A kriging based practical approach for areal interpolation
نویسندگان
چکیده
منابع مشابه
A parallel computing approach to fast geostatistical areal interpolation
Areal interpolation is the procedure of using known attribute values at a set of (source) areal units to predict unknown attribute values at another set of (target) units. Geostatistical areal interpolation employs spatial prediction algorithms, that is, variants of Kriging, which explicitly incorporate spatial autocorrelation and scale differences between source and target units in the interpo...
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Kriging is a spatial interpolation algorithm which provides the best unbiased linear prediction of an observed phenomena by taking a weighted average of samples within a neighbourhood. It is widely used in areas such as geo-statistics where, for example, it may be used to predict the quality of mineral deposits in a location based on previous sample measurements. Kriging has been identified as ...
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Frequently in spatial analysis, data are collected using one measurement system while analyses are conducted using a different measurement system. In these two systems, data regarding individual objects often are aggregated into areal units because (1) data concerning personal information are restricted by privacy and confidentiality regulations; (2) aggregated data require less storage and hav...
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Whenever simulation requires much computer time, interpolation is needed. There are several interpolation techniques in use (for example, linear regression), but this paper focuses on Kriging. This technique was originally developed in geostatistics by D. G. Krige, and has recently been widely applied in deterministic simulation. This paper, however, focuses on random or stochastic simulation. ...
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This paper applies a novel Kriging model to the interpolation of stochastic simulation with high computational expense. The novel Kriging model is developed by using Taylor expansion to construct a drift function for Kriging, thus named Taylor Kriging. The interpolation capability of Taylor Kriging for stochastic simulation is empirically compared with those of Simple Kriging and Ordinary Krigi...
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ژورنال
عنوان ژورنال: Theory and Applications of GIS
سال: 2011
ISSN: 1340-5381,2185-5633
DOI: 10.5638/thagis.19.115