Prediction of soil salinity in the Yellow River Delta using geographically weighted regression

doi:10.1080/03650340.2016.1249475

	Prediction of soil salinity in the Yellow River Delta using geographically weighted regression
	Wu, Chunsheng 1,2; Liu, Gaohuan 1; Huang, Chong 1
刊名	ARCHIVES OF AGRONOMY AND SOIL SCIENCE
	2017-06-01
卷号	63 期号:7 页码:928-941
关键词	Salinization local regression model environmental variables spatial interpolation Yellow River Delta
ISSN号	0365-0340
DOI	10.1080/03650340.2016.1249475
通讯作者	Huang, Chong(huangch@lreis.ac.cn)
英文摘要	It is essential to determine the content and spatial distribution of soil salinity in a timely manner because soil salinization can cause land degradation on a regional scale. Geographically weighted regression (GWR) is a local regression method that can achieve the spatial extension of dependent variables based on the relationships between the dependent variables and environment variables and the spatial distances between the sample points and predicted locations. This study aimed to explore the feasibility of GWR in predicting soil salinity because the existing interpolation methods for soil salinity in the Yellow River Delta are still of low precision. Additionally, multiple linear regressions, cokriging and regression kriging were added to compare the accuracy of GWRs. The results showed that GWR predicted soil salinity with high accuracy. Furthermore, the accuracy was improved when compared to other methods. The root mean square error, correlation coefficient, regression coefficient and adjustment coefficients between the observed values and predicted values of the validation points were 0.31, 0.65, 0.57 and 0.42, respectively, which were better than that of other methods, indicating that GWR is an optimal method.
资助项目	National Natural Science Foundation of China[41471335] ; National Natural Science Foundation of China[41271407] ; National Science - Technology Support Plan Projects[2013BAD05B03]
WOS关键词	SPATIAL NON-STATIONARITY ; ORGANIC-MATTER ; GEOSTATISTICS ; VARIABILITY
WOS研究方向	Agriculture
语种	英语
出版者	TAYLOR & FRANCIS LTD
WOS记录号	WOS:000399797600005
资助机构	National Natural Science Foundation of China ; National Science - Technology Support Plan Projects
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/62625]
专题	中国科学院地理科学与资源研究所
通讯作者	Huang, Chong
作者单位	1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Wu, Chunsheng,Liu, Gaohuan,Huang, Chong. Prediction of soil salinity in the Yellow River Delta using geographically weighted regression[J]. ARCHIVES OF AGRONOMY AND SOIL SCIENCE,2017,63(7):928-941.
APA	Wu, Chunsheng,Liu, Gaohuan,&Huang, Chong.(2017).Prediction of soil salinity in the Yellow River Delta using geographically weighted regression.ARCHIVES OF AGRONOMY AND SOIL SCIENCE,63(7),928-941.
MLA	Wu, Chunsheng,et al."Prediction of soil salinity in the Yellow River Delta using geographically weighted regression".ARCHIVES OF AGRONOMY AND SOIL SCIENCE 63.7(2017):928-941.