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Estimation of Aboveground Biomass Carbon Stock in Danyang Area using kNN Algorithm and Landsat TM Seasonal Satellite Images  

Jung, Jae-Hoon (연세대학교 토목환경공학과)
Heo, Joon (연세대학교 토목환경공학과)
Yoo, Su-Hong (연세대학교 토목환경공학과)
Kim, Kyung-Min (국립산림과학원)
Lee, Jung-Bin (국립산림과학원)
Publication Information
Journal of Korean Society for Geospatial Information Science / v.18, no.4, 2010 , pp. 119-129 More about this Journal
Abstract
The joint use of remotely sensed data and field measurements has been widely used to estimate aboveground carbon stock in many countries. Recently, Korea Forest Research Institute has developed new carbon emission factors for kind of tree, thus more accurate estimate is possible. In this study, the aboveground carbon stock of Danyang area in South Korea was estimated using k-Nearest Neighbor(kNN) algorithm with the 5th National Forest Inventory(NFI) data. Considering the spectral response of forested area under the climate condition in Korea peninsular which has 4 distinct seasons, Landsat TM seasonal satellite images were collected. As a result, the estimated total carbon stock of Danyang area was ranged from 3542768.49tonC to 3329037.51tonC but seasonal trends were not found.
Keywords
Landsat TM; NFI; kNN; Carbon stock; Carbon map;
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Times Cited By KSCI : 3  (Citation Analysis)
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