文献类型：期刊文献

中文题名：A partial least-squares regression approach to land use studies in the Suzhou-Wuxi-Changzhou region

英文题名：A partial least-squares regression approach to land use studies in the Suzhou-Wuxi-Changzhou region

作者：Zhang Yang[1,2];Zhou Chenghu[1];Zhang Yongmin[3]

第一作者：Zhang Yang

通讯作者：Zhang, Y[1]

机构：[1]Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China;[2]Chinese Acad Sci, Grad Sch, Beijing 100039, Peoples R China;[3]Henan Univ Finance & Econ, Dept Resources & Environm Sci, Zhengzhou 450002, Peoples R China

第一机构：Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China

通讯机构：[1]corresponding author), Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.

年份：2007

卷号：17

期号：2

起止页码：234-244

中文期刊名：地理学报：英文版

外文期刊名：JOURNAL OF GEOGRAPHICAL SCIENCES

收录：CSTPCD;;Scopus(收录号：2-s2.0-34247642310);WOS:【SCI-EXPANDED(收录号:WOS:000254941600010)】；CSCD:【CSCD2011_2012】；

基金：Received: 2006-12-01 Accepted: 2007-02-10 Foundation: National Natural Science Foundation of China; No.40301038 Author: Zhang Yang (1975-), Ph.D. Candidate, specialized in remote sensing, GIS, LUCC and geomorphology. E-mail: zhangyang@lreis.ac.cn

语种：英文

中文关键词：江苏;苏州-无锡-常州地区;土地利用研究;多变量数据分析;最小二乘偏回归法

外文关键词：land use; multivariate data analysis; partial least-squares regression; Suzhou-Wuxi-Changzhou region; multicollinearity

摘要：In several LUCC studies, statistical methods are being used to analyze land use data. A problem using conventional statistical methods in land use analysis is that these methods assume the data to be statistically independent. But in fact, they have the tendency to be dependent, a phenomenon known as multicollinearity, especially in the cases of few observations. In this paper, a Partial Least-Squares (PLS) regression approach is developed to study relationships between land use and its influencing factors through a case study of the Suzhou-Wuxi-Changzhou region in China. Multicollinearity exists in the dataset and the number of variables is high compared to the number of observations. Four PLS factors are selected through a preliminary analysis. The correlation analyses between land use and in- fluencing factors demonstrate the land use character of rural industrialization and urbaniza- tion in the Suzhou-Wuxi-Changzhou region, meanwhile illustrate that the first PLS factor has enough ability to best describe land use patterns quantitatively, and most of the statistical relations derived from it accord with the fact. By the decreasing capacity of the PLS factors, the reliability of model outcome decreases correspondingly.
In several LUCC studies, statistical methods are being used to analyze land use data. A problem using conventional statistical methods in land use analysis is that these methods assume the data to be statistically independent. But in fact, they have the tendency to be dependent, a phenomenon known as multicollinearity, especially in the cases of few observations. In this paper, a Partial Least-Squares (PLS) regression approach is developed to study relationships between land use and its influencing factors through a case study of the Suzhou-Wuxi-Changzhou region in China. Multicollinearity exists in the dataset and the number of variables is high compared to the number of observations. Four PLS factors are selected through a preliminary analysis. The correlation analyses between land use and influencing factors demonstrate the land use character of rural industrialization and urbanization in the Suzhou-Wuxi-Changzhou region, meanwhile illustrate that the first PLS factor has enough ability to best describe land use patterns quantitatively, and most of the statistical relations derived from it accord with the fact. By the decreasing capacity of the PLS factors, the reliability of model outcome decreases correspondingly.