Geocomputation with R is for people who want to analyze, visualize, and model geographic data with open source software. The second edition features numerous updates, including the adoption of the high-performance terra package for all raster data processing.
Geocomputation with R is for people who want to analyze, visualize, and model geographic data with open source software. The second edition features numerous updates, including the adoption of the high-performance terra package for all raster data processing.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
The authors are well-established geospatial researchers and teachers. Dr. Robin Lovelace is an Associate Professor at the University of Leeds, is the developer of high impact applications for more data-driven transport planning and policy. Dr. Jakub Nowosad is an Associate Professor at the Adam Mickiewicz University in Poznan, where his focus is on methods for analyzing and understanding spatial patterns in the environment. Dr. Jannes Muenchow is a researcher, engineer and developer at the data science consultancy Cynkra, where he holds a dual role as a senior data scientist and supporting DevOps engineer.
Inhaltsangabe
Foreword (2nd Edition) Preface 1. Introduction 2. Geographic data in R 3. Attribute data operations 4. Spatial data operations 5. Geometry operations 6. Raster-vector interactions 7. Reprojecting geographic data 8. Geographic data I/O Part 1: Foundations 9. Making maps with R 10. Bridges to GIS software 11. Scripts, algorithms and functions 12. Statistical learning Part 2: Extensions 13. Transportation 14. Geomarketing 15. Ecology 16. Conclusion Bibliography Index
Foreword (2nd Edition) Preface 1. Introduction 2. Geographic data in R 3. Attribute data operations 4. Spatial data operations 5. Geometry operations 6. Raster-vector interactions 7. Reprojecting geographic data 8. Geographic data I/O Part 1: Foundations 9. Making maps with R 10. Bridges to GIS software 11. Scripts, algorithms and functions 12. Statistical learning Part 2: Extensions 13. Transportation 14. Geomarketing 15. Ecology 16. Conclusion Bibliography Index
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