Exploring and Visualising Geographic Information for Social Scientists

Description:

This course is aimed at people who have no experience of digital map making or GIS. The three day course will provide delegates with the skills to be able to produce map visualisations to put in briefing papers / journal articles / PhD theses etc. This will draw on data used in research by the AQMeN Crime and Victimisation strand on crime trends in local neighbourhoods. Open source software: the Exploratory Spatial Data Analysis software GeoDa and the GIS software Quantum GIS will be used in practical sessions.

The first two days of the course will focus particularly on exploring and mapping data released pre-aggregated to a commonly used geographical unit (polygon area) such as the standard statistical geographies data zones, super output areas or census tracts (for example Census data or data released by Scottish Neighbourhood Statistics). We will also briefly look at how to produce maps providing context about an area (e.g. roads, rivers, administrative boundaries) and how you might visualise your own individual level data with a geographic identifier at an aggregate level.

The third day will give participants an introduction to the key exploratory spatial data analysis concepts of spatial autocorrelation and Local Indicators of Spatial Association (LISA). Day 3 will focus on how to explore and visualise whether there are underlying spatial associations in data relating to place (e.g. data on neighbourhoods or regions) and understanding why this might be useful.

Learning outcomes –

The course will give participants:

Days 1 and 2

• A knowledge of the functional capabilities of GIS

• An understanding of ways in which we can analyse geographic information

• Knowledge and experience of visualising geographic information

• A brief introduction to some key sources of socio-economic data and related geographic contextual data available within the UK

• Knowledge and experience of methods they can use to map their own data

Day 3

• An understanding of the concept of spatial autocorrelation

• A brief introduction to different types of spatial weights

• Knowledge and experience in how test for global spatial autocorrelation (Moran’s I) and discussion of its’ possible implications for data analysis

• An understanding and experience of how to explore local spatial associations within and between data using Local Indicators of Spatial Association focusing on how to test for and visualise two types of LISA (Local Moran’s I and Getis and Ord’s Gi and Gi*)

• A brief introduction to some of the issues around assessing significance of LISA measures

• A brief discussion of the potential implications of spatial association in data for wider data analysis

Cost:

Various - depends upon job title/position

Website and registration:

https://www.aqmen.ac.uk/events/Jun2016/GIS

Region:

Scotland

Keywords:

Data Quality and Data Management , Quantitative Data Handling and Data Analysis

Related publications and presentations:

Data Quality and Data Management
Quantitative Data Handling and Data Analysis

Back to archive...