Spatial Data Science: With Applications in R by Edzer Pebesma Hardcover Book

Description: FREE SHIPPING UK WIDE Spatial Data Science by Edzer Pebesma, Roger Bivand Spatial Data Science is a book for data scientists with intermediate R knowledge. The book gives a detailed explanation of the core spatial software packages for R: sf for simple feature access, and stars for raster and vector data cubes – array data with spatial and temporal dimensions. FORMAT Hardcover CONDITION Brand New Publisher Description Spatial Data Science introduces fundamental aspects of spatial data that every data scientist should know before they start working with spatial data. These aspects include how geometries are represented, coordinate reference systems (projections, datums), the fact that the Earth is round and its consequences for analysis, and how attributes of geometries can relate to geometries. In the second part of the book, these concepts are illustrated with data science examples using the R language. In the third part, statistical modelling approaches are demonstrated using real world data examples. After reading this book, the reader will be well equipped to avoid a number of major spatial data analysis errors.The book gives a detailed explanation of the core spatial software packages for R: sf for simple feature access, and stars for raster and vector data cubes – array data with spatial and temporal dimensions. It also shows how geometrical operations change when going from a flat space to the surface of a sphere, which is what sf and stars use when coordinates are not projected (degrees longitude/latitude). Separate chapters detail a variety of plotting approaches for spatial maps using R, and different ways of handling very large vector or raster (imagery) datasets, locally, in databases, or in the cloud. The data used and all code examples are freely available online from https://r-spatial.org/book/. The solutions to the exercises can be found here: _exercises/. Author Biography Edzer Pebesma is professor at the Institute for Geoinformatics of the University of Muenster, Germany, where he leads the spatiotemporal modelling lab. He co-initiated openEO, an open source software ecosystem around a language neutral API for analyzing very large data cubes and image collections.Roger Bivand is a geographer, emeritus professor of the Department of Economics of the Norwegian School of Economics, Bergen, Norway, has worked with spatial autocorrelation since the 1970s, and is a Fellow of the Spatial Econometrics Association.Edzer and Roger have actively interacted with the open source geospatial user and developer communities since the last century. They author and maintain a number of key R packages for the handling and analysis of spatial and spatiotemporal data, including sf, stars, s2, sp, and gstat, spdep, spatialreg and rgrass. Both are ordinary members of the R foundation. 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 Review "I think that this is an important book. I am convinced it will be seen as a reference for scientists working with spatial data in R but also as a textbook for scientists and postgraduate students who are learning the concepts and how to do it practically in R (admittedly at a very advanced level!). It has certainly be on the shelf of everyone working with and teaching spatial data in R."-Hanna Meyer, Institute of Landscape Ecology, University of MÜnster, Germany Review Quote "I think that this is an important book. I am convinced it will be seen as a reference for scientists working with spatial data in R but also as a textbook for scientists and postgraduate students who are learning the concepts and how to do it practically in R (admittedly at a very advanced level!). It has certainly be on the shelf of everyone working with and teaching spatial data in R." -Hanna Meyer, Institute of Landscape Ecology, University of M Details ISBN1138311189 ISBN-10 1138311189 ISBN-13 9781138311183 Format Hardcover Author Roger Bivand Publisher Taylor & Francis Ltd Year 2023 Publication Date 2023-05-10 UK Release Date 2023-05-10 Imprint CRC Press Subtitle With Applications in R Place of Publication London Country of Publication United Kingdom Illustrations 64 Line drawings, color; 12 Line drawings, black and white; 20 Halftones, color; 2 Halftones, black and white; 84 Illustrations, color; 14 Illustrations, black and white AU Release Date 2023-05-10 NZ Release Date 2023-05-10 Pages 300 Series Chapman & Hall/CRC The R Series DEWEY 519.53502855133 Audience Tertiary & Higher Education We've got this At The Nile, if you're looking for it, we've got it. 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