Modules

The degree consists of compulsory modules in term 1 and pathways* or recommended modules in terms 2 and 3, alongside a final dissertation in term 3.  

Urban Spatial Science MRes 

Urban Spatial Science 

Compulsory modules (135 credits and dissertation) 

• CASA0005: Geographic Information Systems and Science (15 credits) – term 1 
• CASA0007: Quantitative Methods (15 credits) – term 1 
• CASA0001: Urban Systems Theory (15 credits) – term 1 
• CASA0004: Urban Spatial Science Dissertation (90 credits) - term 3 

Smart Cities and Urban Policy Pathway 

• CASA0008: Smart Cities: Context, Policy and Government (15 credits) – term 2 
• CASA0002: Urban Simulation (15 credits) – term 2 
• CASA0023: Remotely Sensing Cities and Environments (15 credits) - term 2  

Data Visualisation Pathway 

• CASA0006: Data Science for Spatial Systems (15 credits) - term 2 
• CASA0003: Digital Visualisation: Group Mini Project (30 credits) - term 2 

Urban Modelling and Simulation Pathway 

• CASA0006: Data Science for Spatial Systems (15 credits) - term 2 
• CASA0011: Agent Based Modelling for Spatial Systems (15 credits) – term 2 
• CASA0002: Urban Simulation (15 credits) – term 2 

The pathways are recommended combinations of optional modules, but students are open to take any combination of the above optional modules up to 45 credits. In addition to the modules listed above (on other pathways) students can choose from the following optional CASA module:

• CASA0013: Foundations of Spatial Data Science (formerly Introduction to Programming for Spatial Analysts) (15 credits) – term 1 

Alternatively students can select up to one 15 credit elective module from outside of CASA. This elective module must be relevant to the overall MRes Urban Spatial Science degree. Departments at UCL with suitable relevant elective modules include Geography, Civil Environmental & Geomatic Engineering, Computer Science, the Bartlett School of Architecture and the Bartlett School of Planning.

*Pathway modules may change annually, but sufficient choice will be offered to represent the current expertise of the department.