small landslides within the low canopy temperature area.