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http://dx.doi.org/10.11108/kagis.2011.14.3.236

Overview of Research Trends in Estimation of Forest Carbon Stocks Based on Remote Sensing and GIS  

Kim, Kyoung-Min (Division Forest Resources Information, Korea Forest Research Institute)
Lee, Jung-Bin (Division Forest Resources Information, Korea Forest Research Institute)
Kim, Eun-Sook (Division Forest Resources Information, Korea Forest Research Institute)
Park, Hyun-Ju (Environmental Strategy Research Group, Korea Environment Institute)
Roh, Young-Hee (Dept. Geography, Seoul National University)
Lee, Seung-Ho (Division Forest Resources Information, Korea Forest Research Institute)
Park, Key-Ho (Dept. Geography, Seoul National University)
Shin, Hyu-Seok (Institute for Korean Regional Studies, Seoul National University)
Publication Information
Journal of the Korean Association of Geographic Information Studies / v.14, no.3, 2011 , pp. 236-256 More about this Journal
Abstract
Forest carbon stocks change due to land use change is an important data required by UNFCCC(United Nations framework convention on climate change). Spatially explicit estimation of forest carbon stocks based on IPCC GPG(intergovernmental panel on climate change good practice guidance) tier 3 gives high reliability. But a current estimation which was aggregated from NFI data doesn't have detail forest carbon stocks by polygon or cell. In order to improve an estimation remote sensing and GIS have been used especially in Europe and North America. We divided research trends in main countries into 4 categories such as remote sensing, GIS, geostatistics and environmental modeling considering spatial heterogeneity. The easiest way to apply is combination NFI data with forest type map based on GIS. Considering especially complicated forest structure of Korea, geostatistics is useful to estimate local variation of forest carbon. In addition, fine scale image is good for verification of forest carbon stocks and determination of CDM site. Related domestic researches are still on initial status and forest carbon stocks are mainly estimated using k-nearest neighbor(k-NN). In order to select suitable method for forest in Korea, an applicability of diverse spatial data and algorithm must be considered. Also the comparison between methods is required.
Keywords
Forest Carbon Stocks; Forest Biomass; Remote Sensing; GIS; Geostatistics; National Forest Inventory;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
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