Module manager: Helen Durham
Email: H.P.Durham@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2024/25
| GEOG5001M | GIS Data Visualisation and Analysis 1 |
| GEOG5002M | GIS Data Visualisation and Analysis 2 |
| GEOG5032M | GIS Data Visualisation & Analysis |
| GEOG5052M | Environmental Data Visualisation & Analysis |
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 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
- Provide an opportunity for students to independently carry out and critically evaluate spatial and statistical analyses
On successful completion of the module you will be able to:
1. Demonstrate a theoretical knowledge of core spatial and statistical analysis and visualisation techniques suitable for the analysis of geographically referenced data
2. Appl and critique appropriate statistical and spatial analytical techniques in predominantly vector applications 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 supported by appropriate visualisation tools.
4. Implement the skills learnt to execute and critically evaluate an independent analysis project using software, techniques and data resources introduced within this module
Skills Learning Outcomes
On successful completion of the module students will have demonstrated the following skills learning outcomes:
5. Work-ready skills: Communication
6. Digital skills: Digital proficiency and productivity
7. Work-ready skills: Problem solving and analytical skills
Details of the syllabus will be provided on the Minerva organisation (or equivalent) for the module
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Lectures | 4 | 2 | 8 |
| Practical | 4 | 2 | 8 |
| Independent online learning hours | 32 | ||
| Private study hours | 102 | ||
| Total Contact hours | 16 | ||
| Total hours (100hr per 10 credits) | 150 | ||
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 formative feedback.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Assignment | Coursework | 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: 29/04/2024
Errors, omissions, failed links etc should be notified to the Catalogue Team