R for Geospatial Predictive Mapping: Takeaways from the Talk
Read OriginalThis article summarizes a talk on geospatial predictive mapping in R, comparing methods like Inverse Distance Weighting, Kriging, and Random Forests. It highlights challenges in evaluating map reliability and introduces tools like kNNDM cross-validation and Area of Applicability (AoA) to improve trust in spatial predictions.
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