Handbook of Geospatial Artificial Intelligence

7Intelligent Spatial Prediction and Interpolation Methods

Di Zhu

Department of Geography, Environment, and Society, University of Minnesota, Twin Cities

Guofeng Cao

Department of Geography, University of Colorado, Boulder

DOI: 10.1201/9781003308423-7

CONTENTS

• 7.1 Introduction

• 7.2 GeoAI Motivations for Spatial Prediction and Interpolation

  1. 7.2.1 Representing spatial data

  2. 7.2.2 Measuring spatial structure

  3. 7.2.3 Modeling spatial relationships

• 7.3 GeoAI for Geostatistics

  1. 7.3.1 Deep learning and kriging methods

  2. 7.3.2 Case study: Wind and solar radiation downscaling

• 7.4 GeoAI for Spatial Regression

  1. 7.4.1 Modeling spatial association relationships

  2. 7.4.2 Spatial regression graph convolutional neural networks

  3. 7.4.3 Case study: Social media check-ins ...