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Satellite remote sensing of phytoplankton phenology in Lake Balaton using 10 years of MERIS observations
Phytoplankton biomass is important to monitor in lakes due to its influence on water quality and lake productivity. Phytoplankton has also been identified as sensitive to environmental change, with shifts in the seasonality of blooms, or phenology, resulting from changing temperature and nutrient conditions. A satellite remote sensing approach to retrieving and mapping freshwater phytoplankton phenology is demonstrated here in application to Lake Balaton, Hungary. Chlorophyll-a (chl-a) concentration mapping using Medium Resolution Imaging Spectrometer (MERIS) allows new insights into such spatiotemporal dynamics for Lake Balaton as bloom start, peak and end timing, duration, maximum chl-a concentrations, spatial extent, rates of increase and decrease, and bloom chl-a concentration integral. TIMESAT software is used to extract and map these phenology metrics. Three approaches to time series smoothing are compared and mapped metrics are evaluated in comparison with phenology metrics of in situ chl-a. The high degree of both spatial and temporal variability is highlighted and discussed, as are methodological limitations and correlation between phenology metrics. Both the feasibility of and novel insights permitted through such phenology mapping are demonstrated, and priority topics for future research are suggested. GIONET, funded by the European Commission, Marie Curie Programme Initial Training Network, Grant Agreement PITN-GA-2010-264509, NERC-funded GloboLakes project (NE/J024279/1, ESA Diversity-II project (ESRIN/AO/1-7025/12/I-LG). S. Palmer was supported by a doctoral scholarship from the Fonds de Recherche du Québec — Nature et Technologies (B2-05D-146316). H. Balzter was supported by the Royal Society Wolfson Research Merit Award, 2011/R3. Peer-reviewed Publisher Version
Satellite remote sensing of phytoplankton phenology in Lake Balaton using 10 years of MERIS observations
Phytoplankton biomass is important to monitor in lakes due to its influence on water quality and lake productivity. Phytoplankton has also been identified as sensitive to environmental change, with shifts in the seasonality of blooms, or phenology, resulting from changing temperature and nutrient conditions. A satellite remote sensing approach to retrieving and mapping freshwater phytoplankton phenology is demonstrated here in application to Lake Balaton, Hungary. Chlorophyll-a (chl-a) concentration mapping using Medium Resolution Imaging Spectrometer (MERIS) allows new insights into such spatiotemporal dynamics for Lake Balaton as bloom start, peak and end timing, duration, maximum chl-a concentrations, spatial extent, rates of increase and decrease, and bloom chl-a concentration integral. TIMESAT software is used to extract and map these phenology metrics. Three approaches to time series smoothing are compared and mapped metrics are evaluated in comparison with phenology metrics of in situ chl-a. The high degree of both spatial and temporal variability is highlighted and discussed, as are methodological limitations and correlation between phenology metrics. Both the feasibility of and novel insights permitted through such phenology mapping are demonstrated, and priority topics for future research are suggested. GIONET, funded by the European Commission, Marie Curie Programme Initial Training Network, Grant Agreement PITN-GA-2010-264509, NERC-funded GloboLakes project (NE/J024279/1, ESA Diversity-II project (ESRIN/AO/1-7025/12/I-LG). S. Palmer was supported by a doctoral scholarship from the Fonds de Recherche du Québec — Nature et Technologies (B2-05D-146316). H. Balzter was supported by the Royal Society Wolfson Research Merit Award, 2011/R3. Peer-reviewed Publisher Version
Satellite remote sensing of phytoplankton phenology in Lake Balaton using 10 years of MERIS observations
Palmer, S. C. J (author) / Odermatt, D / Hunter, P. D / Brockmann, C / Présing, M / Balzter, Heiko / Tóth, V. R
2015
Article (Journal)
English
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