An adaptive uncertainty-guided sampling method for geospatial prediction and its application in digital soil mapping
文献类型：期刊论文
| 作者 | Zhang, Lei3,4; Zhu, A-Xing1,2,3,5,6; Liu, Junzhi3,5,6; Ma, Tianwu3,5,6; Yang, Lin1,4; Zhou, Chenghu1,4 |
| 刊名 | INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
 |
| 出版日期 | 2022-09-23 |
| 页码 | 23 |
| 关键词 | Spatial sampling prediction uncertainty adaptive approach spatial prediction digital soil mapping |
| ISSN号 | 1365-8816 |
| DOI | 10.1080/13658816.2022.2125973 |
| 通讯作者 | Zhu, A-Xing(azhu@wisc.edu) |
| 英文摘要 | Sampling design can significantly reduce the uncertainty in geospatial predictions. In this paper, we developed an adaptive uncertainty-guided stepwise sampling (AUGSS) method to select sampling locations to supplement existing legacy sample points whose representation should be improved. The proposed method selects supplemental samples in a stepwise manner as guided by an objective function with two weighted sub-objectives. One reduces the area with high prediction uncertainty, and the other minimizes the overall prediction uncertainty for the entire area. The method takes an adaptive approach to adjust weights for the two sub-objectives and to tune an uncertainty threshold controlling whether a location can be reliably predicted during the sampling procedure. A case study on soil property prediction shows that AUGSS outperforms the stratified random sampling (SRS) and the non-adaptive uncertainty guided sampling method (UGSS) in terms of RMSE and Lin's concordance correlation coefficient with different sample sizes. This study shows that the AUGSS method offers a potential for effectively adding supplemental samples to existing samples which are insufficient for spatial prediction. The adaptive strategy guided by predicted uncertainty provides an efficient support to improve the spatial pattern of samples, which plays a key role in the result accuracy of geospatial predictive mapping. |
| WOS关键词 | SUPPORT VECTOR REGRESSION ; SPATIAL PREDICTION ; DESIGN ; STRATEGIES ; PATTERNS ; STOCKS ; MODEL ; GIS ; LAW |
| 资助项目 | National Natural Science Foundation of China[41871300] ; National Natural Science Foundation of China[41971054] ; National Natural Science Foundation of China[41901062] ; 111 Program of China[D19002] ; Postgraduate Research and Practice Innovation Program of Jiangsu Province[KYCX22_0109] ; PAPD |
| WOS研究方向 | Computer Science ; Geography ; Physical Geography ; Information Science & Library Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000860056000001 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 资助机构 | National Natural Science Foundation of China ; 111 Program of China ; Postgraduate Research and Practice Innovation Program of Jiangsu Province ; PAPD |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/185343]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhu, A-Xing |
| 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 Wisconsin, Dept Geog, Madison, WI 53706 USA 3.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing, Peoples R China 4.Nanjing Univ, Sch Geog & Ocean Sci, Nanjing, Peoples R China 5.Nanjing Normal Univ, Minist Educ, Key Lab Virtual Geog Environm, Nanjing, Peoples R China 6.Nanjing Normal Univ, Sch Geog, Nanjing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Lei,Zhu, A-Xing,Liu, Junzhi,et al. An adaptive uncertainty-guided sampling method for geospatial prediction and its application in digital soil mapping[J]. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,2022:23. |
| APA | Zhang, Lei,Zhu, A-Xing,Liu, Junzhi,Ma, Tianwu,Yang, Lin,&Zhou, Chenghu.(2022).An adaptive uncertainty-guided sampling method for geospatial prediction and its application in digital soil mapping.INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,23. |
| MLA | Zhang, Lei,et al."An adaptive uncertainty-guided sampling method for geospatial prediction and its application in digital soil mapping".INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE (2022):23. |
入库方式： OAI收割
来源：地理科学与资源研究所
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