Programming software (R) and spatial information software (ArcGIS) are used in this subject. R can be downloaded for free. ArcGIS is supplied.
In this subject students are introduced to the fundamentals of spatial modelling in the context of environmental and ecological applications. Students learn how to evaluate different approaches to model the distribution of spatial and spatiotemporal data, at different scales. The practical component provides an in-depth understanding of species distribution modelling using machine learning algorithms. It also includes basic spatiotemporal data visualization and analysis. Students completing this subject will have the ability to apply intermediate knowledge and skills in spatial modelling to address projects dealing with environmental and ecological data analysis and mapping.
HD/FL
One session
School of Environmental Sciences
Postgraduate study only
An understanding of basic mathematics and knowledge of Geographical Information Science equivalent to SPA431
Programming software (R) and spatial information software (ArcGIS) are used in this subject. R can be downloaded for free. ArcGIS is supplied.
The information contained in the CSU Handbook was accurate at the date of publication: October 2020. The University reserves the right to vary the information at any time without notice.