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Forest Cover Classification from Multi-temporal MODIS Images in Southeast Asia Using Decision Tree

Abstract : MODIS data is of significant for the classification of regional forest cover due to its high temporal resolution and high spectral resolution. Forest cover is an important parameter for forest ecosystem. The objective of this preliminary study is to mapping forest cover from multi-temporal MODIS data with decision tree. The classification forest samples were selected from four global land cover datasets with specific rules. The selected samples were used to generate rules of the decision tree for the classification of forest cover. The study results show that multi-temporal remote sensing data with decision tree method have great potential to improve the regional forest cover mapping.
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Sijie Wu, Jianxi Huang, Xingquan Liu, Guannan Ma. Forest Cover Classification from Multi-temporal MODIS Images in Southeast Asia Using Decision Tree. 5th Computer and Computing Technologies in Agriculture (CCTA), Oct 2011, Beijing, China. pp.400-414, ⟨10.1007/978-3-642-27278-3_43⟩. ⟨hal-01361311⟩

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