CASA0023 Remotely Sensing Cities and Environments

This module will enable students to operationalise remotely sensed Earth observation data for informing decisions on environmental hazards arising from a changing climate, specifically in relation to (a) urban areas and (b) future urban sustainability

Firstly, the module presents an overview of the core concepts, methods and practices used to pre-process imagery underlying the discipline. Building upon this, the content focuses on advanced methodologies to extract meaning from Earth observation data and combinations of spatial data. It will examine and provide specific applied examples of achievable local, national and international policy modifications to incorporate spatial data and analytical requirements allowing data-driven optimisation of resources, maximising investment, environmental and sustainability outcomes. The module has a large practical component that is primarily taught in the R data science programming language but will briefly cover some specialist tools such as opensource geographic information systems software and cloud computing. Students will gain an operational knowledge of Earth observation data that can be drawn upon in future research or employment. The practical book for the module is available online for more detail on weekly content, however this can change annually.