Journal article Open Access
Bresciani, Mariano; Pinardi, Monica; Free, Gary; Luciani, Giulia; Ghebrehiwot, Semhar; Laanen, Marnix; Peters, Steef; Della Bella, Valentina; Padula, Rosalba; Giardino, Claudia
<?xml version='1.0' encoding='utf-8'?> <resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"> <identifier identifierType="DOI">10.5281/zenodo.3617960</identifier> <creators> <creator> <creatorName>Bresciani, Mariano</creatorName> <givenName>Mariano</givenName> <familyName>Bresciani</familyName> </creator> <creator> <creatorName>Pinardi, Monica</creatorName> <givenName>Monica</givenName> <familyName>Pinardi</familyName> </creator> <creator> <creatorName>Free, Gary</creatorName> <givenName>Gary</givenName> <familyName>Free</familyName> </creator> <creator> <creatorName>Luciani, Giulia</creatorName> <givenName>Giulia</givenName> <familyName>Luciani</familyName> </creator> <creator> <creatorName>Ghebrehiwot, Semhar</creatorName> <givenName>Semhar</givenName> <familyName>Ghebrehiwot</familyName> </creator> <creator> <creatorName>Laanen, Marnix</creatorName> <givenName>Marnix</givenName> <familyName>Laanen</familyName> </creator> <creator> <creatorName>Peters, Steef</creatorName> <givenName>Steef</givenName> <familyName>Peters</familyName> </creator> <creator> <creatorName>Della Bella, Valentina</creatorName> <givenName>Valentina</givenName> <familyName>Della Bella</familyName> </creator> <creator> <creatorName>Padula, Rosalba</creatorName> <givenName>Rosalba</givenName> <familyName>Padula</familyName> </creator> <creator> <creatorName>Giardino, Claudia</creatorName> <givenName>Claudia</givenName> <familyName>Giardino</familyName> </creator> </creators> <titles> <title>The Use of Multisource Optical Sensors to Study Phytoplankton Spatio-Temporal Variation in a Shallow Turbid Lake</title> </titles> <publisher>Zenodo</publisher> <publicationYear>2020</publicationYear> <subjects> <subject>chlorophyll-a; water monitoring; remote sensing; Sentinel-2 MSI; Sentinel-3 OLCI; WISPstation</subject> </subjects> <dates> <date dateType="Issued">2020-01-18</date> </dates> <resourceType resourceTypeGeneral="JournalArticle"/> <alternateIdentifiers> <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3617960</alternateIdentifier> </alternateIdentifiers> <relatedIdentifiers> <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3617959</relatedIdentifier> </relatedIdentifiers> <rightsList> <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights> <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights> </rightsList> <descriptions> <description descriptionType="Abstract"><p>Lake water quality monitoring has the potential to be improved through integrating<br> detailed spatial information from new generation remote sensing satellites with high frequency<br> observations from in situ optical sensors (WISPstation). We applied this approach for Lake Trasimeno<br> with the aim of increasing knowledge of phytoplankton dynamics at dierent temporal and spatial<br> scales. High frequency chlorophyll-a data from the WISPstation was modeled using non-parametric<br> multiplicative regression. The &lsquo;day of year&rsquo; was the most important factor, reflecting the seasonal<br> progression of a phytoplankton bloom from July to September. In addition, weather factors such as<br> the east&ndash;west wind component were also significant in predicting phytoplankton seasonal and diurnal<br> patterns. Sentinel 3-OLCI and Sentinel 2-MSI satellites delivered 42 images in 2018 that successfully<br> mapped the spatial and seasonal change in chlorophyll-a. The potential influence of localized inflows<br> in contributing to increased chlorophyll-a in mid-summer was visualized. The satellite data also<br> allowed an estimation of quality status at a much finer scale than traditional manual methods. Good<br> correspondence was found with manually collected field data but more significantly, the greatly<br> increased spatial and temporal resolution provided by satellite and WISPstation sensors clearly oers<br> an unprecedented resource in the research and management of aquatic resources.</p></description> </descriptions> <fundingReferences> <fundingReference> <funderName>European Commission</funderName> <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/100010661</funderIdentifier> <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/730066/">730066</awardNumber> <awardTitle>Earth Observation based services for Monitoring and Reporting of Ecological Status</awardTitle> </fundingReference> </fundingReferences> </resource>
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