Abstract
Shallow and deep lakes receive and recycle organic and inorganic substances from within the confines of these lakes, their watershed and beyond. Hence, a large range in absorption and scattering and extreme differences in optical variability can be found between and within global lakes. This poses a challenge for atmospheric correction and bio-optical algorithms applied to optical remote sensing for water quality monitoring applications. To optimize these applications for the wide variety of lake optical conditions, we adapted a spectral classification scheme based on the concept of optical water types. The optical water types were defined through a cluster analysis of in situ hyperspectral remote sensing reflectance spectra collected by partners and advisors of the European Union 7th Framework Programme (FP7) Global Lakes Sentinel Services (GLaSS) project. The method has been integrated in the Envisat-BEAM software and the Sentinel Application Platform (SNAP) and generates maps of water types from image data. Two variations of water type classification are provided: one based on area-normalized spectral reflectance focusing on spectral shape (6CN, six-class normalized) and one that retains magnitude with no modification to the reflectance signal (6C). This resulted in a protocol, or processing scheme, that can also be applied or adapted for Sentinel-3 Ocean and Land Colour Imager (OLCI) datasets. We apply both treatments to MERIS imagery of a variety of European lakes to demonstrate its applicability. The studied target lakes cover a range of biophysical types, from shallow turbid to deep and clear, as well as eutrophic and dark absorbing waters, rich in colored dissolved organic matter (CDOM). In shallow, high-reflecting Dutch and Estonian lakes with high sediment load, 6C performed better, while in deep, low-reflecting clear Italian and Swedish lakes, 6CN performed better. The 6CN classification of in situ data is promising for very dark, high CDOM, absorbing lakes, but we show that our atmospheric correction of the imagery was insufficient to corroborate this. We anticipate that the application of the protocol to other lakes with unknown in-water characterization, but with comparable biophysical properties will suggest similar atmospheric correction (AC) and in-water retrieval algorithms for global lakes.
Highlights
Freshwater lakes, reservoirs and rivers are an essential resource for human and animal survival.Population increase coupled with change in land use, hydrologic regimes and climate are stressing these systems worldwide, threatening their function as sources for drinking water, socio-economic activities and ecological environments
The resulting water types in each scheme were described by in-water concentrations of chlorophyll-a, colored dissolved organic matter (CDOM) and total suspended matter
While each scheme differs at a fundamental level, they serve the same roles for downstream applications, which in the past have included using them as intermediary products for optimizing bio-optical algorithm selection and as stand-alone products for supporting biogeochemical and biodiversity system analysis
Summary
Freshwater lakes, reservoirs and rivers are an essential resource for human and animal survival.Population increase coupled with change in land use, hydrologic regimes and climate are stressing these systems worldwide, threatening their function as sources for drinking water, socio-economic activities and ecological environments. There has been an increase in the capacity and availability of remote sensing imagery from satellites for lake systems worldwide, promoting the usage and creating new demands for reliable remotely-sensed datasets. These new capabilities stem in part from newly-launched satellites, such as the MultiSpectral Imager (MSI) on board the European Space Agency’s (ESA) Sentinel-2 satellite and the Ocean Land Colour Imager (OLCI) on board ESA’s Sentinel-3 satellite. Resolution Imaging Spectrometer (MERIS) sensor (2002–2012), containing spectral channels well suited to derive bio-optical parameters over the large range of optical conditions exhibited in lakes [1,2].
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
