Training and Events
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![]() Introduction to Spatial Data & Using R as a GIS (join a waiting list) | |
Organised by |
ADRC-E/University of Southampton & CDRC/UCL |
Presenter | Dr Nick Bearman |
Date | 20/07/2017 |
Venue | UCL, Pearson Building, Gower Street, London |
Map | View in Google Maps (WC1E 6BT) |
Contact | |
Description | Course No.: ADRCE Training044 Bearman NOTE: THIS COURSE IS NOW FULLY BOOKED AND THE ON-LINE BOOKING SYSTEM HAS BEEN CLOSED. YOU CAN JOIN OUR WAITING LIST. Event Description We are pleased to offer you this short course jointly organised by the Administrative Data Research Centre for England (ADRC-E) and Consumer Data Research Centre (CDRC). www.cdrc.ac.uk This 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. Course Contents
Some basic spatial analysis in R Learning Outcomes 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 Presenter Dr Nick Bearman, FRGS, CGeog (GIS), AFHEA Nick has been teaching undergrad & postgrad level at a range universities in the UK including Universities of Liverpool, East Anglia and Exeter. He is a Chartered Geographer (GIS), Fellow of Royal Geographical Society (RGS) and Associate Member of Higher Education Authority, with 9 years’ experience. He has advanced knowledge of Geographic Information Systems (GIS), working with many sources and types of spatial and non-spatial data, including big data. Nick has taught GIS to a wide range of students across many subject areas including Geography, International Development and Public Health. The courses range from day courses to two week residential courses, for users from undergraduate students with no GIS experience to advance spatial analysis, designed to give the students the best set of skills for the work they need to do. He uses QGIS, R/RStudio and ArcGIS and has used these with a range of programming and APIs including Google Maps API, JavaScript, MySQL/PHP, R, Python, PostGreSQL and GeoDa. Nick has been using GIS products and applying them in a variety of contexts for 13 years. Target Audience This course is ideal for anyone who wishes to use spatial data in their role. This includes 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. Provisional Programme • 10:00am – 10:15am – Registration & Refreshments • 10:15am – 10:45am – What is GIS & R? • 10:45am – 11:15am – Practical 1: Intro to GIS & R • 11:15am – 11:45am – Classification • 11:45am – 12:30pm – Practical 1: Intro to GIS & R ctd. • 12:30pm – 1:30pm – Lunch • 1:30pm – 1:45pm – Recap and Making Maps • 1:45pm – 3:00pm – Practical 2: Analysis • 3:00pm – 3:15pm – Coffee • 3:15pm – 4pm/4:30pm – Practical 2: Bring your own data
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Level | Intermediate (some prior knowledge) |
Cost | Course Fee: |
Website and registration | |
Region | Greater London |
Keywords | Spatial Data Analysis, Geographical Information System (GIS), ArcGIS, Spatial data, GIS, R, Rstudio, spatial data analysis, choropleth, map, mapping, geographic information systems, choropleth maps, symbology |
Related publications and presentations |
Spatial Data Analysis |