Effects of different sampling densities on geographically weighted regression kriging for predicting soil organic carbon | |
Ye, Huichun1,2; Huang, Wenjiang1,2; Huang, Shanyu3; Huang, Yuanfang4; Zhang, Shiwen5; Dong, Yingying1; Chen, Pengfei6 | |
刊名 | SPATIAL STATISTICS
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2017-05-01 | |
卷号 | 20页码:76-91 |
关键词 | Sampling density Geographically weighted regression Geographically weighted regression kriging Soil organic carbon Spatial variation |
ISSN号 | 2211-6753 |
DOI | 10.1016/j.spasta.2017.02.001 |
通讯作者 | Huang, Wenjiang(huangwj@radi.ac.cn) |
英文摘要 | Geographically weighted regression kriging (GWRK) is a popular interpolation method, considering not only spatial parametric nonstationarity and relationship between target and explanatory variables, but also spatial autocorrelation of residuals. However, little attention has been paid to the effects of different sampling densities on GWRK technique for estimating soil properties. Objectives of this study were: (i) comparing the GWRK predictions with those obtained from multiple linear regression kriging (MLRK) and ordinary kriging (OK), and (ii) examining how different sampling densities affect the performance of GWRK for predicting soil organic carbon (SOC). Soil samples were simulated with four sampling densities, including 0.010, 0.020, 0.041, and 0.082 sites/km(2). The results showed that GWRK made less prediction errors and outperformed MLRK and OK in the case of a high sampling density, with the root mean squared errors of GWRK |
资助项目 | Science & Technology Basic Research Program of China[2014FY210100] ; National Natural Science Foundation of China[41501468] ; National Natural Science Foundation of China[41471186] ; Natural Science Foundation of Hainan Province, China[20154177] ; Natural Science Foundation of Hainan Province, China[2016CXTD015] |
WOS关键词 | SPATIAL PREDICTION ; REGIONAL-SCALE ; CHINA ; INTERPOLATION ; PRECIPITATION ; ATTRIBUTES ; SCHEMES ; MODELS ; MATTER ; STOCKS |
WOS研究方向 | Geology ; Mathematics ; Remote Sensing |
语种 | 英语 |
出版者 | ELSEVIER SCI LTD |
WOS记录号 | WOS:000405608800004 |
资助机构 | Science & Technology Basic Research Program of China ; National Natural Science Foundation of China ; Natural Science Foundation of Hainan Province, China |
内容类型 | 期刊论文 |
源URL | [http://ir.igsnrr.ac.cn/handle/311030/62730] ![]() |
专题 | 中国科学院地理科学与资源研究所 |
通讯作者 | Huang, Wenjiang |
作者单位 | 1.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China 2.Key Lab Earth Observat, Sanya 572029, Hainan, Peoples R China 3.Univ Cologne, Inst Geog, D-50923 Cologne, Germany 4.China Agr Univ, Coll Resources & Environm, Beijing 100193, Peoples R China 5.Anhui Univ Sci & Technol, Coll Earth & Environm, Huainan 232001, Peoples R China 6.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China |
推荐引用方式 GB/T 7714 | Ye, Huichun,Huang, Wenjiang,Huang, Shanyu,et al. Effects of different sampling densities on geographically weighted regression kriging for predicting soil organic carbon[J]. SPATIAL STATISTICS,2017,20:76-91. |
APA | Ye, Huichun.,Huang, Wenjiang.,Huang, Shanyu.,Huang, Yuanfang.,Zhang, Shiwen.,...&Chen, Pengfei.(2017).Effects of different sampling densities on geographically weighted regression kriging for predicting soil organic carbon.SPATIAL STATISTICS,20,76-91. |
MLA | Ye, Huichun,et al."Effects of different sampling densities on geographically weighted regression kriging for predicting soil organic carbon".SPATIAL STATISTICS 20(2017):76-91. |
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