1990 Fiscal Year Final Research Report Summary
Studies on Resource Inventory and Environment Monitoring in Natural Forests
| Project/Area Number |
63860018
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| Research Category |
Grant-in-Aid for Developmental Scientific Research (B).
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| Allocation Type | Single-year Grants |
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| Research Field |
林学
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| Research Institution | The University of Tokyo |
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Principal Investigator |
MINOWA Mitsuhiro Univ. of Tokyo Fac. of Agric. Associate Prof., 農学部, 助教授 (60011996)
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| Co-Investigator(Kenkyū-buntansha) |
OHNUKI Itsuhito For. and Forest Prod. Res. Inst. Division Chief, 企画部長
TSUYUKI Satoshi Univ. of Tokyo Fac. of Agric. Assistant Prof., 農学部, 助手 (90217381)
YAMAMOTO Hirokazu Univ. of Tokyo Fac. of Agric. Associate Prof., 農学部(林), 助教授 (70174810)
WATANABE Sadamoto Univ. of Tokyo Fac. of Agric. Professor., 農学部(林), 教授 (30182918)
NAGUMO Hidejiro Univ. of Tokyo Fac. of Agric. Professor., 農学部, 教授 (30023401)
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| Project Period (FY) |
1988 – 1990
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| Keywords | Remote sensing / GIS (Geographic Information System) / Forest inventory / Environment monitoring / Forest Management / 04FREDAM (Forest Remote Sensing Data Analysis System on MS-DOS) |
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| Research Abstract |
1. Constructing an integrated forest management information system based on GIS (Geographic information system) and remote sensing techniques.
First, a simple GIS was constructed using forest registers, forest basic maps, forest type maps and other graphic data which have been gathered in the Tokyo University Forest in Hokkaido. Then, a remote sensing-based image processing system called FREDAM (Forest Remote Sensing Data Analysis System on MS-DOS) was developed, which allows the statistical processing and image processing of remote sensing data concerned with both artificial and natural forests.
2. A design of resource-environment monitoring system and its application to the management of natural forests.
First, the CVA (Change Vector Analysis) was made using Landsat TM data (aquired in 1984, 1987 and 1988) associated with the Tokyo University Forest in Chichibu, and it found useful for detecting harvested areas. Then, the Texture Analysis found it efficient to classify natural forest type based on crown density index in the Tokyo University Forest in Hokkaido. Finally, the satellite image map (scale : 1/50,000) of the natural forests was constructed through the RGB-HSV transformation of Multi-spectral data and Panchromatic data of SPOT. This map provides the clear image of real natural forests and plays an important role in managing and monitoring natural forests.
3. Some future technical problems such as information loss caused by cloud and shadow were discussed. Above all, the most important subject is to change our way of thinking and to place properly remote sensing technology in forest resource inventory and environment monitoring.
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