2024/25 Taught Postgraduate Module Catalogue

GEOG5032M GIS Data Visualisation & Analysis

30 creditsClass Size: 50

Module manager: Helen Durham
Email: H.P.Durham@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2024/25

This module is mutually exclusive with

GEOG5001M	GIS Data Visualisation and Analysis 1
GEOG5002M	GIS Data Visualisation and Analysis 2
GEOG5042M	Geographic Data Visualisation & Analysis
GEOG5052M	Environmental Data Visualisation & Analysis

This module is not approved as an Elective

Module summary

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 in both human and environmental contexts. 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 and environmental 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.

Objectives

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’ and novel sources; Environmental sources, for example, including landscape, indicators of rurality and pollution;
- 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.

Learning outcomes
On successful completion of the module students will have demonstrated the following learning outcomes relevant to the subject:
1. Have a theoretical knowledge of core spatial and statistical analysis and visualisation techniques suitable for the analysis of geographically referenced data
2. Applied and critiqued appropriate statistical and spatial analytical techniques to predominantly vector applications using core industry standard geographical information systems and statistical packages
3. Applied and critiqued appropriate statistical and spatial analytical techniques to predominantly raster applications using core industry standard geographical information systems and statistical packages
4. Critically assess insights derived from the analysis of traditional and novel spatial datasets and communicate findings and insight supported by appropriate visualisation tools.
5. Develop the skills 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:

6. Work-ready skills: Communication
7. Digital skills: Digital proficiency and productivity
8. Work-ready skills: Problem solving and analytical skills

Syllabus

Details of the syllabus will be provided on the Minerva organisation (or equivalent) for the module

Teaching methods

Delivery type	Number	Length hours	Student hours
Workshop	4	5.00	20.00
Lecture	4	2.00	8.00
Practical	4	2.00	8.00
Independent online learning hours			72.00
Private study hours			192.00
Total Contact hours			36.00
Total hours (100hr per 10 credits)			300.00

Opportunities for Formative Feedback

Student progress monitored via informal formative assessment of student progress during practical sessions. In addition, students will submit weekly outputs from the practical sessions for formative feedback.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Assignment	Coursework	50.00
Assignment	Coursework	50.00
Total percentage (Assessment Coursework)		100.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

There is no reading list for this module

Last updated: 29/04/2024 16:14:37

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