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学科主题: Remote Sensing; Imaging Science & Photographic Technology
题名: Determination of ocean primary productivity using support vector machines
作者: Tang, S ; Chen, C ; Zhan, H ; Zhang, T
通讯作者: sltang@scsio.ac.cn
刊名: INTERNATIONAL JOURNAL OF REMOTE SENSING
发表日期: 2008
卷: 29, 期:21, 页:6227-6236
收录类别: sci
部门归属: [Tang, S.; Chen, C.; Zhan, H.; Zhang, T.] Chinese Acad Sci, S China Sea Inst Oceanol, LED, Guangzhou 510301, Guangdong, Peoples R China; [Tang, S.] Chinese Acad Sci, Grad Univ, Beijing 100049, Peoples R China
项目归属: LED
摘要: A major task of ocean colour observations is to determine the distribution of phytoplankton primary production. At present, the global coverage of the sea surface chlorophyll concentration, sea surface temperature, photosynthetically available radiation (PAR) can nominally be achieved every 1 to 2 days with standard algorithms from satellite data. From these standard products, a variety of bio-optical algorithms has been developed to estimate ocean primary productivity. In this communication, we have investigated the possibility of using a novel universal approximator-support vector machine (SVM) as the nonlinear transfer function between ocean primary productivity and the information that can be retrieved from satellite data, including chlorophyll concentration, PAR, maximum carbon fixation rate and day length, which is the same as the vertically generalized production model (VPGM). The VGPM dataset was used to evaluate the proposed approach. The primary production algorithm round robin 2 (PPARR2) dataset was used to further compare the precision between the VGPM and the SVM model. The results suggest that the SVM model is more accurate than the VGPM. Using the SVM model to calculate the global ocean primary productivity, the result is 45.5PgCyr(-1), which is a little higher than the VGPM result.
WOS记录号: WOS:000260326200012
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.scsio.ac.cn/handle/344004/5947
Appears in Collections:热带海洋环境动力实验室(LTO)_期刊论文

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Recommended Citation:
Tang, S; Chen, C; Zhan, H; Zhang, T.Determination of ocean primary productivity using support vector machines,INTERNATIONAL JOURNAL OF REMOTE SENSING,2008,29(21):6227-6236
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