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'?> <record xmlns="http://www.loc.gov/MARC21/slim"> <leader>00000nam##2200000uu#4500</leader> <datafield tag="653" ind1=" " ind2=" "> <subfield code="a">chlorophyll-a; water monitoring; remote sensing; Sentinel-2 MSI; Sentinel-3 OLCI; WISPstation</subfield> </datafield> <controlfield tag="005">20200124192133.0</controlfield> <controlfield tag="001">3617960</controlfield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="a">Pinardi, Monica</subfield> </datafield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="a">Free, Gary</subfield> </datafield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="a">Luciani, Giulia</subfield> </datafield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="a">Ghebrehiwot, Semhar</subfield> </datafield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="a">Laanen, Marnix</subfield> </datafield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="a">Peters, Steef</subfield> </datafield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="a">Della Bella, Valentina</subfield> </datafield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="a">Padula, Rosalba</subfield> </datafield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="a">Giardino, Claudia</subfield> </datafield> <datafield tag="856" ind1="4" ind2=" "> <subfield code="s">6259833</subfield> <subfield code="z">md5:df8db5452ab10a801083f2862c9e3b96</subfield> <subfield code="u">https://zenodo.org/record/3617960/files/water-12-00284.pdf</subfield> </datafield> <datafield tag="542" ind1=" " ind2=" "> <subfield code="l">open</subfield> </datafield> <datafield tag="260" ind1=" " ind2=" "> <subfield code="c">2020-01-18</subfield> </datafield> <datafield tag="909" ind1="C" ind2="O"> <subfield code="p">openaire</subfield> <subfield code="o">oai:zenodo.org:3617960</subfield> </datafield> <datafield tag="100" ind1=" " ind2=" "> <subfield code="a">Bresciani, Mariano</subfield> </datafield> <datafield tag="245" ind1=" " ind2=" "> <subfield code="a">The Use of Multisource Optical Sensors to Study Phytoplankton Spatio-Temporal Variation in a Shallow Turbid Lake</subfield> </datafield> <datafield tag="536" ind1=" " ind2=" "> <subfield code="c">730066</subfield> <subfield code="a">Earth Observation based services for Monitoring and Reporting of Ecological Status</subfield> </datafield> <datafield tag="540" ind1=" " ind2=" "> <subfield code="u">https://creativecommons.org/licenses/by/4.0/legalcode</subfield> <subfield code="a">Creative Commons Attribution 4.0 International</subfield> </datafield> <datafield tag="650" ind1="1" ind2="7"> <subfield code="a">cc-by</subfield> <subfield code="2">opendefinition.org</subfield> </datafield> <datafield tag="520" ind1=" " ind2=" "> <subfield code="a"><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></subfield> </datafield> <datafield tag="773" ind1=" " ind2=" "> <subfield code="n">doi</subfield> <subfield code="i">isVersionOf</subfield> <subfield code="a">10.5281/zenodo.3617959</subfield> </datafield> <datafield tag="024" ind1=" " ind2=" "> <subfield code="a">10.5281/zenodo.3617960</subfield> <subfield code="2">doi</subfield> </datafield> <datafield tag="980" ind1=" " ind2=" "> <subfield code="a">publication</subfield> <subfield code="b">article</subfield> </datafield> </record>
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