Home » Introduction to Spatial Data & Using R as a GIS

Introduction to Spatial Data & Using R as a GIS

Date/Time
Date(s) - 16/01/2018
10:00 am - 4:30 pm

Categories No Categories


This course is now fully booked.

We are pleased to offer you this short course jointly organised by the Consumer Data Research Centre (CDRC) and the Administrative Data Research Centre for England (ADRC-E).

Please note this course can be taken as a one-day course, or can also be taken in conjunction with other two one-day courses on 15 January and 17 January 2018.

The course will cover an introduction to R, how to load and manage spatial data and how to create maps using R and RStudio. We will show you appropriate ways of using classifications for choropleth maps, using loops in R to create multiple maps and some basic spatial analysis.

We will be using RStudio to work with the R environment. By the end of the course you will be able to load data into R, represent it effectively and be able to prepare an output quality map.

This course is ideal for anyone who wishes to use spatial data in their role. This includes academics, commercial users, government & other public sector researchers who have data with some spatial information (e.g. address, postcode, etc.) which they wish to show on a map.

This course is also suitable for those who wish to have an overview of what spatial data can be used for. No previous experience of spatial data is required. No experience of spatial data, GIS or scripting required. Some basic experience of using Google Earth / Maps would be beneficial.

Further course details, including fees, can be found here.

More information regarding our courses can be found here.

Podcast for some of our previous courses can be found here

Course Code (to quote to the ADRCE)
ADRCE-training048Bearman
Course Date
16th January 2018
Places Available
19
Course Leader
Dr Nick Bearman

Course Description
Course Contents:

  • The basic theories behind spatial data, such as projections and coordinate systems
  • Different types of spatial data, including vector, raster and point, line and polygon
  • How to create a choropleth map, and why colours and classifications are important
  • Working with spatial data in R & Rstudio
  • Reprojecting data in R
  • Some basic spatial analysis in R

By the end of the course, students will be able to:

  • Use R to read in CSV data
  • Use R to read in spatial data
  • Know how to plot spatial data using R
  • Join spatial data to attribute data
  • Customize colour and classification methods
  • Understand how to use loops to make multiple maps
  • Know how to reproject spatial data
  • Be able to perform point in polygon operations
  • Know how to write shape files
  • Know how create a ‘heat-map’ style map using point data