{"id":"https://openalex.org/W7128535240","doi":"https://doi.org/10.48550/arxiv.2602.08511","title":"Estimation of Fish Catch Using Sentinel-2, 3 and XGBoost-Kernel-Based Kernel Ridge Regression","display_name":"Estimation of Fish Catch Using Sentinel-2, 3 and XGBoost-Kernel-Based Kernel Ridge Regression","publication_year":2026,"publication_date":"2026-02-09","ids":{"openalex":"https://openalex.org/W7128535240","doi":"https://doi.org/10.48550/arxiv.2602.08511"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.08511","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.08511","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2602.08511","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125507133","display_name":"Kanu Mohammed","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohammed, Kanu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125486131","display_name":"Vaishnavi Joshi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Joshi, Vaishnavi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125506652","display_name":"Pranjali Diliprao Patil","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Patil, Pranjali Diliprao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043095341","display_name":"Sandipan Mondal","orcid":"https://orcid.org/0000-0002-9909-1285"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mondal, Sandipan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125556621","display_name":"Ming-An Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Ming-An","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5125549476","display_name":"Subhadip Dey","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dey, Subhadip","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":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10230","display_name":"Marine and fisheries research","score":0.4397999942302704,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10230","display_name":"Marine and fisheries research","score":0.4397999942302704,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12697","display_name":"Water Quality Monitoring Technologies","score":0.164900004863739,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.06129999831318855,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.5238000154495239},{"id":"https://openalex.org/keywords/fish-actinopterygii","display_name":"Fish <Actinopterygii>","score":0.46860000491142273},{"id":"https://openalex.org/keywords/ridge","display_name":"Ridge","score":0.4684000015258789},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.46639999747276306},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.450300008058548},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.36169999837875366},{"id":"https://openalex.org/keywords/abundance-estimation","display_name":"Abundance estimation","score":0.36059999465942383},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.358599990606308},{"id":"https://openalex.org/keywords/fish-stock","display_name":"Fish stock","score":0.35179999470710754}],"concepts":[{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.5238000154495239},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.47749999165534973},{"id":"https://openalex.org/C2909208804","wikidata":"https://www.wikidata.org/wiki/Q127282","display_name":"Fish <Actinopterygii>","level":2,"score":0.46860000491142273},{"id":"https://openalex.org/C32277403","wikidata":"https://www.wikidata.org/wiki/Q740445","display_name":"Ridge","level":2,"score":0.4684000015258789},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.46639999747276306},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.450300008058548},{"id":"https://openalex.org/C505870484","wikidata":"https://www.wikidata.org/wiki/Q180538","display_name":"Fishery","level":1,"score":0.41690000891685486},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.36169999837875366},{"id":"https://openalex.org/C2778514742","wikidata":"https://www.wikidata.org/wiki/Q16245026","display_name":"Abundance estimation","level":3,"score":0.36059999465942383},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.358599990606308},{"id":"https://openalex.org/C58479451","wikidata":"https://www.wikidata.org/wiki/Q16782389","display_name":"Fish stock","level":3,"score":0.35179999470710754},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.35120001435279846},{"id":"https://openalex.org/C134097258","wikidata":"https://www.wikidata.org/wiki/Q1507383","display_name":"Sea surface temperature","level":2,"score":0.3395000100135803},{"id":"https://openalex.org/C110872660","wikidata":"https://www.wikidata.org/wiki/Q37813","display_name":"Ecosystem","level":2,"score":0.33809998631477356},{"id":"https://openalex.org/C2779042980","wikidata":"https://www.wikidata.org/wiki/Q5333878","display_name":"Ecosystem-based management","level":3,"score":0.3353999853134155},{"id":"https://openalex.org/C202041845","wikidata":"https://www.wikidata.org/wiki/Q5454893","display_name":"Fisheries management","level":3,"score":0.32829999923706055},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.3208000063896179},{"id":"https://openalex.org/C549605437","wikidata":"https://www.wikidata.org/wiki/Q1229911","display_name":"Food security","level":3,"score":0.32010000944137573},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3165000081062317},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.314300000667572},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.31349998712539673},{"id":"https://openalex.org/C200695384","wikidata":"https://www.wikidata.org/wiki/Q1739319","display_name":"Kernel regression","level":3,"score":0.30970001220703125},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.3095000088214874},{"id":"https://openalex.org/C2776841996","wikidata":"https://www.wikidata.org/wiki/Q1517781","display_name":"Shrimp","level":2,"score":0.30649998784065247},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3000999987125397},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.2985999882221222},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.2939000129699707},{"id":"https://openalex.org/C2776939893","wikidata":"https://www.wikidata.org/wiki/Q7076134","display_name":"Ocean color","level":3,"score":0.29339998960494995},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.28380000591278076},{"id":"https://openalex.org/C2780748813","wikidata":"https://www.wikidata.org/wiki/Q7649683","display_name":"Sustainable management","level":3,"score":0.2720000147819519},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.2687000036239624},{"id":"https://openalex.org/C49204034","wikidata":"https://www.wikidata.org/wiki/Q52139","display_name":"Climatology","level":1,"score":0.26409998536109924},{"id":"https://openalex.org/C132651083","wikidata":"https://www.wikidata.org/wiki/Q7942","display_name":"Climate change","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C158709400","wikidata":"https://www.wikidata.org/wiki/Q3578586","display_name":"Spatial ecology","level":2,"score":0.25920000672340393},{"id":"https://openalex.org/C100970517","wikidata":"https://www.wikidata.org/wiki/Q52107","display_name":"Physical geography","level":1,"score":0.2540000081062317}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.08511","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.08511","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2602.08511","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.08511","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Oceanographic":[0],"factors,":[1],"such":[2],"as":[3],"sea":[4],"surface":[5],"temperature":[6],"and":[7,37,66,109,122],"upper-ocean":[8],"dynamics,":[9],"have":[10],"a":[11],"significant":[12],"impact":[13],"on":[14],"fish":[15,42],"distribution.":[16],"Maintaining":[17],"fisheries":[18,112],"that":[19],"contribute":[20],"to":[21,40,56,77],"global":[22],"food":[23],"security":[24],"requires":[25],"quantifying":[26],"these":[27],"connections.":[28,81],"This":[29],"study":[30],"uses":[31],"multispectral":[32],"images":[33],"from":[34],"Sentinel-2":[35,83],"MSI":[36,84],"Sentinel-3":[38,93],"OLCI":[39,94],"estimate":[41],"catch":[43],"using":[44],"an":[45],"Extreme":[46],"Gradient":[47],"Boosting":[48],"(XGBoost)-kernelized":[49],"Kernel":[50],"Ridge":[51],"Regression":[52],"(KRR)":[53],"technique.":[54],"According":[55],"model":[57],"evaluation,":[58],"the":[59,63,67,114],"XGBoost-KRR":[60],"framework":[61],"achieves":[62],"strongest":[64],"correlation":[65],"lowest":[68],"prediction":[69],"error":[70],"across":[71],"both":[72],"sensors,":[73],"suggesting":[74],"improved":[75],"capacity":[76],"capture":[78],"nonlinear":[79],"ocean-fish":[80],"While":[82],"resolves":[85],"finer-scale":[86],"spatial":[87,102],"variability,":[88],"emphasizing":[89],"localized":[90],"ecological":[91],"interactions,":[92],"displays":[95],"smoother":[96],"spectral":[97],"responses":[98],"associated":[99],"with":[100],"poorer":[101],"resolution.":[103],"By":[104],"supporting":[105],"sustainable":[106],"ecosystem":[107],"management":[108],"strengthening":[110],"satellite-based":[111],"assessment,":[113],"proposed":[115],"approach":[116],"advances":[117],"SDGs":[118],"2":[119],"(Zero":[120],"Hunger)":[121],"14":[123],"(Life":[124],"Below":[125],"Water).":[126]},"counts_by_year":[],"updated_date":"2026-08-16T07:02:28.622633","created_date":"2026-02-11T00:00:00"}