This module is comprised of two parts. Part I focuses on spatially distributed dynamic models with particular emphasis on environmental modelling. A range of spatially distributed models will be studied from application areas such as forestry, climate change, and land use planning. Subjects such as model calibration and validation, sensitivity analysis and what-if scenarios are covered, and students should be able to recognise the different types of spatially distributed model by the end of the module. In Part II of the module, the focus is on techniques and concepts in spatial data handling. This encompasses issues such as geospatial data systems, accessing and inputting data, measuring accessibility, and issues of temporal representation and uncertainty. There will be some coverage of Python coding for GIS applications, though this will not be assessed.
It should be emphasised that the methods and techniques used, and the skills developed in both halves of the course, are applicable across the breadth of quantitative geography (whether human or physical) and environmental science.
