Spatial Data in R

workshop notes for working with spatial data in R SEI R-users group 6-29-2016

Goals

Go over some common workflows relevant to members of the group. In particular...

• Getting Data in -- importing data from common GIS formats .shp and .tif
• Basic manipulations -- projecting, extracting, cropping, overlay
• Visualizing it -- some tips and tricks for interacting with data
• A (slightly more advanced) discussion of interpolation and cross validation

Resources

• lets try using Etherpad, a tool for collaborative note-taking, during the presentation. Click on the link here, to post comments, notes, and questions throughout the session.
• Data used for the examples are hosted in this repository. The zipped file contains the following:
  • dem.tif : an elevation raster for Hawaii
  • stations.csv: a csv of climate stations and locations with monthly rainfall
  • watersheds.shp: a shapefile of polygons with level x watersheds. You can download/unzip the data by hand or run the following code to download and unzip the data to a temporary directory

setwd( tempdir() )  # set working directory to temporary directory 
rcurl ... # download zipped data
unzip( f , exdir = '.')

0. Prerequisites

Most of the functions we will use come from the raster package. Raster provides some 'high-level' interface to spatial data. Also maps comes in handy for quick visualization. You can download these packages with...

install.packages('raster', repos = "http://cran.cnr.berkeley.edu/")
install.packages('maps', repos = "http://cran.cnr.berkeley.edu/")