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- W2561304410 abstract "Landform Classification maps are used in many areas such as disaster damage assessment, developmental conformity evaluation, and environmental study. For the high resource demand of the classification processes, such maps are not available in many regions including developing countries. Our ongoing research focuses on providing Landform Classification maps for those regions using DEM which is easily obtainable by remote sensing technology. In this paper, we propose an algorithm that extracts alluvial fans, an element of our landform classification, from readily available DEM supplied by SRTM. Then we tested the algorithm over the entire area of Japan, and found that the results were consistent with existing classification maps in terms of the number, size, and location of the alluvial fans extracted, thus confirming the applicability to the regions without classification maps." @default.
- W2561304410 created "2017-01-06" @default.
- W2561304410 creator A5081263963 @default.
- W2561304410 date "2009-01-01" @default.
- W2561304410 modified "2023-09-24" @default.
- W2561304410 title "Building Landform Classification Maps from DEM: Alluvial Fan Extraction Method Taewoon KIM, Byeongpyo JEONG, Osamu TAKIZAWA and Masafumi HOSOKAWA" @default.
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- W2561304410 hasPublicationYear "2009" @default.
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