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2020/21 Taught Postgraduate Module Catalogue

GEOG5032M GIS Data Visualisation & Analysis

30 creditsClass Size: 50

Module manager: Helen Durham

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2020/21

This module is mutually exclusive with

GEOG5042MGeographic Data Visualisation & Analysis

Module replaces

GEOG5010M: Principles of GISGEOG5520M: Quantitative and Spatial MethodsGEOG740M: Introducing GISGEOG5510M: Using GIS

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.


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;
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 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. Develop the skills to design, execute and critically evaluate an independent analysis project using software, techniques and data resources introduced within this module.


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 and network analysis and spatial data visualisation

Statistical analysis – descriptive statistics, correlation & regression

Spatial clustering of phenomena

Raster analysis of environmental data

Interpolation of data to surfaces

Teaching methods

Delivery typeNumberLength hoursStudent hours
Private study hours252.00
Total Contact hours48.00
Total hours (100hr per 10 credits)300.00

Private study

Undertaking core and wider reading, research and preparation of independent assessed work and final project.
Independent work on practical activities outside of timetabled practical session.

Opportunities for Formative Feedback

Students will submit a practical output at the end of Unit 1 for formative feedback.
Student progress monitored via informal formative assessment of student progress during practical sessions. Since students should be compiling their portfolio on an ongoing basis, this can be viewed during practical sessions to ensure their skillset and understanding are progressing.

Methods of assessment

Assessment typeNotes% of formal assessment
Portfolio9 Practical outputs (equivalent to 2,000 words)0.00
ReportGuided report (equivalent to 3,000 words)50.00
ReportGuided report (equivalent to 3,000 words)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: 05/08/2020 17:04:15


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