Hiromitsu Yamagishi

GIS Analysis of Heavy-Rainfall Induced Shallow Landslides in Japan

Heavy rainfall often triggers shallow landslides (slope failures) in Japan. In addition, the Geographical Survey Institute (GSI) now provides digital elevation data and digital geological maps from the Geological Survey of Japan are also available. Hence using GIS, we analysed the distribution of heavy-rainfall induced shallow landslides at six locations (Fig. 1) in relation to slope gradient.

TXT-tool 1.081-6.1 A Comparative Study of the Binary Logistic Regression (BLR) and Artificial Neural Network (ANN) Models for GIS-Based Spatial Predicting Landslides at a Regional Scale

This teaching tool is to present how to generate the landslide susceptibility maps using binary logistic regression (BLR) and artificial neural network (ANN) methods at a regional scale. The study area is one of most landslide-prone areas in Japan. First, the landslide inventory data from the National Research Institute for Earth Science and Disaster Prevention (NIED) were randomly partitioned into two parts: training and testing data. Then, 10 m DEM data and geology map were analyzed to extract the landslide predisposing factors. Next, the susceptibility maps were produced in a geographic information system (GIS) environment. Then, the receiver operating characteristics (ROC) was used to assess the model accuracy. Validation results show that both of two methods can be obtained with acceptable results. The maps can provide useful information for the future planning of hazard mitigation.

Spatial Comparison of Two High-resolution Landslide Inventory Maps Using GIS—A Case Study of the August 1961 and July 2004 Landslides Caused by Heavy Rainfalls in the Izumozaki Area, Niigata Prefecture, Japan

The spatial distribution of shallow landslides in the Izumozaki area, Niigata, caused by the heavy rainfalls in August 1961 and July 2004 was investigated using high-resolution ortho-photoimagery and a 2-m DEM. We found that the number of the August 1961 landslides is more than twice the July 2004 landslides. More than half of the July 2004 landslides (about 70% as the number ratio and 54% as the area ratio) were primary landslides. These primary landslides seem to occur randomly regardless of the geological structure of the stratum. The large landslides which occurred in July 2004 were often expanded landslides immediately higher than the August 1961 landslides. These expanded landslides often occurred on daylighting dip slopes. Among the July 2004 landslides, the ratio of landslides along roads is very high compared to 1961 (1961: 4.2%; 2004: 16.4%).

Characteristics of the Torrential Rainfall-Induced Shallow Landslides by Typhoon Bilis, in July 2006, Using Remote Sensing and GIS

During July 14–16, 2006 Typhoon Bilis swept over the southern China. The typhoon brought torrential downpour, resulting in many shallow landslides in the region. This study describes the characteristics of the landslides in an area around the Dongjiang Reservoir, Hunan Province, which was seriously affected by the event. We sketch the landslide occurrences and extreme rainfall event in the study area based on the high-resolution QuickBird images, medium-scale China-Brazil Earth Resources Satellite (CBERS) images, rain gauge data, a digital elevation model, and field surveys. All the satellite images, rain gauge points, geological maps, and field notes were processed and constructed into a spatial database in a GIS platform. The landslide occurrences in the study area before the event was low, and significantly increased during and after Typhoon Bilis of 2006. The short duration, high-intensity rainfall was the major triggering factor. In addition, topographical factors such as slope and aspect also contributed to landslide occurrence. The combined influence of rainfall and the topographic factors. The paper attempts to provide a better understanding of the rainfall and causative factors of landslides in the wake of typhoon Bilis.