Monitoring of phytoplankton – the photosynthetic primary producers – in inland waters has been a bottleneck of environmental observation due to the overwhelming signal from the background, including humic compounds in the water. Now, new sensor and computing technologies have brought this issue to a turning point. The aim of this research is to develop a generalizable method to resolve optical signals of functional groups of phytoplankton mixed with the background. This will be reached by deploying laboratory-based hyperspectral imaging and novel satellite-mounted imagers together with computational models to resolve and classify inherent optical features of phytoplankton amongst the water colour component. The methodology developed here enables a robust and efficient monitoring of ecological status inland waters despite the water colour. This would open great possibilities to ecosystem-level research of boreal landscapes, in temporal and spatial coverages that was impossible before.

2023

2025