{"id":"https://openalex.org/W1982017204","doi":"https://doi.org/10.1080/014311699212515","title":"The use of Neural Networks for the estimation of oceanic constituents based on the MERIS instrument","display_name":"The use of Neural Networks for the estimation of oceanic constituents based on the MERIS instrument","publication_year":1999,"publication_date":"1999-01-01","ids":{"openalex":"https://openalex.org/W1982017204","doi":"https://doi.org/10.1080/014311699212515","mag":"1982017204"},"language":"en","primary_location":{"id":"doi:10.1080/014311699212515","doi":"https://doi.org/10.1080/014311699212515","is_oa":false,"landing_page_url":"https://doi.org/10.1080/014311699212515","pdf_url":null,"source":{"id":"https://openalex.org/S117411352","display_name":"International Journal of Remote Sensing","issn_l":"0143-1161","issn":["0143-1161","1366-5901"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","dongbi-d","jufo-1","norway-2","poland-70","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Remote Sensing","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010141472","display_name":"Daniel J. Buckton","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Daniel Buckton","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023383542","display_name":"Eon O'Mongain","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eon O'Mongain","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5068043644","display_name":"S. Danaher","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sean Danaher","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.6251,"has_fulltext":false,"cited_by_count":57,"citation_normalized_percentile":{"value":0.78688047,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":98},"biblio":{"volume":"20","issue":"9","first_page":"1841","last_page":"1851"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10032","display_name":"Marine Plankton and Biogeochemistry","score":0.5210000276565552,"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/T10032","display_name":"Marine Plankton and Biogeochemistry","score":0.5210000276565552,"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/T10320","display_name":"Neural Networks and Applications","score":0.16030000150203705,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.10279999673366547,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":0.9480000138282776},{"id":"https://openalex.org/keywords/meris","display_name":"MERIS","score":0.9240000247955322},{"id":"https://openalex.org/keywords/ocean-color-remote-sensing","display_name":"ocean color remote sensing","score":0.8820000290870667},{"id":"https://openalex.org/keywords/chlorophyll-a","display_name":"chlorophyll a","score":0.7059999704360962},{"id":"https://openalex.org/keywords/suspended-particulate-matter","display_name":"suspended particulate matter","score":0.8730000257492065},{"id":"https://openalex.org/keywords/dissolved-organic-matter","display_name":"dissolved organic matter","score":0.9980000257492065},{"id":"https://openalex.org/keywords/case-2-waters","display_name":"Case 2 waters","score":0.8619999885559082},{"id":"https://openalex.org/keywords/band-ratio-algorithms","display_name":"band ratio algorithm","score":0.7689999938011169},{"id":"https://openalex.org/keywords/atmospheric-visibility","display_name":"atmospheric visibility","score":0.777999997138977}],"concepts":[{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6297305822372437},{"id":"https://openalex.org/C135009316","wikidata":"https://www.wikidata.org/wiki/Q986090","display_name":"Colored dissolved organic matter","level":4,"score":0.6292621493339539},{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.6082084774971008},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5873346328735352},{"id":"https://openalex.org/C183852935","wikidata":"https://www.wikidata.org/wiki/Q6002848","display_name":"Imaging spectrometer","level":3,"score":0.5608547329902649},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.5314855575561523},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5195974707603455},{"id":"https://openalex.org/C33390570","wikidata":"https://www.wikidata.org/wiki/Q188463","display_name":"Spectrometer","level":2,"score":0.42874300479888916},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.31326568126678467},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22713884711265564},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.2125244438648224},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.12066680192947388},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.09283798933029175},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C142796444","wikidata":"https://www.wikidata.org/wiki/Q181394","display_name":"Nutrient","level":2,"score":0.0},{"id":"https://openalex.org/C2780892065","wikidata":"https://www.wikidata.org/wiki/Q184755","display_name":"Phytoplankton","level":3,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/014311699212515","doi":"https://doi.org/10.1080/014311699212515","is_oa":false,"landing_page_url":"https://doi.org/10.1080/014311699212515","pdf_url":null,"source":{"id":"https://openalex.org/S117411352","display_name":"International Journal of Remote Sensing","issn_l":"0143-1161","issn":["0143-1161","1366-5901"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","dongbi-d","jufo-1","norway-2","poland-70","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1616330624","https://openalex.org/W1847045976","https://openalex.org/W4321085507","https://openalex.org/W2084444320","https://openalex.org/W2142140093","https://openalex.org/W2048985333","https://openalex.org/W2024643119","https://openalex.org/W2165836576","https://openalex.org/W2078749539","https://openalex.org/W6989933275"],"abstract_inverted_index":{"Artificial":[0],"Neural":[1],"Networks":[2],"(NNs)":[3],"are":[4],"used":[5,57],"in":[6],"estimations":[7],"of":[8,33,70,78,104],"oceanic":[9,34,60],"constituents":[10,61],"from":[11],"simulated":[12,64],"data":[13,65],"for":[14,23],"the":[15,31,68,102],"Mechron":[16],"Resolution":[17],"Imaging":[18],"Spectrometer":[19],"(MERIS)":[20],"instrument":[21],"system":[22],"Case":[24],"II":[25],"water":[26],"applications.":[27],"The":[28,76],"simulation":[29],"includes":[30],"effects":[32,69],"substances":[35],"such":[36,93,110],"as":[37,94,111],"algal":[38],"related":[39],"chlorophyll,":[40],"non-chlorophyllous":[41],"suspended":[42],"matter":[43],"and":[44,73,114],"DOM":[45],"(dissolved":[46],"organic":[47],"matter).":[48],"It":[49],"is":[50,80],"shown":[51],"here":[52],"that":[53,81],"NNs":[54,79],"can":[55],"be":[56],"to":[58],"estimate":[59],"based":[62],"on":[63],"which":[66],"include":[67],"realistic":[71],"noise":[72],"variability":[74],"models.":[75],"advantage":[77],"they":[82,99],"not":[83],"only":[84],"achieve":[85],"higher":[86],"retrieval":[87],"accuracy":[88],"than":[89],"more":[90],"traditional":[91],"techniques":[92],"band":[95],"ratio":[96],"algorithms,":[97],"but":[98],"also":[100],"allow":[101],"inclusion":[103],"usually":[105],"superfluous":[106],"or":[107],"unused":[108],"information,":[109],"geometric":[112],"parameters":[113],"atmospheric":[115],"visibility.":[116]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":5},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":3}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}