Proposal Description

Rich spatiotemporal data sources are required for effective environmental and ecological planning and management. With rapid advances in technology, there has been an increase in available potential sources of data to aid such investigations. Relevant data sources are potentially of both structured and unstructured forms and could contain: measurements from in-situ monitoring, automatic sensors, satellite, aircraft and drone imagery, or be obtained from photographs, images, citizen science surveys, transcripts, social media posts. The challenge then lies in how to appropriately link such data sources in order to provide the most informative picture to inform environmental protection. This session will present novel statistical and AI approaches for such data fusion and integration of both qualitative and quantitative data. A range of cutting-edge environmental applications are covered from the GALLANT: Glasgow as a Living Lab Accelerating Novel Transformation, ReefCloud and air pollution projects.