Land use / cover change processes in less developed countries are typically rapid and extensive, and they often include a considerable proportion of unplanned or informal development. Land use / cover change models can help to understand, analyse and simulate the outcomes of such processes, providing information that can inform policy development. This course develops the student's conceptual understanding of three methods for modelling land use / cover change and their ability to select, develop and apply these methods in an appropriate manner. The methods to be examined are: spatial logistic regression for identifying drivers of land use / cover change, Cellular Automata (CA) models and Agent Based Models (ABMs). The course commences with introductory lectures, readings and discussions on the field of land use / cover change modelling. The three methods will be introduced with an urban case study using the modelling platform NetLogo. In the group work phase, students can choose their own application case and apply in depth one of the methods.