2020/21 Undergraduate Module Catalogue
GEOG3195 Geocomputation and Spatial Analysis
20 creditsClass Size: 70
Module manager: Alexis Comber
Email: a.comber@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2020/21
Module replaces
The Geocomputation component of Geocomputation and Geoplanning (GEOG3150).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.Objectives
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)
Syllabus
- 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 type | Number | Length hours | Student hours |
| Lecture | 10 | 2.00 | 20.00 |
| Practical | 10 | 2.00 | 20.00 |
| Private study hours | 160.00 | ||
| Total Contact hours | 40.00 | ||
| 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
Coursework
| Assessment type | Notes | % of formal assessment |
| Report | 2,500 word project | 100.00 |
| 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 websiteLast updated: 05/08/2020 17:04:15
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