2002 Fiscal Year Final Research Report Summary
Fundamental studies for intensive use of information obtained form biosphere
| Project/Area Number |
11460152
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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 |
生物資源科学
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| Research Institution | KYOTO UNIVERSITY |
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Principal Investigator |
MORIYA Kazuyuki Kyoto University, Graduate School of informatics, professor, 情報学研究科, 教授 (90159195)
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| Co-Investigator(Kenkyū-buntansha) |
NUMATA Kunihiko Kyoto University, Graduate School of informatics, associate professor, 情報学研究科, 助教授 (30026405)
ARAI Nobuaki Kyoto University, Graduate School of informatics, associate professor, 情報学研究科, 助教授 (20252497)
SAKAI Tetsuro Kyoto University, Graduate School of informatics, professor, 情報学研究科, 教授 (10101247)
KOBA Keisuke Kyoto University, Graduate School of informatics, assistant professor, 情報学研究科, 助手 (90311745)
YOSHIMURA Tetsuhiko Kyoto University, Graduate School of informatics, assistant professor, 情報学研究科, 助手 (40252499)
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| Project Period (FY) |
1999 – 2002
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| Keywords | Global Positioning System / Environmental Education / Image obtained from Satellite / Cattle grazing in the forest |
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| Research Abstract |
In this study, we developed the acquisition method of various data in biosphere using information and network techniques, and investigated the intensive use of these data.
1. GPS (global Positioning System) is one of the fundamental techniques to obtain the positioning data in the biosphere. In this study, we investigated the possibility of acquisition of positioning data in the forest, because GPS signal may be disturbed by crown or topography of mountain. We concluded that accuracy of positioning measurements using GPS were enough to use. We developed the environmental learning system using positioning data by GPS in the forest, and behavior of grazing cattle in the forest was investigated by GPS.
2. We developed a support system for collaborative environmental learning using distributed virtual space. The learner with GPS and PC in the real world (actual field) sent the position data and messages by way of network to the distributed virtual space, and both learners in the real world and virtual world communicated each other under this virtual space.
3. Remote sensing technique is one of the useful tools to predict of the amount of forest yield. In recently, high-density image obtained by satellite (IKONOS) can be utilized for this purpose. We processed the IKONOS photo of Iriomote Island and analyzed the distribution of mangrove forest in this area. Identification of mangrove area and spices of mangrove in this area are able to do using IKONOS image data.
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