Geocomputation with R is for people who want to analyze, visualize, and model geographic data with open source software. The book provides a foundation for learning how to solve a wide range of geographic data analysis problems in a reproducible, and therefore scientifically sound and scalable way. The second edition features numerous updates, including the adoption of the high-performance terra package for all raster data processing, detailed coverage of the spherical geometry engine s2, updated information on coordinate reference systems and new content on openEO, STAC, COG, and gdalcubes. The data visualization chapter has been revamped around version 4 of the tmap package, providing a fresh perspective on creating publication-quality maps from the command line. The importance of the book is also highlighted in a new foreword by Edzer Pebesma.
The book equips you with the knowledge and skills necessary to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. The book is especially well-suited to:
The book is divided into three parts: Foundations, Extensions, and Applications, covering progressively more advanced topics. The exercises at the end of each chapter provide the necessary skills to address various geospatial problems, with solutions and supplementary materials available at r.geocompx.org/solutions/.
"synopsis" may belong to another edition of this title.
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.
"About this title" may belong to another edition of this title.
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Paperback. Condition: new. Paperback. Geocomputation with R is for people who want to analyze, visualize, and model geographic data with open source software. The book provides a foundation for learning how to solve a wide range of geographic data analysis problems in a reproducible, and therefore scientifically sound and scalable way. The second edition features numerous updates, including the adoption of the high-performance terra package for all raster data processing, detailed coverage of the spherical geometry engine s2, updated information on coordinate reference systems and new content on openEO, STAC, COG, and gdalcubes. The data visualization chapter has been revamped around version 4 of the tmap package, providing a fresh perspective on creating publication-quality maps from the command line. The importance of the book is also highlighted in a new foreword by Edzer Pebesma.The book equips you with the knowledge and skills necessary to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. The book is especially well-suited to:Data scientists and engineers interested in upskilling to handle spatial data.People with existing geographic data skills interested in developing powerful geosolutions via code.Anyone who needs to work with spatial data in a reproducible and scalable way.The book is divided into three parts: Foundations, Extensions, and Applications, covering progressively more advanced topics. The exercises at the end of each chapter provide the necessary skills to address various geospatial problems, with solutions and supplementary materials available at r.geocompx.org/solutions/. 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781032248882
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