Sampling and Kriging Spatial Means: Efficiency and Conditions
文献类型：SCI/SSCI论文
| 作者 | Wang J. F. ; Li L. F. ; Christakos G. |
| 发表日期 | 2009 |
| 关键词 | random field mean Kriging spatial dependence GIS site-specific information variational assimilation kalman filter soil interpolation precipitation equation adjoint region model |
| 英文摘要 | Sampling and estimation of geographical attributes that vary across space (e. g., area temperature, urban pollution level, provincial cultivated land, regional population mortality and state agricultural production) are common yet important constituents of many real-world applications. Spatial attribute estimation and the associated accuracy depend on the available sampling design and statistical inference modelling. In the present work, our concern is areal attribute estimation, in which the spatial sampling and Kriging means are compared in terms of mean values, variances of mean values, comparative efficiencies and underlying conditions. Both the theoretical analysis and the empirical study show that the mean Kriging technique outperforms other commonly-used techniques. Estimation techniques that account for spatial correlation (dependence) are more efficient than those that do not, whereas the comparative efficiencies of the various methods change with surface features. The mean Kriging technique can be applied to other spatially distributed attributes, as well. |
| 出处 | Sensors |
| 卷 | 9 |
| 期 | 7 |
| 页 | 5224-5240 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 1424-8220 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/22926]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Wang J. F.,Li L. F.,Christakos G.. Sampling and Kriging Spatial Means: Efficiency and Conditions. 2009. |
入库方式： OAI收割
来源：地理科学与资源研究所
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