SPATIAL DATA ANALYSIS WITH R
Date:
31/03/2017
Organised by:
Jumping Rivers ltd
Presenter:
Dr Colin Gillespie/Dr Jamie Owen
Level:
Intermediate (some prior knowledge)
Contact:
Esther Gillespie, esther@jumpingrivers.com, 07740285328
Map:
View in Google Maps (WC1E 7HU)
Venue:
University of London, Senate House, University of London, Malet St, London WC1E 7HU
Description:
LONDON at London University Senate House
As spatial datasets get larger more sophisticated software needs to be harnessed for their analysis. R is now a widely used open source software platform for working with spatial data thanks to its powerful analysis and visualisation packages.
The course demonstrates the many useful features that are hidden away in package documentation. The functions get_map() and getData(), from the ggmap and raster packages, for example, allow users to download data from anywhere in the world into R directly. Participants will be introduced to functionality in R that is very difficult to achieve in other software, such as the clustering of points into polygons and geographically weighted regression. The focus is on the principles rather than the specific methods, providing participants with the understanding needed to apply R's powerful suite of geographical tools to their own problems.
It is expected that participants have basic R experience, e.g. attending the Introduction to R and Introduction to Programming courses. The course will be hands-on and applied with short introductory lectures to each of the topics, followed by practical sessions loading and analysing real spatial datasets.
COURSE STRUCTURE:
This course will be structured as follows:
- Introducing R as a GIS
- The structure of spatial objects in R
- Loading and interrogating spatial data
- Visualising spatial datasets
- Acquiring external data with R
- Point pattern analysis and spatial interpolation
- Geographical models in R
- Webmaps
Cost:
£450 + Vat (25% discount to academics & charity)
Website and registration:
Region:
Greater London
Keywords:
Secondary Analysis, Digital Social Research, Mixed Methods, Data Collection (other), Qualitative Data Handling and Data Analysis, Quantitative Data Handling and Data Analysis, Statistical Theory and Methods of Inference, Mixed Methods Data Handling and Data Analysis, ICT and Software, R, Data Visualisation, Creating graphs and charts, Interactive data visualisation, Workshops, Training research methods teachers
Related publications and presentations:
Secondary Analysis
Digital Social Research
Mixed Methods
Data Collection (other)
Qualitative Data Handling and Data Analysis
Quantitative Data Handling and Data Analysis
Statistical Theory and Methods of Inference
Mixed Methods Data Handling and Data Analysis
ICT and Software
R
Data Visualisation
Creating graphs and charts
Interactive data visualisation
Workshops
Training research methods teachers