Loading…
Validation of NASA Sea Surface Temperature Satellite Products Using Saildrone Data
Sea Surface Temperature (SST) is at the core of many processes in the oceans. Various remote sensing platforms have been used to obtain SST products of different scales, but their validation remains a topic of ongoing research. One promising platform is an uncrewed surface vehicle called Saildrone....
Saved in:
Published in: | Remote sensing (Basel, Switzerland) Switzerland), 2023-04, Vol.15 (9), p.2277 |
---|---|
Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c400t-e3bb22263e15a0e7f099441de8fedbfc43a5de18c0aa61b4f7b5cf5859285cf93 |
---|---|
cites | cdi_FETCH-LOGICAL-c400t-e3bb22263e15a0e7f099441de8fedbfc43a5de18c0aa61b4f7b5cf5859285cf93 |
container_end_page | |
container_issue | 9 |
container_start_page | 2277 |
container_title | Remote sensing (Basel, Switzerland) |
container_volume | 15 |
creator | Koutantou, Kalliopi Brunner, Philip Vazquez-Cuervo, Jorge |
description | Sea Surface Temperature (SST) is at the core of many processes in the oceans. Various remote sensing platforms have been used to obtain SST products of different scales, but their validation remains a topic of ongoing research. One promising platform is an uncrewed surface vehicle called Saildrone. We use the data from eight Saildrone deployments of the USA West Coast 2019 campaign to validate MODIS level-2 and Multi-scale Ultra-high Resolution (MUR) level-4 satellite SST products at 1 km spatial resolution and to assess the robustness of the quality levels of MODIS level-2 products over the California Coast. Pixel-based SST comparisons between Saildrone and the satellite products were performed, as well as thermal gradient comparisons computed both at the pixel-base level and using kriging interpolation. The results generally showed better accuracies for the MUR products. The characterization of the MODIS quality level proved to be valid in areas covered by bad-quality MODIS pixels but less valid in areas covered by lower-quality pixels. The latter implies possible errors in the MODIS quality level characterization and MUR interpolation processes. We have demonstrated the ability of the Saildrones to accurately validate near-shore satellite SST products and provide important information for the quality assessment of satellite products. |
doi_str_mv | 10.3390/rs15092277 |
format | article |
fullrecord | <record><control><sourceid>gale_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_4324658fc0234817b3ca808ff2813bfc</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A750634865</galeid><doaj_id>oai_doaj_org_article_4324658fc0234817b3ca808ff2813bfc</doaj_id><sourcerecordid>A750634865</sourcerecordid><originalsourceid>FETCH-LOGICAL-c400t-e3bb22263e15a0e7f099441de8fedbfc43a5de18c0aa61b4f7b5cf5859285cf93</originalsourceid><addsrcrecordid>eNpNUU1rHDEMHUoDCcle8gsMvRU29eeMfVzSNgmENGR3czUaj7x4mR1vbc-h_z5Ot7SVDhLSe08SapprRm-EMPRLykxRw3nXfWguOO34UnLDP_6XnzeLnPe0mhDMUHnRvLzCGAYoIU4kevK0Wq_IGoGs5-TBIdng4YgJypyQrKHgOIaC5DnFYXYlk20O0642wjikOCH5CgWumjMPY8bFn3jZbL9_29zeLx9_3D3crh6XTlJalij6nnPeCmQKKHaeGiMlG1B7HHrvpAA1INOOArSsl77rlfNKK8N1TYy4bB5OukOEvT2mcID0y0YI9nchpp2FVIIb0UrBZau0d5QLqVnXCweaau-5ZqLOqlqfTlrHFH_OmIvdxzlNdX1bIbyrfMMr6uaE2kEVDZOPJYGrPuAhuHq_D7W-6hRt65hWVcLnE8GlmHNC_3dNRu37z-y_n4k3L76HPQ</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2812732492</pqid></control><display><type>article</type><title>Validation of NASA Sea Surface Temperature Satellite Products Using Saildrone Data</title><source>Publicly Available Content (ProQuest)</source><creator>Koutantou, Kalliopi ; Brunner, Philip ; Vazquez-Cuervo, Jorge</creator><creatorcontrib>Koutantou, Kalliopi ; Brunner, Philip ; Vazquez-Cuervo, Jorge</creatorcontrib><description>Sea Surface Temperature (SST) is at the core of many processes in the oceans. Various remote sensing platforms have been used to obtain SST products of different scales, but their validation remains a topic of ongoing research. One promising platform is an uncrewed surface vehicle called Saildrone. We use the data from eight Saildrone deployments of the USA West Coast 2019 campaign to validate MODIS level-2 and Multi-scale Ultra-high Resolution (MUR) level-4 satellite SST products at 1 km spatial resolution and to assess the robustness of the quality levels of MODIS level-2 products over the California Coast. Pixel-based SST comparisons between Saildrone and the satellite products were performed, as well as thermal gradient comparisons computed both at the pixel-base level and using kriging interpolation. The results generally showed better accuracies for the MUR products. The characterization of the MODIS quality level proved to be valid in areas covered by bad-quality MODIS pixels but less valid in areas covered by lower-quality pixels. The latter implies possible errors in the MODIS quality level characterization and MUR interpolation processes. We have demonstrated the ability of the Saildrones to accurately validate near-shore satellite SST products and provide important information for the quality assessment of satellite products.</description><identifier>ISSN: 2072-4292</identifier><identifier>EISSN: 2072-4292</identifier><identifier>DOI: 10.3390/rs15092277</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>California Coast ; Climate change ; Coasts ; Kriging interpolation ; Meteorological satellites ; MODIS ; MUR ; Oceans ; Pixels ; Precipitation ; Quality assessment ; Quality control ; quality levels ; Radiation ; Radiometers ; Remote sensing ; Saildrone ; Satellites ; Sea surface temperature ; Sensors ; Skin ; Spatial discrimination ; Spatial resolution ; SST ; Surface vehicles ; Temperature ; Temperature gradients</subject><ispartof>Remote sensing (Basel, Switzerland), 2023-04, Vol.15 (9), p.2277</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c400t-e3bb22263e15a0e7f099441de8fedbfc43a5de18c0aa61b4f7b5cf5859285cf93</citedby><cites>FETCH-LOGICAL-c400t-e3bb22263e15a0e7f099441de8fedbfc43a5de18c0aa61b4f7b5cf5859285cf93</cites><orcidid>0000-0002-2007-1725 ; 0000-0001-6304-6274</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2812732492/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2812732492?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,44590,75126</link.rule.ids></links><search><creatorcontrib>Koutantou, Kalliopi</creatorcontrib><creatorcontrib>Brunner, Philip</creatorcontrib><creatorcontrib>Vazquez-Cuervo, Jorge</creatorcontrib><title>Validation of NASA Sea Surface Temperature Satellite Products Using Saildrone Data</title><title>Remote sensing (Basel, Switzerland)</title><description>Sea Surface Temperature (SST) is at the core of many processes in the oceans. Various remote sensing platforms have been used to obtain SST products of different scales, but their validation remains a topic of ongoing research. One promising platform is an uncrewed surface vehicle called Saildrone. We use the data from eight Saildrone deployments of the USA West Coast 2019 campaign to validate MODIS level-2 and Multi-scale Ultra-high Resolution (MUR) level-4 satellite SST products at 1 km spatial resolution and to assess the robustness of the quality levels of MODIS level-2 products over the California Coast. Pixel-based SST comparisons between Saildrone and the satellite products were performed, as well as thermal gradient comparisons computed both at the pixel-base level and using kriging interpolation. The results generally showed better accuracies for the MUR products. The characterization of the MODIS quality level proved to be valid in areas covered by bad-quality MODIS pixels but less valid in areas covered by lower-quality pixels. The latter implies possible errors in the MODIS quality level characterization and MUR interpolation processes. We have demonstrated the ability of the Saildrones to accurately validate near-shore satellite SST products and provide important information for the quality assessment of satellite products.</description><subject>California Coast</subject><subject>Climate change</subject><subject>Coasts</subject><subject>Kriging interpolation</subject><subject>Meteorological satellites</subject><subject>MODIS</subject><subject>MUR</subject><subject>Oceans</subject><subject>Pixels</subject><subject>Precipitation</subject><subject>Quality assessment</subject><subject>Quality control</subject><subject>quality levels</subject><subject>Radiation</subject><subject>Radiometers</subject><subject>Remote sensing</subject><subject>Saildrone</subject><subject>Satellites</subject><subject>Sea surface temperature</subject><subject>Sensors</subject><subject>Skin</subject><subject>Spatial discrimination</subject><subject>Spatial resolution</subject><subject>SST</subject><subject>Surface vehicles</subject><subject>Temperature</subject><subject>Temperature gradients</subject><issn>2072-4292</issn><issn>2072-4292</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpNUU1rHDEMHUoDCcle8gsMvRU29eeMfVzSNgmENGR3czUaj7x4mR1vbc-h_z5Ot7SVDhLSe08SapprRm-EMPRLykxRw3nXfWguOO34UnLDP_6XnzeLnPe0mhDMUHnRvLzCGAYoIU4kevK0Wq_IGoGs5-TBIdng4YgJypyQrKHgOIaC5DnFYXYlk20O0642wjikOCH5CgWumjMPY8bFn3jZbL9_29zeLx9_3D3crh6XTlJalij6nnPeCmQKKHaeGiMlG1B7HHrvpAA1INOOArSsl77rlfNKK8N1TYy4bB5OukOEvT2mcID0y0YI9nchpp2FVIIb0UrBZau0d5QLqVnXCweaau-5ZqLOqlqfTlrHFH_OmIvdxzlNdX1bIbyrfMMr6uaE2kEVDZOPJYGrPuAhuHq_D7W-6hRt65hWVcLnE8GlmHNC_3dNRu37z-y_n4k3L76HPQ</recordid><startdate>20230425</startdate><enddate>20230425</enddate><creator>Koutantou, Kalliopi</creator><creator>Brunner, Philip</creator><creator>Vazquez-Cuervo, Jorge</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7QR</scope><scope>7SC</scope><scope>7SE</scope><scope>7SN</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>JQ2</scope><scope>KR7</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PCBAR</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-2007-1725</orcidid><orcidid>https://orcid.org/0000-0001-6304-6274</orcidid></search><sort><creationdate>20230425</creationdate><title>Validation of NASA Sea Surface Temperature Satellite Products Using Saildrone Data</title><author>Koutantou, Kalliopi ; Brunner, Philip ; Vazquez-Cuervo, Jorge</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c400t-e3bb22263e15a0e7f099441de8fedbfc43a5de18c0aa61b4f7b5cf5859285cf93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>California Coast</topic><topic>Climate change</topic><topic>Coasts</topic><topic>Kriging interpolation</topic><topic>Meteorological satellites</topic><topic>MODIS</topic><topic>MUR</topic><topic>Oceans</topic><topic>Pixels</topic><topic>Precipitation</topic><topic>Quality assessment</topic><topic>Quality control</topic><topic>quality levels</topic><topic>Radiation</topic><topic>Radiometers</topic><topic>Remote sensing</topic><topic>Saildrone</topic><topic>Satellites</topic><topic>Sea surface temperature</topic><topic>Sensors</topic><topic>Skin</topic><topic>Spatial discrimination</topic><topic>Spatial resolution</topic><topic>SST</topic><topic>Surface vehicles</topic><topic>Temperature</topic><topic>Temperature gradients</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Koutantou, Kalliopi</creatorcontrib><creatorcontrib>Brunner, Philip</creatorcontrib><creatorcontrib>Vazquez-Cuervo, Jorge</creatorcontrib><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Ecology Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>SciTech Premium Collection</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Engineering Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>Publicly Available Content (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Directory of Open Access Journals</collection><jtitle>Remote sensing (Basel, Switzerland)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Koutantou, Kalliopi</au><au>Brunner, Philip</au><au>Vazquez-Cuervo, Jorge</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Validation of NASA Sea Surface Temperature Satellite Products Using Saildrone Data</atitle><jtitle>Remote sensing (Basel, Switzerland)</jtitle><date>2023-04-25</date><risdate>2023</risdate><volume>15</volume><issue>9</issue><spage>2277</spage><pages>2277-</pages><issn>2072-4292</issn><eissn>2072-4292</eissn><abstract>Sea Surface Temperature (SST) is at the core of many processes in the oceans. Various remote sensing platforms have been used to obtain SST products of different scales, but their validation remains a topic of ongoing research. One promising platform is an uncrewed surface vehicle called Saildrone. We use the data from eight Saildrone deployments of the USA West Coast 2019 campaign to validate MODIS level-2 and Multi-scale Ultra-high Resolution (MUR) level-4 satellite SST products at 1 km spatial resolution and to assess the robustness of the quality levels of MODIS level-2 products over the California Coast. Pixel-based SST comparisons between Saildrone and the satellite products were performed, as well as thermal gradient comparisons computed both at the pixel-base level and using kriging interpolation. The results generally showed better accuracies for the MUR products. The characterization of the MODIS quality level proved to be valid in areas covered by bad-quality MODIS pixels but less valid in areas covered by lower-quality pixels. The latter implies possible errors in the MODIS quality level characterization and MUR interpolation processes. We have demonstrated the ability of the Saildrones to accurately validate near-shore satellite SST products and provide important information for the quality assessment of satellite products.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/rs15092277</doi><orcidid>https://orcid.org/0000-0002-2007-1725</orcidid><orcidid>https://orcid.org/0000-0001-6304-6274</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2072-4292 |
ispartof | Remote sensing (Basel, Switzerland), 2023-04, Vol.15 (9), p.2277 |
issn | 2072-4292 2072-4292 |
language | eng |
recordid | cdi_doaj_primary_oai_doaj_org_article_4324658fc0234817b3ca808ff2813bfc |
source | Publicly Available Content (ProQuest) |
subjects | California Coast Climate change Coasts Kriging interpolation Meteorological satellites MODIS MUR Oceans Pixels Precipitation Quality assessment Quality control quality levels Radiation Radiometers Remote sensing Saildrone Satellites Sea surface temperature Sensors Skin Spatial discrimination Spatial resolution SST Surface vehicles Temperature Temperature gradients |
title | Validation of NASA Sea Surface Temperature Satellite Products Using Saildrone Data |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-24T00%3A43%3A08IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Validation%20of%20NASA%20Sea%20Surface%20Temperature%20Satellite%20Products%20Using%20Saildrone%20Data&rft.jtitle=Remote%20sensing%20(Basel,%20Switzerland)&rft.au=Koutantou,%20Kalliopi&rft.date=2023-04-25&rft.volume=15&rft.issue=9&rft.spage=2277&rft.pages=2277-&rft.issn=2072-4292&rft.eissn=2072-4292&rft_id=info:doi/10.3390/rs15092277&rft_dat=%3Cgale_doaj_%3EA750634865%3C/gale_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c400t-e3bb22263e15a0e7f099441de8fedbfc43a5de18c0aa61b4f7b5cf5859285cf93%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2812732492&rft_id=info:pmid/&rft_galeid=A750634865&rfr_iscdi=true |