2000 Fiscal Year Final Research Report Summary
Development of a vegetation environment classification method based on degree of urbanization
Project/Area Number |
11660142
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Single-year Grants |
Section | 一般 |
Research Field |
林学
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Research Institution | THE UNIVERSITY OF TOKYO |
Principal Investigator |
TSUYUKI Satoshi Graduate School of Agricultural and Life Sciences, Department of Global Agricultural Sciences, THE UNIVERSITY OF TOKYO Associate Professor, 大学院・農学生命科学研究科, 助教授 (90217381)
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Project Period (FY) |
1999 – 2000
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Keywords | Landsat TM / rate of forest area / rate of agricultural area / population density / 3rd-order mesh / cluster analysis |
Research Abstract |
A new method concerning vegetation environment classification based on degree of urbanization was developed using population density, vegetation (natural) area and agricultural area data. Classification was done by cluster analysis of descending-order curves made from population density and vegetation area within 5km radius from each pixel, using 3rd-order mesh of National Digital Information. To manage different dynamic ranges between these data, a new scaling method was developed, which made able to apply this new classification method to any part and/or whole area of Japan. Although National Population Survey has been conducted 5 years interval, digital landuse information was not updated since 1990. To apply this new classification method periodically, Kinki district was selected as a test site, and Landsat TM data was used to get updated information of landuse area. First, one scene of TM data of 1989 were classified and aggregated into 3rd-order mesh to test land cover classification accuracy comparing with digital landuse information. As this result was successful, land cover of 1995 were classified using TM data of 1996, and vegetation environment classification method was applied using 1995 National Population Survey data. By this research, the new vegetation environment classification method was proved to be able to apply periodically to fine changes concerning vegetational environment, using Landsat TM data and National Population Survey data.
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