Landscape Ecology with Geographical Information Systems, PGCert/PGDip/MSc

Overview
This programme equips graduates with the skills required for professional roles involving collection, management, analysis and presentation of landscape ecology and environmental conservation datasets using Geographical Information Systems (GIS).
In both the UK and overseas the concept of landscape scale land management has gained acceptance over the last decade. The implementation of environmental conservation policies and strategies based on a landscape ecology approach is increasingly dependent on spatial data that are managed and manipulated within a GIS. As a result, the Ecological Skills Gap Project has identified a clear need for ecologists with experience of GIS and for GIS specialists with an understanding of the environmental data they are being asked to manage and manipulate within a GIS.
This programme is designed to address these skills gaps and is structured around three compulsory conservation courses that integrate theoretical and practical aspects of contemporary conservation and environmental management, and three compulsory courses covering the principles and implementation of GIS. Additionally students take a compulsory Professional Practice for GI course, and one optional course. The MSc programme culminates in a third term with the dissertation, an individual piece of research focused on the application of GIS techniques to a specific landscape ecology problem.
Outcomes
The aims of the programme are to:
Provide landscape ecology practitioners and conservation managers with an appreciation of the merits and limitations of the spatial data that are potentially available to them
Provide an understanding of how these data can potentially be processed and managed within a GI System; encompassing data collection strategies, errors, uncertainties, GIS modelling, and GIS decision support systems
Provide the knowledge and skills to confidently operate and manage a GI system for landscape ecology and environmental conservation data sets.