A Mixed Application of Geographically Weighted Regression and Unsupervised Classification for Analyzing Latex Yield Variability in Yunnan, China

KIB OpenIR > 离退休

	A Mixed Application of Geographically Weighted Regression and Unsupervised Classification for Analyzing Latex Yield Variability in Yunnan, China
	Kim, Oh Seok 1,7; Nugent, Jeffrey B.2; Yi, Zhuang-Fang 3,4; Newell, Joshua P.5; Curtis, Andrew J.6
	2017-05-01
发表期刊	FORESTS
卷号	8 期号:5 页码:162
关键词	Agricultural Yield Mixed Method Geographically Weighted Regression Iterative Self-organizing Data Analysis Technique Rubber Plantation Xishuangbanna Mekong Region
语种	英语
WOS记录号	WOS:000404099300024
引用统计
文献类型	期刊论文
条目标识符	http://ir.kib.ac.cn/handle/151853/54455
专题	离退休
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
推荐引用方式 GB/T 7714	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.
APA	Kim, Oh Seok,Nugent, Jeffrey B.,Yi, Zhuang-Fang,Newell, Joshua P.,&Curtis, Andrew J..(2017).A Mixed Application of Geographically Weighted Regression and Unsupervised Classification for Analyzing Latex Yield Variability in Yunnan, China.FORESTS,8(5),162.
MLA	Kim, Oh Seok,et al."A Mixed Application of Geographically Weighted Regression and Unsupervised Classification for Analyzing Latex Yield Variability in Yunnan, China".FORESTS 8.5(2017):162.

条目包含的文件		下载所有文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
forests-08-00162.pdf（3391KB）	期刊论文	作者接受稿	开放获取	CC BY-NC-SA	浏览下载