Spatial interpolation of marine environment data using P-MSN
文献类型：期刊论文
| 作者 | Gao, Bingbo2; Hu, Maogui3 ; Wang, Jinfeng3; Xu, Chengdong3; Chen, Ziyue4; Fan, Haimei1; Ding, Haiyuan5
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| 刊名 | INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
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| 出版日期 | 2019-11-01 |
| 页码 | 27 |
| ISSN号 | 1365-8816 |
| 关键词 | Stratified non-homogeneity best linear unbiased estimator (BLUE) spatial interpolation marine environment |
| DOI | 10.1080/13658816.2019.1683183 |
| 通讯作者 | Wang, Jinfeng(wangjf@lreis.ac.cn) |
| 英文摘要 | When a marine study area is large, the environmental variables often present spatially stratified non-homogeneity, violating the spatial second-order stationary assumption. The stratified non-homogeneous surface can be divided into several stationary strata with different means or variances, but still with close relationships between neighboring strata. To give the best linear-unbiased estimator for those environmental variables, an interpolated version of the mean of the surface with stratified non-homogeneity (MSN) method called point mean of the surface with stratified non-homogeneity (P-MSN) was derived. P-MSN distinguishes the spatial mean and variogram in different strata and borrows information from neighboring strata to improve the interpolation precision near the strata boundary. This paper also introduces the implementation of this method, and its performance is demonstrated in two case studies, one using ocean color remote sensing data, and the other using marine environment monitoring data. The predictions of P-MSN were compared with ordinary kriging, stratified kriging, kriging with an external drift, and empirical Bayesian kriging, the most frequently used methods that can handle some extent of spatial non-homogeneity. The results illustrated that for spatially stratified non-homogeneous environmental variables, P-MSN outperforms other methods by simultaneously improving interpolation precision and avoiding artificially abrupt changes along the strata boundaries. |
| WOS关键词 | LAND-COVER ; REGRESSION ; CLASSIFICATION ; NONSTATIONARY ; OPTIMIZATION ; AREA |
| 资助项目 | National Key Research and Development Program[2017YFD0801205] ; National Natural Science Foundation of China[41531179] ; National Natural Science Foundation of China[41601425] ; Beijing Training Support Project for excellent scholars[2016000020060G123] |
| WOS研究方向 | Computer Science ; Geography ; Physical Geography ; Information Science & Library Science |
| 语种 | 英语 |
| 出版者 | TAYLOR & FRANCIS LTD |
| WOS记录号 | WOS:000494635100001 |
| 资助机构 | National Key Research and Development Program ; National Natural Science Foundation of China ; Beijing Training Support Project for excellent scholars |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/131694]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Wang, Jinfeng |
| 作者单位 | 1.SOA, East China Sea Environm Monitoring Ctr, Assessment Dept, Shanghai, Peoples R China 2.China Agr Univ, Coll Land Sci & Technol, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, LREIS, Beijing, Peoples R China 4.Beijing Normal Univ, Coll Global Change & Earth Syst Sci, Beijing, Peoples R China 5.Sinosoft Ltd, Dept Publ Hlth, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Gao, Bingbo,Hu, Maogui,Wang, Jinfeng,et al. Spatial interpolation of marine environment data using P-MSN[J]. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,2019:27. |
| APA | Gao, Bingbo.,Hu, Maogui.,Wang, Jinfeng.,Xu, Chengdong.,Chen, Ziyue.,...&Ding, Haiyuan.(2019).Spatial interpolation of marine environment data using P-MSN.INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,27. |
| MLA | Gao, Bingbo,et al."Spatial interpolation of marine environment data using P-MSN".INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE (2019):27. |
入库方式： OAI收割
来源：地理科学与资源研究所
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