TY  - GEN
AU  - Chris Brunsdon
AU  - Lex Comber
TI  - An introduction to r for spatial analysis and mapping
SN  -  9781446272947
U1  - 300.15195 BRU 
PY  - 2015///
CY  - New Delhi
PB  - Sage
N1  - Objectives of this book    Spatial Data Analysis in R    Chapters and Learning Arcs    The R Project for Statistical Computing    Obtaining and Running the R software    The R interface    Other resources and accompanying website  
Part 2: Data and Plots
  The basic ingredients of R: variables and assignment    Data types and Data classes    Plots    Reading, writing, loading and saving data  
Part 3: Handling Spatial Data in R
  Introduction: GISTools    Mapping spatial objects    Mapping spatial data attributes    Simple descriptive statistical analyses  
Part 4: Programming in R
  Building blocks for Programs    Writing Functions    Writing Functions for Spatial Data  
Part 5: Using R as a GIS
  Spatial Intersection or Clip Operations    Buffers    Merging spatial features    Point-in-polygon and Area calculations    Creating distance attributes    Combining spatial datasets and their attributes    Converting between Raster and Vector    Introduction to Raster Analysis
N2  - "In an age of big data, data journalism and with a wealth of quantitative information around us, it is not enough for students to be taught only 100 year old statistical methods using 'out of the box' software. They need to have 21st-century analytical skills too. This is an excellent and student-friendly text from two of the world leaders in the teaching and development of spatial analysis. It shows clearly why the open source software R is not just an alternative to commercial GIS, it may actually be the better choice for mapping, analysis and for replicable research. Providing practical tips as well as fully working code, this is a practical 'how to' guide ideal for undergraduates as well as those using R for the first time. It will be required reading on my own courses."
ER  -