2023/24 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 2023/24

This module is mutually exclusive with

GEOG5032M	GIS Data Visualisation & Analysis
GEOG5042M	Geographic 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 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.
4. Design, execute and critically evaluate a ‘guided’ socio-economic project using software, techniques and data resources introduced within this module.

Syllabus

Topics include:

 Introduction to key sources of spatial data related to socio-economics, households and neighbourhoods plus environmental data

 Introduction to spatial data, including types of spatial data, geographical referencing, spatial units and geographical building blocks.

 Application of core GIS techniques: spatial analysis and spatial data visualisation

 Statistical analysis – descriptive statistics, correlation & regression

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

Private study

Private study and online learning includes directed and independent wider reading, independent practical work and researching/undertaking module assessments and related tasks.

Opportunities for Formative Feedback

Formative feedback will be provided via discussion boards where students are encouraged to post questions, comments, practical outputs etc. Note that the outputs requested here will differ from those required as part of the summative portfolio.
The module leader will also provide support via email and Skype/Collaborate Ultra during the software learning stages, in advance of assessment.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Report	Guided report on the application of skills to a socio-economic problem prject	80.00
Portfolio	Weekly outputs from practicals	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: 28/04/2023 14:56:06

Disclaimer

Browse Other Catalogues

• Undergraduate module catalogue
• Taught Postgraduate module catalogue
• Undergraduate programme catalogue
• Taught Postgraduate programme catalogue

Errors, omissions, failed links etc should be notified to the Catalogue Team.PROD