Presentation: Remote sensing as a monitoring strategy for aquatic litter

Shungu Garaba is a scientist at the University of Oldenburg in Germany. He has expertise in hyperspectral remote sensing technologies on floating, airborne and satellite platforms. The dataset gathered from various remote sensing technologies is important in his research focusing on water quality and floating litter monitoring. Current efforts are towards remote sensing applications in monitoring from source to sink of mismanaged plastics in the blue planet. The goals of his research is to develop proxy indicators derived from remote sensing dataset for aquatic litter based on classic empirical approaches and modern machine learning algorithms utilizing information from the ultraviolet to longwave infrared spectrum.