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题名: A Mixed Application of Geographically Weighted Regression and Unsupervised Classification for Analyzing Latex Yield Variability in Yunnan, China
作者: Kim, Oh Seok1, 7; Nugent, Jeffrey B.2; Yi, Zhuang-Fang3, 4; Newell, Joshua P.5; Curtis, Andrew J.6
刊名: FORESTS
关键词: agricultural yield ; mixed method ; geographically weighted regression ; iterative self-organizing data analysis technique ; rubber plantation ; Xishuangbanna ; Mekong region
出版日期: 2017-05-01
卷号: 8, 期号:5, 页码:162
语种: 英语
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内容类型: 期刊论文
URI标识: http://ir.kib.ac.cn/handle/151853/54455
Appears in Collections:离退休_期刊论文

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作者单位: 1.Univ Southern Calif, Geog Doctoral Program, Los Angeles, CA 90089 USA
2.Univ Southern Calif, Dept Econ, Los Angeles, CA 90089 USA
3.Chinese Acad Sci, Kunming Inst Bot, Kunming 650201, Peoples R China
4.World Agroforestry Ctr ICRAF East & Cent Asia, Kunming 650201, Peoples R China
5.Univ Michigan, Sch Nat Resources & Environm, Ann Arbor, MI 48109 USA
6.Kent State Univ, Dept Geog, Kent, OH 44242 USA
7.Korea Environm Inst, Sejong 30147, South Korea

Recommended Citation:
Kim, Oh Seok,Nugent, Jeffrey B.,Yi, Zhuang-Fang,et al. A Mixed Application of Geographically Weighted Regression and Unsupervised Classification for Analyzing Latex Yield Variability in Yunnan, China[J]. FORESTS,2017,8(5):162.
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