Spatial Interpolation

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Spatial interpolation is used to estimate values from locations with known values to locations with unknown values. It is a crucial technique in analyzing spatial data and has been utilized in a wide range of disciplines. Spatial interpolation includes two types: if the locational data is provided in point form, it is referred as point interpolation; whereas interpolation of aggregate data defined in one set of areal boundaries to another is called areal interpolation. Point interpolation methods can further be classified into ‘exact’ and ‘approximate’, according to whether they preserve or not preserve the original sample point values. Distance-weighting and Kriging methods are examples of exact method, whereas examples of approximate method include splines and trend surface models. Two types of areal interpolation can also be distinguished, according to whether the method can preserve the original source zone values (volume-preserving) or not (non-volume-preserving). The non-volume-preserving approach is an older approach and involves the use of point interpolation, whereas the volume-preserving one is the newer and more accurate approach and includes polygon overlay (areal-weighted) and pycnophylactic interpolation. Spatial interpolation often involves error. An understanding of the nature of these various methods is necessary to minimize the error and its effects on study conclusions.

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