Inverse distance weighting (IDW) is a spatial interpolation method that estimates unknown values at specific locations based on the values of nearby known points, where closer points have a greater influence on the estimated value. The fundamental idea is that the influence of a data point decreases with distance, which allows for creating smooth surfaces from discrete spatial data, making it particularly useful in spatial data exploration and analysis as well as in generating continuous predictions.
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