The Second Dimension of Spatial Association
Generating second-dimension variables for a spatial variable
Removing outliers.
Preparing explanatory variables data for SDA-based prediction
Selecting variables using linear regression
Selecting variables for the SDA model
Fast calculation of the variance inflation factor (VIF)
Most of the current methods explore spatial association using observations at sample locations, which are defined as the first dimension of spatial association (FDA). The proposed concept of the second dimension of spatial association (SDA), as described in Yongze Song (2022) <doi:10.1016/j.jag.2022.102834>, aims to extract in-depth information about the geographical environment from locations outside sample locations for exploring spatial association.