2024/25 Taught Postgraduate Module Catalogue

GEOG5001M GIS Data Visualisation and Analysis 1

15 creditsClass Size: 40

Module manager: Nick Hood
Email: n.a.hood@leeds.ac.uk

Taught: 01 Oct to 31 Dec, 1 Sep to 31 Dec (adv yr) View Timetable

Year running 2024/25

This module is mutually exclusive with

GEOG5032M	GIS Data Visualisation & Analysis
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 various contexts. Taught through instructional notes and 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 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
- 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. Be able to develop 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. Be able to critically assess insights derived from the analysis of traditional and novel spatial datasets and communicate findings and insight supported by appropriate visualisation tools.
4. Be able to design, execute and critically evaluate a ‘guided’ socio-economic 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:
1. Academic. Assessed work will involve academic writing which requires students to report on their work in a concise and evidence-based way, with integrity. Within the module students will be expected to plan, organise and manage their time effectively to meet deadlines. There will be opportunities for students to work autonomously on a guided socio-economic project report..
2. Digital. Students will use digital technology to demonstrate spatial analysis skills by using digital tools.
3. Work-ready. Using widely-used tools for computational analysis, students will develop technical and IT skills valued in the workplace. Through the assessments, students will develop their problem-solving skills through being expected to apply decision-making strategies, applying their critical thinking and analytical skills.
4. Technical. Through the use of appropriate software and analytical environments for modern GIS analysis, students will develop and apply a range of technical skills.
5. Sustainability. Since the module covers, conceptually and practically, aspects of human behaviour, students will be introduced to systems-level thinking, with a particular focus on voting behaviour.
6. Enterprise. Through the modules activities, students will have the opportunity to develop enterprise skills through participating in learning activities which develop their ability to spot opportunities, solve problems and develop creative solutions to GIS tasks. They will have the opportunity to develop their enterprise skills through self-directed learning (private study) and project-based learning, working on ‘live’ real-world data sets.

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
Supervision	8	1.00	8.00
Discussion forum	8	2.00	16.00
Independent online learning hours			48.00
Private study hours			78.00
Total Contact hours			24.00
Total hours (100hr per 10 credits)			150.00

Opportunities for Formative Feedback

Formative feedback will be provided during practical activities where students will be encouraged to post outputs to devoted unit-by-unit discussion boards. This will allow for peer critique in addition to staff comments. Note that the outputs requested here will differ from those required as part of the summative assessments.

The module leader will also be on hand to provide support (email / Teams / discussion board / etc) during the teaching weeks, in advance of assessment. Whilst not directly formative assessment, this will ensure that the students receive feedback / support on matters of need.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Assignment	Coursework	80.00
Assignment	Coursework	20.00
Total percentage (Assessment Coursework)		100.00

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

Reading list

The reading list is available from the Library website

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

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