Prediction of soil salinity in the Yellow River Delta using geographically weighted regression
文献类型：期刊论文
| 作者 | Wu, Chunsheng1,2; Liu, Gaohuan1; Huang, Chong1 |
| 刊名 | ARCHIVES OF AGRONOMY AND SOIL SCIENCE
 |
| 出版日期 | 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. |
| WOS关键词 | SPATIAL NON-STATIONARITY ; ORGANIC-MATTER ; GEOSTATISTICS ; VARIABILITY |
| 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研究方向 | Agriculture |
| 语种 | 英语 |
| WOS记录号 | WOS:000399797600005 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 资助机构 | National Natural Science Foundation of China ; National Science - Technology Support Plan Projects |
| 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. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。