Optimization Model to Estimate Mount Tai Forest Biomass Based on Remote Sensing

Abstract : The development of low-carbon economy and the promotion of energy conservation are becoming a basic consensus of all countries. Therefore, global carbon cycle becomes a widespread concern research topic in scientific community. About 77% of the vegetation carbon stores in forest biomass in terrestrial ecosystems. So forest biomass is the most important parameter in terrestrial ecosystem carbon cycle. In this paper, for estimating the forest biomass of Mount Tai, a support vector machine (SVM) optimization model based on remote sensing is proposed. The meteorological data, terrain data, remote sensing data are taken into account in this model. In comparison the results of SVM with that of regressive analysis method, both the training accuracy and testing accuracy of regressive analysis method are lower than those of SVM, so SVM could obtain higher accuracy.
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Daoliang Li; Yingyi Chen. 5th Computer and Computing Technologies in Agriculture (CCTA), Oct 2011, Beijing, China. Springer, IFIP Advances in Information and Communication Technology, AICT-370 (Part III), pp.453-459, 2012, Computer and Computing Technologies in Agriculture V. 〈10.1007/978-3-642-27275-2_51〉
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Yanfang Diao, Chengming Zhang, Jiping Liu, Yong Liang, Xuelian Hou, et al.. Optimization Model to Estimate Mount Tai Forest Biomass Based on Remote Sensing. Daoliang Li; Yingyi Chen. 5th Computer and Computing Technologies in Agriculture (CCTA), Oct 2011, Beijing, China. Springer, IFIP Advances in Information and Communication Technology, AICT-370 (Part III), pp.453-459, 2012, Computer and Computing Technologies in Agriculture V. 〈10.1007/978-3-642-27275-2_51〉. 〈hal-01361172〉

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