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A database of global coastal conditions

Remote sensing satellite imagery has the potential to monitor and understand dynamic environmental phenomena by retrieving information about Earth’s surface. Marine ecosystems, however, have been studied with less intensity than terrestrial ecosystems due, in part, to data limitations. Data on sea s...

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Autores principales: Castaneda-Guzman, Mariana, Mantilla-Saltos, Gabriel, Murray, Kris A., Settlage, Robert, Escobar, Luis E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8626420/
https://www.ncbi.nlm.nih.gov/pubmed/34836949
http://dx.doi.org/10.1038/s41597-021-01081-9
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author Castaneda-Guzman, Mariana
Mantilla-Saltos, Gabriel
Murray, Kris A.
Settlage, Robert
Escobar, Luis E.
author_facet Castaneda-Guzman, Mariana
Mantilla-Saltos, Gabriel
Murray, Kris A.
Settlage, Robert
Escobar, Luis E.
author_sort Castaneda-Guzman, Mariana
collection PubMed
description Remote sensing satellite imagery has the potential to monitor and understand dynamic environmental phenomena by retrieving information about Earth’s surface. Marine ecosystems, however, have been studied with less intensity than terrestrial ecosystems due, in part, to data limitations. Data on sea surface temperature (SST) and Chlorophyll-a (Chlo-a) can provide quantitative information of environmental conditions in coastal regions at a high spatial and temporal resolutions. Using the exclusive economic zone of coastal regions as the study area, we compiled monthly and annual statistics of SST and Chlo-a globally for 2003 to 2020. This ready-to-use dataset aims to reduce the computational time and costs for local-, regional-, continental-, and global-level studies of coastal areas. Data may be of interest to researchers in the areas of ecology, oceanography, biogeography, fisheries, and global change. Target applications of the database include environmental monitoring of biodiversity and marine microorganisms, and environmental anomalies.
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spelling pubmed-86264202021-12-10 A database of global coastal conditions Castaneda-Guzman, Mariana Mantilla-Saltos, Gabriel Murray, Kris A. Settlage, Robert Escobar, Luis E. Sci Data Data Descriptor Remote sensing satellite imagery has the potential to monitor and understand dynamic environmental phenomena by retrieving information about Earth’s surface. Marine ecosystems, however, have been studied with less intensity than terrestrial ecosystems due, in part, to data limitations. Data on sea surface temperature (SST) and Chlorophyll-a (Chlo-a) can provide quantitative information of environmental conditions in coastal regions at a high spatial and temporal resolutions. Using the exclusive economic zone of coastal regions as the study area, we compiled monthly and annual statistics of SST and Chlo-a globally for 2003 to 2020. This ready-to-use dataset aims to reduce the computational time and costs for local-, regional-, continental-, and global-level studies of coastal areas. Data may be of interest to researchers in the areas of ecology, oceanography, biogeography, fisheries, and global change. Target applications of the database include environmental monitoring of biodiversity and marine microorganisms, and environmental anomalies. Nature Publishing Group UK 2021-11-26 /pmc/articles/PMC8626420/ /pubmed/34836949 http://dx.doi.org/10.1038/s41597-021-01081-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) applies to the metadata files associated with this article.
spellingShingle Data Descriptor
Castaneda-Guzman, Mariana
Mantilla-Saltos, Gabriel
Murray, Kris A.
Settlage, Robert
Escobar, Luis E.
A database of global coastal conditions
title A database of global coastal conditions
title_full A database of global coastal conditions
title_fullStr A database of global coastal conditions
title_full_unstemmed A database of global coastal conditions
title_short A database of global coastal conditions
title_sort database of global coastal conditions
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8626420/
https://www.ncbi.nlm.nih.gov/pubmed/34836949
http://dx.doi.org/10.1038/s41597-021-01081-9
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