Spatial Association

"Spatial association uses variables that are easier to observe to infer variables that are more difficult to observe, such as predicting soil properties from matching landscape positions and parent materials. Spatial autocorrelation assumes that nearby observations tend to be more similar than distant observations. Interpolation methods such as inverse distance weighting and kriging use these relationships to estimate values between sampled locations."