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The Coastal Surveillance Through Observation of Ocean Color (COASTℓOOC) dataset
oleh: P. Massicotte, M. Babin, M. Babin, F. Fell, V. Fournier-Sicre, V. Fournier-Sicre, D. Doxaran
| Format: | Article |
|---|---|
| Diterbitkan: | Copernicus Publications 2023-08-01 |
Deskripsi
<p>Coastal Surveillance Through Observation of Ocean Color (<span class="inline-formula">COASTℓOOC</span>) oceanographic expeditions were conducted in 1997 and 1998 to examine the relationship between the optical properties of seawater and related biological and chemical properties across the coastal to open-ocean gradient in various European seas. A total of 379 stations were visited along the coasts of the Gulf of Lion in the Mediterranean Sea (<span class="inline-formula"><i>n</i>=61</span>), the Adriatic Sea (<span class="inline-formula"><i>n</i>=39</span>), the Baltic Sea (<span class="inline-formula"><i>n</i>=57</span>), the North Sea (<span class="inline-formula"><i>n</i>=99</span>), the English Channel (<span class="inline-formula"><i>n</i>=85</span>), and the Atlantic Ocean (<span class="inline-formula"><i>n</i>=38</span>). Particular emphasis was placed on the collection of a comprehensive set of apparent and inherent optical properties (AOPs and IOPs) to support the development of ocean color remote-sensing algorithms. The data were collected in situ using traditional ship-based sampling but also from a helicopter, which is a very efficient means for that type of coastal sampling. The dataset collected during the <span class="inline-formula">COASTℓOOC</span> campaigns is unique in that it is fully consistent in terms of operators, protocols, and instrumentation. This rich and historical dataset is still today frequently requested and used by other researchers. Therefore, we present the result of an effort to compile and standardize a dataset which will facilitate its reuse in future development and evaluation of new bio-optical models adapted for optically complex waters. The dataset is available at <a href="https://doi.org/10.17882/93570">https://doi.org/10.17882/93570</a> <span class="cit" id="xref_paren.1">(<a href="#bib1.bibx43">Massicotte et al.</a>, <a href="#bib1.bibx43">2023</a>)</span>.</p>