Brunsdon / Comber An Introduction to R for Spatial Analysis and Mapping

2. Auflage 2019
ISBN: 978-1-5264-5420-1
Verlag: SAGE Publications
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 336 Seiten, Format (B × H): 170 mm x 242 mm

Reihe: Spatial Analytics and GIS

This is a new edition of the accessible and student-friendly 'how to' for anyone using R for the first time, for use in spatial statistical analysis, geocomputation and digital mapping. The authors, once again, take readers from ‘zero to hero’, updating the now standard text to further enable practical R applications in GIS, spatial analyses, spatial statistics, web-scraping and more.

Revised and updated, each chapter includes:

- example data and commands to explore hands-on;
- scripts and coding to exemplify specific functionality;
- self-contained exercises for students to work through;
- embedded code within the descriptive text.

The new edition includes detailed discussion of new and emerging packages within R like sf, ggplot, tmap, making it the go to introduction for all researchers collecting and using data with location attached. This is the introduction to the use of R for spatial statistical analysis, geocomputation, and GIS for all researchers - regardless of discipline - collecting and using data with location attached.

Autoren/Hrsg.

Brunsdon, Chris

Comber, Lex

Fachgebiete

• Geowissenschaften Geographie | Raumplanung Geographie: Allgemeines, Karten & Atlanten

Inhaltsverzeichnis

Chapter 1 Introduction
Chapter 2 Data and Plots
Chapter 3 Handling Spatial Data
Chapter 4 Programming in R
Chapter 5 Using R as a GIS
Chapter 6 Point Pattern Analysis
Chapter 7 Spatial Attribute Analysis
Chapter 8 Localised Spatial Analysis
Chapter 9 R and Internet Data
Chapter 10 Epilogue

Über Autor(innen)

Comber, Lex
Alexis Comber, Lex, is Professor of Spatial Data Analytics at Leeds Institute for Data Analytics (LIDA) the University of Leeds. He worked previously at the University of Leicester where he held a chair in Geographical Information Science. His first degree was in Plant and Crop Science at the University of Nottingham and he completed a PhD in Computer Science at the Macaulay Institute, Aberdeen (now the James Hutton Institute) and the University of Aberdeen. This developed expert systems for land cover monitoring from satellite imagery and brought him into the world of spatial data, spatial analysis, and mapping.

Lex’s research interests span many different application areas including environment, land cover / land use, demographics, public health, agriculture, bio-energy and accessibility, all of which require multi-disciplinary approaches. His research draws from methods in geocomputation, mathematics, statistics and computer science and he has extended techniques in operations research / location-allocation (what to put where), graph theory (cluster detection in networks), heuristic searches (how to move intelligently through highly dimensional big data), remote sensing (novel approaches for classification), handling divergent data semantics (uncertainty handling, ontologies, text mining) and spatial statistics (quantifying spatial and temporal process heterogeneity).

He has co-authored (with Chris Brunsdon) An Introduction to R for Spatial Analysis and Mapping, the first ‘how to book’ for spatial analyses and mapping in R, the open source statistical software, now in its second edition.

Outside of academic work and in no particular order, Lex enjoys his vegetable garden, walking the dog and playing pinball (he is the proud owner of a 1981 Bally Eight Ball Deluxe).

Brunsdon, Chris
Chris Brunsdon is Professor of Geocomputation and Director of the National Centre for Geocomputation at the National University of Ireland, Maynooth, having worked previously in the Universities of Newcastle, Glamorgan, Leicester and Liverpool, variously in departments focusing on both geography and computing. He has interests that span both of these disciplines, including spatial statistics, geographical information science, and exploratory spatial data analysis, and in particular the application of these ideas to crime pattern analysis, the modelling of house prices, medical and health geography and the analysis of land use data. He was one of the originators of the technique of geographically weighted regression (GWR).

He has extensive experience of programming in R, going back to the late 1990s, and has developed a number of R packages which are currently available on CRAN, the Comprehensive R Archive Network. He is an advocate of free and open source software, and in particular the use of reproducible research methods, and has contributed to a large number of workshops on the use of R and of GWR in a number of countries, including the UK, Ireland, Japan, Canada, the USA, the Czech Republic and Australia.

When not involved in academic work he enjoys running, collecting clocks and watches, and cooking – the last of these probably cancelling out the benefits of the first.