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Unit information: Mapping and Modelling Geographic Data in R in 2025/26

Please note: Programme and unit information may change as the relevant academic field develops. We may also make changes to the structure of programmes and assessments to improve the student experience.

Unit name Mapping and Modelling Geographic Data in R
Unit code GEOGM0046
Credit points 20
Level of study M/7
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Dr. Timmerman
Open unit status Not open
Units you must take before you take this one (pre-requisite units)

Participants will benefit from an understanding of statistics, including descriptive and inferential statistics, and linear regression. Experience in command-line coding will be beneficial but is not essential.

Units you must take alongside this one (co-requisite units)

None.

Units you may not take alongside this one

None.

School/department School of Geographical Sciences
Faculty Faculty of Science

Unit Information

This unit introduces students to principles of Geographic Data Science in R, with a focus on mapping and modelling geographic data in R, a popular open source statistical and computing environment that offers both GIS and spatial statistical functionality suitable for research and other applications.

The unit focuses on visualisation – especially geographic visualisation (maps) – methods of GIS and their implementation in R, and on spatial analysis: measures of spatial dependency, spatial regression and geographically weighted statistics.

The aims of the unit are:

  • To provide an introduction to coding in R
  • To use R as a tool for visualisation and the mapping of geographic data
  • To teach what is meant by a spatial weights matrix and how it can be specified in R
  • To show how the spatial weights matrix is used in methods of spatial analysis and regression.

Your learning on this unit

Upon successful completion of this unit, students will be able to:

  1. Apply R to map and model geographic data
  2. Employ methods of spatial analysis to detect, to allow for and to model patterns of geographical clustering
  3. Describe and discuss the differences between global and local approaches
  4. Describe and discuss the centrality of a spatial weights matrix to most spatial analysis
  5. Appky R as a software environment for geographic data science

How you will learn

The unit will be taught through lectures, computer practicals, asynchronous individual activities, and online resources.

How you will be assessed

Tasks which count towards your unit mark (summative):

Data analysis project and report, written using R Markdown (100%). The assessment tests all the ILOs.

When assessment does not go to plan

Students will be offered an alternative assessment for completion in the summer reassessment period, of a similar format to that of the original submission.

Resources

If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.

If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. GEOGM0046).

How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours of study to complete. Your total learning time is made up of contact time, directed learning tasks, independent learning and assessment activity.

See the University Workload statement relating to this unit for more information.

Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit. The Board considers each student's outcomes across all the units which contribute to each year's programme of study. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates within the Regulations and Code of Practice for Taught Programmes.

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