Spatial data science : with applications in R
Author(s)
Bibliographic Information
Spatial data science : with applications in R
（The R series）（A Chapman & Hall book）
CRC Press, 2023
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Note
Includes bibliographical references (p. 277-290) and index.
Description and Table of Contents
Description
-Written by the authors of key spatial R packages
-Makes spatial data analysis more robust
-Integrates with the tidyverse and comparable approaches
-Includes many easily reproducible examples
Table of Contents
Part 1. Spatial Data 1. Getting Started 2. Coordinates 3. Geometries 4. Spherical Geometries 5. Attributes and Support 6. Data Cubes Part 2. R for Spatial Data Science 7. Introduction to sf and stars 8. Plotting spatial data 9. Large data and cloud native Part 3. Models for Spatial Data 10. Statistical modelling of spatial data 11. Point Pattern Analysis 12. Spatial Interpolation 13. Multivariate and Spatiotemporal Geostatistics 14. Proximity and Areal Data 15. Measures of spatial autocorrelation 16. Spatial Regression 17. Spatial econometrics models Appendix A. Older R Spatial Packages Appendix B. R basics
by "Nielsen BookData"