克里金
变异函数
插值(计算机图形学)
多元插值
变量(数学)
空间变异性
变化(天文学)
计算机科学
空间分析
数学
地质统计学
统计
双线性插值
人工智能
数学分析
物理
运动(物理)
天体物理学
作者
Margaret A. Oliver,R. Webster
出处
期刊:International journal of geographical information systems
[Taylor & Francis]
日期:1990-07-01
卷期号:4 (3): 313-332
被引量:2011
标识
DOI:10.1080/02693799008941549
摘要
Geographical information systems could be improved by adding procedures for geostatistical spatial analysis to existing facilities. Most traditional methods of interpolation are based on mathematical as distinct from stochastic models of spatial variation. Spatially distributed data behave more like random variables, however, and regionalized variable theory provides a set of stochastic methods for analysing them. Kriging is the method of interpolation deriving from regionalized variable theory. It depends on expressing spatial variation of the property in terms of the variogram, and it minimizes the prediction errors which are themselves estimated. We describe the procedures and the way we link them using standard operating systems. We illustrate them using examples from case studies, one involving the mapping and control of soil salinity in the Jordan Valley of Israel, the other in semi-arid Botswana where the herbaceous cover was estimated and mapped from aerial photographic survey.
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