| Project/Area Number |
16310124
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Natural disaster science
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| Research Institution | Chiba University |
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Principal Investigator |
NAKAI Shoichi Chiba University, Faculty of Engineering, Professor, 工学部, 教授 (90292664)
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| Co-Investigator(Kenkyū-buntansha) |
KONDOH Akihiko Chiba University, Center for Environmental Remote Sensing, Professor, 環境リモートセンシング研究センター, 教授 (30201495)
ISHIDA Riei Chiba University, Faculty of Engineering, Research Associate, 工学部, 助手 (30293674)
清水 善久 東京ガス株式会社, 導管ネットワーク本部・導管部, 導管グループマネージャー
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| Project Period (FY) |
2004 – 2005
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| Project Status |
Completed (Fiscal Year 2005)
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| Budget Amount *help |
¥10,100,000 (Direct Cost: ¥10,100,000)
Fiscal Year 2005: ¥4,400,000 (Direct Cost: ¥4,400,000)
Fiscal Year 2004: ¥5,700,000 (Direct Cost: ¥5,700,000)
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| Keywords | Micro Landform Classification / Land Use Classification / Seismic Risk / Surface Soil Structure / Remote Sensing / Knowledge-based Inference |
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| Research Abstract |
The knowledge about the condition of the ground is a crucial factor that controls damage due to natural disasters. However, to collect information on the ground condition over a wide area is not an easy task. In order to solve this issue, the following topics have been discussed in this research :
1. Land use classification
By combining land use data digitized from maps in the old times and those obtained from satellite data in the present time, a land use database has been constructed on a geographical information system (GIS). In this study, the satellite image classification is based on image objects rather than individual pixels.
2. Landform classification
Based on the land use and its change, landform classification has been obtained by applying inference rules. These inference rules are the relationship between the two classifications and was constructed based on the knowledge about geomorphology.
3. Surface soil structure
A number of boring logs have been collected to construct a boring log database. Based on this database together with the landform classification, typical soil profiles have been selected for each landform classification. This set of soil profiles can be considered to represent a surface soil structure in the target area in this research (Chiba city).
4. Seismic risk assessment
Based on this surface soil model, seismic risk assessment has been conducted. In addition, a series of microtremor measurement and also earthquake observation have been carried out. According to these studies, it was found that dynamic properties of the ground and hence the seismic risk are strongly affected by local land form and soil conditions.
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