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2022/23 Undergraduate Module Catalogue

GEOG3195 Geocomputation and Spatial Analysis

20 creditsClass Size: 200

Module manager: Alexis Comber

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2022/23

This module is not approved as a discovery module

Module summary

Understanding and modelling socio-economic processes in urban, regional and national systems; spatial modelling, the process of gathering data; spatial analysis, mapping and developing models. This module provides an introduction to key tools used in data analytics research and consultancy.


On completion of the module, students should be able to demonstrate:
- an understanding of key geographic data sources and knowledge of how to extract and manipulate and map them;
- an understanding of what models, how to apply them to spatial and non-spatial data and the basic stages of development;
- in depth knowledge of how to visualise data and spatial data properties;
- through case studies and associated practicals, an understanding of spatial processes and the value of modelling for understanding the present and predicting the future;
- skills in designing, constructing and running models in a basic geocomputation framework and linking the results to a GIS for advanced analysis.

Learning outcomes
At the end of this module students will
- have skills in the handling, processing and manipulation of different data and spatial data;
- understand how to source and extract data and spatial data;
- apply different approaches for visualizing data and spatial data properties and the relationships between them;
- be able to create different types of statistical models for prediction and inference and understand their relative differences;
- apply these in advanced spatial analyses;
- have a broad understanding of modelling different processes in urban and regional systems;
- have an in-depth knowledge of approaches to modelling through advanced spatial analysis, GIS and geocomputation;
- have an understanding of the virtues and limitations of describing geographical systems using modelling, visualisation, geocomputation and GIS techniques.

Skills outcomes
A4 Spatial patterns and relationships in human phenomena at a variety of scales
A9 The theory and application of quantitative, visualisation and other spatial techniques across a wide range of geographical contexts
B1 Abstraction and synthesis of information from a variety of sources
B5 Solving problems and making reasoned decisions
C3 Employ a variety of technical and laboratory-based methods for the analysis and presentation of spatial and environmental information (e.g. GIS, water chemistry, etc)
D3 Apply numerical and computational skills to geographical information
D4 Use information technology effectively (including use of spreadsheet, database and word processing programmes; Internet and e-mail)


- Introduction to Geocomputation
- Introduction to R / RStudio
- Working with data and spatial data (linking, joining, summarising)
- Making statistical models
- Exploratory data analysis
- Data and Spatial Data Visualisation
- Spatial interpolation
- Making spatial models
- Data: Big Data, Portals, APIs, Crowdsourced data
- Geo-demographics and classification
- Transparency and reproducibility in Research

Teaching methods

Delivery typeNumberLength hoursStudent hours
Private study hours160.00
Total Contact hours40.00
Total hours (100hr per 10 credits)200.00

Private study

Students will be provided with a reading list and will be expected to demonstrate evidence of reading in project work and examination.
They will also be expected to critique selected articles.
Students will also be expected to have knowledge/experience of various online information systems and web sites

The project to be handed in at the end of Semester 1 will require independent study and use of R/Rstudio and other software in private study time.

Opportunities for Formative Feedback

The Semester 1 practicals will be a means of monitoring progress halfway through the module. The practicals also allow us to monitor progress and provide instant feedback to students in relation to the development of their projects.

Methods of assessment

Assessment typeNotes% of formal assessment
Report2,500 word project100.00
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: 29/04/2022 15:32:20


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