{"id":"https://openalex.org/W4395009994","doi":"https://doi.org/10.3390/rs16081466","title":"A Metadata-Enhanced Deep Learning Method for Sea Surface Height and Mesoscale Eddy Prediction","display_name":"A Metadata-Enhanced Deep Learning Method for Sea Surface Height and Mesoscale Eddy Prediction","publication_year":2024,"publication_date":"2024-04-20","ids":{"openalex":"https://openalex.org/W4395009994","doi":"https://doi.org/10.3390/rs16081466"},"language":"en","primary_location":{"id":"doi:10.3390/rs16081466","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16081466","pdf_url":"https://www.mdpi.com/2072-4292/16/8/1466/pdf?version=1713620859","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/16/8/1466/pdf?version=1713620859","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108881113","display_name":"Rongjie Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongjie Zhu","raw_affiliation_strings":["School of Teacher Education, Nanjing University of Information Science and Technology, Nanjing 211800, China"],"affiliations":[{"raw_affiliation_string":"School of Teacher Education, Nanjing University of Information Science and Technology, Nanjing 211800, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101592002","display_name":"Biao Song","orcid":"https://orcid.org/0000-0002-0423-7369"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Biao Song","raw_affiliation_strings":["School of Software, Nanjing University of Information Science and Technology, Nanjing 211800, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Nanjing University of Information Science and Technology, Nanjing 211800, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014898118","display_name":"Zhongfeng Qiu","orcid":"https://orcid.org/0000-0003-1167-3991"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongfeng Qiu","raw_affiliation_strings":["School of Marine Science, Nanjing University of Information Science and Technology, Nanjing 211800, China"],"affiliations":[{"raw_affiliation_string":"School of Marine Science, Nanjing University of Information Science and Technology, Nanjing 211800, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035919430","display_name":"Yuan Tian","orcid":"https://orcid.org/0000-0002-2307-8201"},"institutions":[{"id":"https://openalex.org/I2799736854","display_name":"Nanjing Institute of Technology","ror":"https://ror.org/00n6txq60","country_code":"CN","type":"education","lineage":["https://openalex.org/I2799736854"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Tian","raw_affiliation_strings":["Nanjing Institute of Technology, Nanjing 210094, China"],"affiliations":[{"raw_affiliation_string":"Nanjing Institute of Technology, Nanjing 210094, China","institution_ids":["https://openalex.org/I2799736854"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101592002"],"corresponding_institution_ids":["https://openalex.org/I200845125"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":4.1654,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.94010374,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"16","issue":"8","first_page":"1466","last_page":"1466"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10255","display_name":"Oceanographic and Atmospheric Processes","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10255","display_name":"Oceanographic and Atmospheric Processes","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11061","display_name":"Ocean Waves and Remote Sensing","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11483","display_name":"Tropical and Extratropical Cyclones Research","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mesoscale-meteorology","display_name":"Mesoscale meteorology","score":0.8928350210189819},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.761493444442749},{"id":"https://openalex.org/keywords/argo","display_name":"Argo","score":0.6539783477783203},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5005862712860107},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42895346879959106},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.42384785413742065},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3858333230018616},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3427107334136963},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.34246760606765747},{"id":"https://openalex.org/keywords/climatology","display_name":"Climatology","score":0.23643168807029724},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07453793287277222}],"concepts":[{"id":"https://openalex.org/C40382383","wikidata":"https://www.wikidata.org/wiki/Q2399824","display_name":"Mesoscale meteorology","level":2,"score":0.8928350210189819},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.761493444442749},{"id":"https://openalex.org/C51614570","wikidata":"https://www.wikidata.org/wiki/Q647931","display_name":"Argo","level":2,"score":0.6539783477783203},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5005862712860107},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42895346879959106},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.42384785413742065},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3858333230018616},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3427107334136963},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.34246760606765747},{"id":"https://openalex.org/C49204034","wikidata":"https://www.wikidata.org/wiki/Q52139","display_name":"Climatology","level":1,"score":0.23643168807029724},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07453793287277222},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs16081466","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16081466","pdf_url":"https://www.mdpi.com/2072-4292/16/8/1466/pdf?version=1713620859","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:87e5903993954cb097b30c35635905af","is_oa":true,"landing_page_url":"https://doaj.org/article/87e5903993954cb097b30c35635905af","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 16, Iss 8, p 1466 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs16081466","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16081466","pdf_url":"https://www.mdpi.com/2072-4292/16/8/1466/pdf?version=1713620859","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/14","score":0.5600000023841858,"display_name":"Life below water"}],"awards":[{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4020255992","display_name":null,"funder_award_id":"Project","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4027109255","display_name":null,"funder_award_id":"41976165","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4395009994.pdf"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W1485009520","https://openalex.org/W1574272897","https://openalex.org/W1974048245","https://openalex.org/W1994184728","https://openalex.org/W2011981241","https://openalex.org/W2012984343","https://openalex.org/W2054982169","https://openalex.org/W2064030455","https://openalex.org/W2071998560","https://openalex.org/W2085795536","https://openalex.org/W2099753271","https://openalex.org/W2122936119","https://openalex.org/W2581018225","https://openalex.org/W2781047404","https://openalex.org/W2914223643","https://openalex.org/W2930664421","https://openalex.org/W2937363749","https://openalex.org/W2940598365","https://openalex.org/W2956255334","https://openalex.org/W2962834855","https://openalex.org/W2963973018","https://openalex.org/W3083771119","https://openalex.org/W3111543595","https://openalex.org/W3128630349","https://openalex.org/W3173661693","https://openalex.org/W3173865166","https://openalex.org/W4200246868","https://openalex.org/W4298988771","https://openalex.org/W4311191406","https://openalex.org/W4312443924","https://openalex.org/W4385346076","https://openalex.org/W6757817989","https://openalex.org/W6797019691"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2387843509","https://openalex.org/W327400388","https://openalex.org/W289559479","https://openalex.org/W139153353","https://openalex.org/W787775643","https://openalex.org/W4328021821","https://openalex.org/W2046716484","https://openalex.org/W2378372156"],"abstract_inverted_index":{"Predicting":[0],"the":[1,5,14,57,70,73,99,107,125,145,149],"mesoscale":[2,30,117,133],"eddies":[3,134],"in":[4,29,95,135],"ocean":[6,15],"is":[7,25,153],"crucial":[8],"for":[9,35,110,148,156,163],"advancing":[10],"our":[11,102,104],"understanding":[12],"of":[13,72,101],"and":[16,60,160],"climate":[17],"systems.":[18],"Establishing":[19],"spatio-temporal":[20,58],"correlation":[21,59],"among":[22],"input":[23,92],"data":[24,66,130],"a":[26,45,51,77,116,157,164],"significant":[27],"challenge":[28],"eddy":[31,118,150],"prediction":[32,53,146,159],"tasks,":[33],"especially":[34],"deep":[36,46],"learning":[37,47],"techniques.":[38],"In":[39],"this":[40],"paper,":[41],"we":[42,75],"first":[43],"present":[44],"solution":[48,139],"based":[49],"on":[50],"video":[52],"model":[54,105],"to":[55,86,124,131],"capture":[56],"predict":[61],"future":[62],"sea":[63,112,127],"surface":[64,128],"height":[65,129],"accurately.":[67],"To":[68,98],"enhance":[69],"performance":[71],"model,":[74],"introduced":[76],"novel":[78],"metadata":[79,90],"embedding":[80],"module":[81],"that":[82,144],"utilizes":[83],"neural":[84],"networks":[85],"fuse":[87],"remote":[88],"sensing":[89],"with":[91],"data,":[93],"resulting":[94],"increased":[96],"accuracy.":[97],"best":[100],"knowledge,":[103],"outperforms":[106],"state-of-the-art":[108],"method":[109],"predicting":[111],"level":[113],"anomalies.":[114],"Consequently,":[115],"detection":[119],"algorithm":[120],"will":[121],"be":[122],"applied":[123],"predicted":[126],"generate":[132],"future.":[136],"The":[137],"proposed":[138],"achieves":[140],"competitive":[141],"results,":[142],"indicating":[143],"error":[147],"center":[151],"position":[152],"5.6":[154],"km":[155,162],"3-day":[158],"13.6":[161],"7-day":[165],"prediction.":[166]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2}],"updated_date":"2026-04-20T07:46:08.049788","created_date":"2025-10-10T00:00:00"}