A0478
Title: Spatiotemporal data fusion for environmental applications
Authors: Craig Wilkie - University of Glasgow (United Kingdom) [presenting]
Claire Miller - University of Glasgow (United Kingdom)
Marian Scott - University of Glasgow (United Kingdom)
Surajit Ray - University of Glasgow (United Kingdom)
Daniela Castro-Camilo - University of Glasgow (United Kingdom)
Daniela Cuba - Agricarbon UK (United Kingdom)
Stephen Jun Villejo - University of Glasgow (United Kingdom)
Pietro Colombo - University of Glasgow (United Kingdom)
Abstract: A summary of recent work is presented on data fusion methods for spatiotemporal environmental applications. The increasing availability of environmental data from multiple sources, such as satellites and low-cost sensors, provides an improved understanding of the changing environment. Data from these sources can, however, be of varying quality, often on different spatial and temporal scales. Data fusion approaches aim to combine information from multiple complementary data sources to provide an enhanced understanding of environmental variables compared to using any single data source, with associated uncertainty measures accounting for differences in the quality of information from each source. A summary of recent work is presented on data fusion methods, with a focus on some work by early-career researchers.
