Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/21422
Appears in Collections:Biological and Environmental Sciences Journal Articles
Peer Review Status: Refereed
Title: Satellite remote sensing of phytoplankton phenology in Lake Balaton using 10 years of MERIS observations
Author(s): Palmer, Stephanie
Odermatt, Daniel
Hunter, Peter
Brockmann, Carsten
Presing, Matyas
Balzter, Heiko
Toth, Victor
Contact Email: p.d.hunter@stir.ac.uk
Keywords: Phenology
Phytoplankton
Inland waters
Remote sensing
Seasonality
TIMESAT
MERIS
Lake Balaton
Issue Date: 1-Mar-2015
Date Deposited: 30-Jan-2015
Citation: Palmer S, Odermatt D, Hunter P, Brockmann C, Presing M, Balzter H & Toth V (2015) Satellite remote sensing of phytoplankton phenology in Lake Balaton using 10 years of MERIS observations. Remote Sensing of Environment, 158, pp. 441-452. https://doi.org/10.1016/j.rse.2014.11.021
Abstract: 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.
DOI Link: 10.1016/j.rse.2014.11.021
Rights: © 2014 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by3.0/).
Licence URL(s): http://creativecommons.org/licenses/by/4.0/

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