IDW (Inverse Distance Weighting) Spatial Interpolation

IDW (Inverse Distance Weighting) is one of the most frequently employed methods in spatial interpolation. This statistically-based interpolation technique estimates unknown point values using weighted averages of surrounding known points, where weights are inversely proportional to distance. The key advantage lies in its model-free approach that requires no preset parameters, making implementation straightforward. Our MATLAB program implements core IDW algorithms through distance matrix calculations and power parameter optimization, while also incorporating other essential spatial interpolation methods including Kriging (with variogram modeling) and spline interpolation techniques. The code structure features modular functions for grid generation, neighbor search routines, and weight computation. Additionally, the program provides comprehensive visualization capabilities through surface plotting, contour mapping, and comparative analysis tools, enabling users to effectively evaluate and compare interpolation results. Through practical application of this toolkit, users can gain deeper insights into spatial interpolation methodologies and their real-world implementations.