The Arctic Frontiers 2017 Most Outstanding Poster Award goes to Katalin Blix, with her poster “Monitoring primary productivity through Chlorophyll-a content estimation in the Arctic”.
“Primary productivity in Arctic oceanic waters can be continuously monitored from space by optical imaging sensors through Chlorophyll-a content. There are several sensors with various spatial and spectral resolution that acquires data over high latitudes.
The Moderate Resolution Imaging Spectroradiometer onboard Aqua (MODIS-Aqua) and Sentinel-3 onboard Ocean and Land Colour Instrument (OLCI), which is the continuity of Medium Resolution Imaging Spectrometer (MERIS) provides data on 1000 m and 300 m spatial resolution, respectively. Chl-a content is estimated by using the state-of-art Ocean Colour (OC) algorithms, for MODIS-Aqua OC3 and for MERIS OC4.
However, these OC algorithms has been shown to under- and/or overestimate Chl-a content when they are applied to Arctic oceanic waters , .
In this poster, we present alternative Chl-a content retrieval models, the Gaussian Process Regression (GPR) and the Partial Least Squares Regression (PLSR) model, for MODIS-Aqua and MERIS.”
Blix, K., Eltoft, T. (2017): Monitoring primary productivity through Chlorophyll-a content estimation in the Arctic. Poster presentations at the Arctic Fr0ntiers 2017, White Space – Blue Future, Tromsø, Norway, 22-27 January, 2017. [intranet]