Information and Data Science|Operational Modelling

AGENT-BASED MODELS|URBAN ANALYTICS|TRAFFIC MODELLING|PEDESTRIAN MODELLING|TRANSPORT MODELLING

This module will introduce students to the design and use of agent-based models (ABMs) in a variety of urban analytical contexts. The course will employ a...

Agent-based Modelling for Spatial Systems (CASA0011)

This module will introduce students to the design and use of agent-based models (ABMs) in a variety of urban analytical contexts. The course will employ a hands-on approach, with practical sessions guiding students through the construction of example models, building up to producing their own simulations and using them to conduct experiments.

Themes covered in this module will include:

Cellular Automata
	Presenting ABMs using the Overview Design Detail (ODD) Protocol
	Modelling competition among agents
	Optimisation of ABM performance
	Using ABM to make forecasts and predictions
	Integration of ABM and GIS
The module will further cover the history and development of the field, as well as current trends, focusing particularly on the evaluation of model outcomes. It will address applications such as pedestrian movement, traffic and transportation, land use, evacuations and crises, and basic epidemiology.

Models will be built using specialist agent-modelling software and/or programming packages (e.g. NetLogo and/or MESA).

Data Collection and Processing|Information and Data Science|Spatial Data Acquisition|Web development

ADVANCED ANALYSIS|SPATIAL DATASETS|DATABASES|SQL|DATA VALIDATION|DATA ANALYSIS|INTERACTIVE

The purpose of this module is to provide students with both the technical and the critical skills required for the treatment, analysis and presentation of...

Spatial Data Capture, Storage and Analysis (CASA0009)

The purpose of this module is to provide students with both the technical and the critical skills required for the treatment, analysis and presentation of spatial datasets. In line with this objective, the course is divided into three main themes. In the first, database concepts and techniques are introduced, providing the students with the skills required for manipulating databases. SQL syntax will be taught in depth at this stage, with a strong emphasis on practical application. The second phase of the course moves towards covering the practical skills required in data handling and analysis. Students will first learn how to manage and validate raw, unprocessed data, before moving onto exploring methods for deriving deeper insight into trends in data. The third and final element of the course moves into the presentation of data, introducing web development practices that enable the interactive visualisation and interrogation of complex datasets. In this section of the course, students will learn the techniques necessary to take datasets from the database through to interactive analysis and visualisation.