How land cover information can modify spatial neighborhood structure in the SAR prior
How covariates get aggregated to coarse observation footprints, and why the same change-of-support operator handles both covariates and the latent field
Why spatial blocking isn’t always the right choice for cross-validation, and what observation density has to do with it
How satellite observations are modeled as weighted averages of an underlying spatial field, and why the weighting function matters
Why spatial structure in your data can silently bias your estimates