Spatial data science : with applications in R

Author(s)

• Pebesma, Edzer
• Bivand, Roger

Bibliographic Information

Spatial data science : with applications in R

Edzer Pebesma, Roger Bivand

（The R series）（A Chapman & Hall book）

CRC Press, 2023

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"

• NCID: BD03598633
• ISBN:
  • 9781138311183
• LCCN: 2022052399
• Country Code: us
• Title Language Code: eng
• Text Language Code: eng
• Place of Publication: Boca Raton
• Pages/Volumes: xiii, 300 p.
• Classification:
  • LCC : QA278.2
  • DC23 : 519.5/3502855133
• Subject Headings:
  • LCSH : Spatial analysis (Statistics) -- Data processing
  • LCSH : R (Computer program language)
• Parent Bibliography ID:
  • BB06063161
  • BB04603869