Curriculum Information

This module will explore the use of multiple technologies in the field of wildlife conservation, including:

§  Geospatial software and online apps including QGIS and ArcPro

§  Geospatial analysis in R

§  Data derived from field technologies e.g., Global Positioning Systems (GPS), camera traps, Unmanned Aerial Vehicles (UAVs), Passive acoustic monitors

§  Artificial Intelligence (AI), machine learning, neural networking and big data

§  Satellite imagery selection and correction

§  Land cover classification methods and accuracy assessment

§  LiDAR and terrestrial laser scanning

Topics explored will include Species distribution modelling and range shifts under climate change, Home range delineation from GPS tag data, Multi criteria decision making for site suitability e.g., for species reintroduction, Coral reef and tropical forest structural analysis, and Land cover change analysis.

The module focuses on development of professional skills in conservation technology, including new and emerging technologies such as AI and machine learning. Activities throughout the module include the use of real-world case studies and application of technology to solving real-world problems. Students will use industry-standard software and hardware to address contemporary case studies in practical applications of conservation technology. Case studies used are linked to staff research expertise and make use of existing databases and datasets.  Students are provided with tutorials to follow at their own pace and are expected to work independently outside of class time to complete a range of skills development activities, linked to assessments.

This module is largely computer-based – working with a variety of industry-standard software and a range of data types, enabling digital fluency within the field of wildlife conservation and management, which is highly beneficial to future employability.