Construction of Real-time Inference System for Key Hazard Extent Distribution on the Ground caused by Earthquakes (RISKHEDGE)
1Kamiya, I.; 2Nakano, T.; 4Otoi, K.; 4Nakajima, H.
Though rough grasping of disaster damages is important to plan early countermeasures, seriousness of damages by a large earthquake is not easy to be grasped just after the strike. For example, seriousness of the Southern Hyogo prefecture earthquake in 1995, Japan was recognized after on-the-spot live TV broadcasting from helicopters. Therefore, we developed “Real-time Inference System for Key Hazard Extent Distribution on the Ground caused by Earthquakes (RISKHEDGE)” (hereafter referred as new name “Seismic Ground Disaster Assessment System (SGDAS)”) to estimate quickly the seriousness of slope failures, landslides with sliding surface (hereafter referred as “slides”), and soil liquefaction caused by an earthquake. SGDAS infers the seriousness of damages by using estimated seismic intensity of the earthquake and geographic information gathered in advance. Next, this system generates graphical report and inform them by e-mail within 15 minutes after the main shock of the earthquake. The estimated seismic intensity is raster data of raw JMA (Japan Meteorological Agency) seismic intensity scale which is interpolated by JMA considering difference of ground property. The original data of the interpolation is raw JMA seismic intensity scale observed by the seismometer network over Japan. Because the estimated seismic intensity is sometimes underestimated near the epicenter, SGDAS modifies the estimated seismic intensity before the execution of inference for each types of disaster. A distance-decay model is used for the modification, and interpolation error is also estimated. So, the estimated seismic intensity is increase only within the estimated error. On the other hand, the estimated seismic intensity is not decreased. Seriousness of slope failures is inferred by the estimated seismic intensity, slope and curvature of ground. The original algorithm was developed using data of the Southern Hyogo prefecture earthquake in 1995 in the west of Japan. We modified the algorithm to accept wider range of input values and to execute the calculation in real-time. We also modified it to consider geological condition, that is, the implementation is simply increase the rank of seriousness one step if the area is covered by week types of geology like Neogene or later sediments. The 10-m grid DEM data produced by Geospatial Information Authority of Japan and Seamless Digital Geological Map produced by National Institute of Advanced Industrial Science and Technology in Japan are used for the inference. Though some of slides are reactivation of existing slides and the others are newly engendered, slides caused by earthquake are located near existing slides like 1 km or closer. Since GIS data of landslide distribution maps by National Research Institute for Earth Science and Disaster Prevention in Japan is available almost all over Japan, seriousness of slides is inferred by the estimated seismic intensity and area coverage ratio of slides calculated by the GIS data of landslide distribution maps. The area coverage ratio is calculated using Gaussian filter, and its weight is higher if geology is same in Seamless Digital Geological Map. Seriousness of soil liquefaction is inferred by the estimated seismic intensity scale and geomorphological classification. SGDAS uses GIS-based 7.5-arc-second Japan engineering geomorphologic classification data (Wakamatsu and Matsuoka, 2009) and some geomorphologic categories are subclassified using DEM. Rank of seriousness is determined by a table consisting of relationship between seismic intensity scale and geomorphological classification. SGDAS has been stably operated since 2013, and have been used in Geospatial Information Authority of Japan.