| Project/Area Number |
25750152
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Natural disaster / Disaster prevention science
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| Research Institution | Kagawa University |
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Principal Investigator |
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| Co-Investigator(Renkei-kenkyūsha) |
HASEGAWA Shuichi 香川大学, 工学部, 教授 (00325317)
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| Project Period (FY) |
2013-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2015: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2014: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2013: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | 深層崩壊 / 地形 / DEM / 地すべり / 地すべり地形 / 前兆地形 |
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| Outline of Final Research Achievements |
Landslides tend to occur on gravitationally deformed slopes, and the distribution of slopes with deep-seated gravitational deformation is primary information for efforts to predict and mitigate landslide damage. Recently developed semi-automatic procedures for recognizing landforms related to earth surface processes reliably delineate landslide crowns, but other surface features typify slopes with histories of complex landslides, particularly deep-seated retrogressive slides. It is desirable to have automatic or semi-automatic procedures for identifying other topographic features beside landslide crowns. We present a simple algorithm for extracting topographic features of slopes that are susceptible to landslides, especially retrogressive rotational and translational landslides, from a digital elevation model.
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