Spatial Interpolation

​Inverse Distance Weighting (IDW)  

Inverse Distance Weighting (IDW) is a spatial interpolation technique commonly used in geographic information systems (GIS) and spatial analysis. It operates on the principle that values at unmeasured locations can be estimated based on the proximity and influence of surrounding measured locations. IDW assumes that closer points have a more significant impact on the estimation than those farther away.

The method assigns weights to neighboring data points inversely proportional to their distance from the target location. This means that closer points have higher weights, reflecting their stronger influence on the interpolated value.

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IDW is versatile and widely used in environmental modeling, terrain analysis, and other spatial applications. However, it has some limitations, such as sensitivity to outliers and a tendency to oversmooth surfaces. Despite these considerations, IDW remains a valuable tool for spatial interpolation, providing a straightforward and intuitive approach to estimate values at unsampled locations within a spatial dataset.

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The interactive map shows the temperature interpolation of Canadian weather stations using the IDW method.