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Interpolation
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==Inverse Distance Weighting== [[Inverse distance weighting|Inverse Distance Weighting]] (IDW) is a spatial interpolation method that estimates values based on nearby data points, with closer points having more influence.<ref>{{cite journal |last1=Donald |first1=Shepard |title=A two-dimensional interpolation function for irregularly-spaced data |journal=23rd ACM National Conference |date=1968}}</ref> It uses an inverse power law for weighting, where higher power values emphasize local effects, while lower values create a smoother surface. IDW is widely used in [[Geographic information system|GIS]], [[meteorology]], and environmental modeling for its simplicity but may produce artifacts in clustered or uneven data.<ref>{{cite journal |last1=Ben Moshe |first1=Nir |title=A Simple Solution for the Inverse Distance Weighting Interpolation (IDW) Clustering Problem |journal=Sci |date=2025 |volume=7 |issue=1 |page=30 |doi=10.3390/sci7010030|doi-access=free }}</ref>
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