| Project/Area Number |
11680467
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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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 | Shiga University |
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Principal Investigator |
ITAKURA Yasumasa ShigaUniversity, Faculty of Education, Professor, 教育学部, 教授 (20027824)
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| Co-Investigator(Kenkyū-buntansha) |
INABA Hiroyuki Kyoto Institute of Technology Assoc. Professor, 工芸学部, 助教授 (40243117)
SAWADA Toyoaki Kyoto University, RIDP Assoc. Professor, 防災研究所, 助教授 (60027258)
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| Project Period (FY) |
1999 – 2001
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| Project Status |
Completed (Fiscal Year 2001)
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| Budget Amount *help |
¥3,400,000 (Direct Cost: ¥3,400,000)
Fiscal Year 2001: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 2000: ¥600,000 (Direct Cost: ¥600,000)
Fiscal Year 1999: ¥2,000,000 (Direct Cost: ¥2,000,000)
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| Keywords | debris-flow detection / microphone sensor / oil-immersed acoustic sensor / improved hydrophone sensor / computer-based spatial filtering velocimetry / MPEG method / spatio-temporal derivative space method / cross-correlation method / 改良型水中マイクロホン / 計算機対応空間フィルタ速度計測 / MPEG画像処理法土石流検知 / 時空勾配空間法速度推定 / 土石流検出 / 振動センサ / 空間フィルタ速度計測 / MPEG画像処理法 / 時空勾配空間法 / マイクロフォンセンサ |
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| Research Abstract |
The purpose of this research is to develop a new monitoring system to prevent and to mitigate debris-flow hazards. The results of this research during three years are as follows:
1. An acoustic sensor with a microphone inside a pipe set underground has a high signal-to-noise ratio compared with other ground vibration sensors, seismometer, piezoelectric sensor, or moving-coil sensor. An improved acoustic sensor having a microphone immersed in oil inside the pipe shows a possibility of twice detection range.
2. A digital image processing based on video images of debris flow can make a proximity-detection by utilizing a detection algorithm of MPEG motion vectors. Another digital image processing methods such as computer-based spatial filtering velocimetry, spatio-temporal derivative space method, or cross-correlation method can estimate surface velocity of debris flow.
3. A combination system of an acoustic sensor and an image-processing method may have a good performance of debris-flow monitoring. The acoustic sensor may compensate the image processing under a bad weather condition of deep fog or heavy rain : on the other hand, the image-processing method makes clear the real image of debris flow, which the acoustic sensor can't observe. Unfortunately, the feasibility test of this combination system has not been confirmed because debris flows have not occurred in a test torrent.
4. A workshop on debris flow monitoring was held at the Swiss National Hydrological and Geological Survey in Ittigen-Bern, Switzerland, on 5-6 November 2001 by partial supporting of this found. The results of this research were presented in the workshop and took a good evaluation in viewing future monitoring of debris flow.
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