Bearman

Dr Nick Bearman is Honorary Lecturer at University of Liverpool and work as Senior GIS Analyst and Course Director at Clear Mapping Co, an award-winning cartographic design consultancy. He teaches GIS and Spatial Data Analysis at undergraduate & postgraduate level at a range universities in the UK including Universities of Liverpool, East Anglia and Exeter. He is currently working to apply GIS analysis techniques to enable small area comparisons of census data over the previous 40 years. His interests are in the use of novel methods to communicate spatial data including the use of sound and cartograms. He is a Chartered Geographer (GIS), Fellow of the Royal Geographical Society and an Associate Fellow of the Higher Education Authority

Course Content
This course will provide an understanding of spatial data, as well as how to make publication quality maps and use spatial analysis techniques to support your work. The course covers the theoretical background to spatial data and GIS, including how to use spatial data effectively and correctly, understanding different types of spatial data and how to critically look at maps. We will also focus on the practical implementation of these skills using a variety of software packages. These include QGIS, a free open source GIS package similar to ArcGIS, R / RStudio, a free open source statistical program which has a wide range of spatial analysis capabilities and GeoDa, a free open source package for spatial analysis.

Course Objectives
Participants will understand the forms and types of spatial data (raster/vector, shape files, geodatabases, etc.) as well as developing the skills to create publication quality maps and to perform spatial data analysis on a range of spatial data sets. We will show you how to make use of spatial data in their own work, including making site maps, using GIS for decision making and performing geocomputation analysis. Analysis will include clustering, hot spot analysis and regression.

Course Prerequisites
No existing GIS knowledge is required, but some basic familiarity with Google Maps or Open Street Maps (for example, using it to look at your local area) is useful. Also participants should be familiar with basic computer use (e.g. Word, Excel, etc.) and working with files & zip files. No experience of QGIS or R is required, but participants should be aware that R is command line driven, and so they should be prepared to learn how to code and write short scripts

Day 1 What is Spatial Data? | Intro to QGIS I

Day 2 Creating Publication Quality Maps | Using Census Data with QGIS

Day 3 Census Data | Using Census Data with R

Day 4 Raster Data | Working with Population Data

Day 5 Geographic Analysis | Geographic Analysis with GeoDa and R