Module manager: Rachel Oldroyd
Email: r.oldroyd@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2022/23
| GEOG5032M | GIS Data Visualisation & Analysis |
| GEOG5052M | Environmental Data Visualisation & Analysis |
GEOG5947M Consumer Data Analytics & Visualisation GEOG5010M Principles of GIS GEOG5520M Quantitative and Spatial Methods GEOG5740M Intro to GIS GEOG5510M Using GIS
This module is not approved as an Elective
This module develops core visualisation and spatial analysis and statistical skills required for the analysis of geographically referenced data. Students are introduced to ‘traditional’ and ‘novel’ datasets at different spatial scales and granularities related to areas, individuals, households and neighbourhoods. Taught through lectures and primarily via fully-supported practical activities, students will gain a comprehensive knowledge of powerful industry-standard Geographic Information Systems (GIS) as a tool for mapping and spatial analysis and become familiar with spatial units, concepts and techniques that are used to analyse quantitative human data. Students gain familiarity in applying statistical analysis techniques to explore geographic data. The module equips students to produce and communicate high quality outputs that can be used to inform decision making. This module provides students with the quantitative skills and familiarity with different types of data to enable them to undertake subsequent modules and independent research.
As relevant to a student’s programme of study, this module seeks to:
- Introduce and deliver core techniques in spatial and statistical analysis and visualisation as required for quantitative analysis of spatial data
- Give students the opportunity to work with and critically evaluate a range of spatial datasets which may be:
Socio-economic sources at different scales (as individuals, households and neighbourhoods) including `traditional’ (e.g. census and survey) and novel (e.g. transactional) sources;
- Enable students to carry out quantitative analysis, data exploration and visualisation using core industry standard geographical information systems and statistical packages
On completion of this module, students will:
1. Have a theoretical knowledge of core spatial and statistical analysis and visualisation techniques suitable for the analysis of geographically referenced data
2. Be able to apply and critique appropriate statistical and spatial analytical techniques using core industry standard geographical information systems and statistical packages
3. Critically assess insights derived from the analysis of traditional and novel spatial datasets and communicate findings and insight supported by appropriate visualisation tools.
As relevant to a student’s programme of study, lectures and practicals will cover:
Introduction to key sources of spatial data related to socio-economics, households and neighbourhoods
Introduction to spatial data, including types of spatial data, geographical referencing, spatial units and geographical building blocks.
Application of core GIS techniques: spatial and network analysis and spatial data visualisation
Statistical analysis – descriptive statistics, correlation & regression
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Lectures | 4 | 2.5 | 10 |
| Practical | 4 | 2 | 8 |
| Private study hours | 132 | ||
| Total Contact hours | 18 | ||
| Total hours (100hr per 10 credits) | 150 | ||
Undertaking core and wider reading, research and preparation of independent assessed work.
Independent work on practical activities outside of timetabled practical session.
Students will be supported through the practical sessions which will allow informal monitoring of progress and verbal feedback. In addition, students will submit weekly outputs from the practical sessions for written formative feedback.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Portfolio | 4 Practical outputs (equivalent to 1,000 words) | 0 |
| Report | Guided Report (equivalent to 3000 words) | 100 |
| Total percentage (Assessment Coursework) | 100 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
There is no reading list for this module
Last updated: 29/04/2022
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