Programming for Geospatial Science and Visualisation

• Credit value: 30 credits at Level 7
• Convenor and tutor: Roberto Murcio
• Assessment: coding a reproducible analysis in Python programming language (50%) and designing maps and visualisation of spatial data (50%)

In this module, you will acquire the core concepts of programming, using Python as the main language. You will learn how to interact with variables, functions, data structures and control structures, as well as explore contemporary tools to create automated, reproducible geospatial data workflows, both for statistical analysis and visualisation. You will also run introductory analyses with Machine Learning and programming languages. In parallel, you will build on your cartographic skills to acquire the theoretical concepts for the visual analysis and communication of spatial data and develop critical thinking by assessing existing online maps and infographics.

Indicative module syllabus

• Introduction to programming
• Working with data
• Building larger programs
• Visualisation
• Vector and raster data
• Networks
• Mapping
• Principles of geographic machine learning

By the end of this module, you will have:

• acquired core concepts in computer programming (variables, functions, data and control structures)
• written code to perform introductory machine learning analyses
• applied theoretical concepts for the visual analysis and communication of spatial data
• imported, integrated, manipulated and analysed spatial data using contemporary programming tools
• worked with diverse data formats and standards.