Lab-06: If you please sir...which way to the Secret Garden?
Introduction
What is there to not like about maps!!!
We will learn to make static and interactive maps and to show off different kinds of data on them, data that have an inherently “spatial” spread or significance!
Trade Routes? Populations? Street Crime hotspots? Theatre and Food districts and popular Restaurants? Literary Paris, London and Barcelona?
sp - defines the set
of base classes for spatial data in R. Most useful for creating, converting,
merging, transforming (e.g. projection), and plotting (see spplot) Spatial*
objects.
rgdal - wrapper
for GDAL. Most useful for reading in vector data (e.g.
ESRI Shapefiles, GeoJSON, KML) with the function readOGR and reading raster
data (e.g. NetCDF, GeoTiff) with the function readGDAL.
rgeos - wrapper
for the GEOS library. Most useful for common
spatial operations such as calculating distances between objects, areas,
intersections, buffers, centroids, etc. See help(package = "rgeos") for a
complete list of functions.
raster -
provides a set of object classes and functions specific to working with
raster data. Most useful for loading, transforming, and analyzing raster
data. A particularly useful function getData retrieves commonly used
spatial data such as administrative boundaries or world climate data.
R Spatial Resources
"Applied Spatial Data Analysis with R" [Book Website][Springer Link] by Roger S. Bivand, Edzer Pebesma, and Virgilio Gómez-Rubio. Perhaps the best and most comprehensive introduction to Spatial* objects in R by the authors of the sp package.
