An adaptive inverse-distance weighting spatial interpolation technique

By G. Y. Lu, David W. S. Wong. Computational Geosciences, 2008

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Deep Distributed Fusion Network for Air Quality Prediction (2018, methodology): “Then, we use a classic spatial interpolation method, inverse distance weighting (IDW) [11], to interpolate the AQI of fake monitoring stations.”
Geostatistical interpolation of daily rainfall at catchment scale: the use of several variogram models in the Ourthe and Ambleve catchments, Belgium (2011, background): “Thus, small powerd tends to give estimated values as averages ofZsi in the neighbourhood, while large powerd tends to give larger weights to the nearest points and increasingly down-weights points further away (Lu and Wong, 2008).”
Spatial interpolation of monthly climate data for Finland: comparing the performance of kriging and generalized additive models (2013, methodology): “Nongeostatistical methods include trendsurface analysis (Chorley and Haggett 1965), inversed distance weighted (IDW) interpolation (Lu and Wong 2008), and spline interpolation (Hong et al.”