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2019/20 Taught Postgraduate Module Catalogue

GEOG5042M Geographic Data Visualisation & Analysis

15 creditsClass Size: 150

Module manager: Helen Durham

Taught: Semester 1 View Timetable

Year running 2019/20

This module is mutually exclusive with

GEOG5032MGIS Data Visualisation & Analysis

Module replaces

GEOG5947M Consumer Data Analytics & VisualisationGEOG5010M Principles of GISGEOG5520M Quantitative and Spatial MethodsGEOG5740M Intro to 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.


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 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

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.


As relevant to a student’s programme of study, lectures and practicals will cover:

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

N.B. Students will study a programme-specific pathway to ensure that they receive the necessary skills training for their programme of study – delivery type and number of each type of session might differ depending on your programme but will be similar contact hours and private study hours across all programmes. The teaching method summary given below is an example of the teaching methods for one programme-specific pathway and you will be given details of your programme’s teaching sessions upon commencement of the module.

Teaching methods

Delivery typeNumberLength hoursStudent hours
Private study hours125.00
Total Contact hours25.00
Total hours (100hr per 10 credits)150.00

Private study

Undertaking core and wider reading, research and preparation of independent assessed work.
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
Portfolio4 Practical outputs (equivalent to 1,000 words)20.00
ReportGuided Report (equivalent to 3000 words)80.00
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: 30/04/2019


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