{"id":"https://openalex.org/W2157655302","doi":"https://doi.org/10.1109/igarss.2004.1368700","title":"Estimation of biophysical parameters from optical remote-sensing images with high-order residues","display_name":"Estimation of biophysical parameters from optical remote-sensing images with high-order residues","publication_year":2004,"publication_date":"2004-12-23","ids":{"openalex":"https://openalex.org/W2157655302","doi":"https://doi.org/10.1109/igarss.2004.1368700","mag":"2157655302"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2004.1368700","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2004.1368700","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE International IEEE International IEEE International Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004","raw_type":"proceedings-article"},"type":"article","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/A5108096196","display_name":"F. Melgani","orcid":null},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"F. Melgani","raw_affiliation_strings":["Department of Information and Communication Technologies, University of Trento, Trento, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communication Technologies, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006095323","display_name":"Lorenzo Bruzzone","orcid":"https://orcid.org/0000-0002-6036-459X"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"L. Bruzzone","raw_affiliation_strings":["Department of Information and Communication Technologies, University of Trento, Trento, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communication Technologies, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5108096196"],"corresponding_institution_ids":["https://openalex.org/I193223587"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.15750788,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"1479","last_page":"1482"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2311","display_name":"Industrial and Manufacturing Engineering"},"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/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2311","display_name":"Industrial and Manufacturing Engineering"},"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":0.9908999800682068,"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/T10032","display_name":"Marine and coastal ecosystems","score":0.9898999929428101,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.8570237159729004},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6576582193374634},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6456665992736816},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.591820240020752},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5723460912704468},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4891350567340851},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47611624002456665},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.46536850929260254},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46082791686058044},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.43416231870651245},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40002357959747314},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38917648792266846},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34362494945526123},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2859269678592682},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2120347023010254},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1452946960926056},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08311763405799866}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8570237159729004},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6576582193374634},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6456665992736816},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.591820240020752},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5723460912704468},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4891350567340851},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47611624002456665},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.46536850929260254},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46082791686058044},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.43416231870651245},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40002357959747314},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38917648792266846},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34362494945526123},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2859269678592682},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2120347023010254},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1452946960926056},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08311763405799866},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss.2004.1368700","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2004.1368700","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE International IEEE International IEEE International Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004","raw_type":"proceedings-article"},{"id":"pmh:oai:iris.unitn.it:11572/78246","is_oa":false,"landing_page_url":"http://hdl.handle.net/11572/78246","pdf_url":null,"source":{"id":"https://openalex.org/S4306401913","display_name":"Institutional Research Information System (Universit\u00e0 degli Studi di Trento)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193223587","host_organization_name":"University of Trento","host_organization_lineage":["https://openalex.org/I193223587"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Clean water and sanitation","score":0.8500000238418579,"id":"https://metadata.un.org/sdg/6"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1547520132","https://openalex.org/W2007101051","https://openalex.org/W2019653893","https://openalex.org/W2082802513","https://openalex.org/W2156418736"],"related_works":["https://openalex.org/W1574414179","https://openalex.org/W4362597605","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4297676672","https://openalex.org/W4281702477","https://openalex.org/W4378510483","https://openalex.org/W4376166922","https://openalex.org/W2490526372","https://openalex.org/W4221142204"],"abstract_inverted_index":{"Robust":[0],"estimation":[1,95,145],"of":[2,51,67,84,96,133,135],"biophysical":[3,49],"parameters":[4,88],"in":[5,25],"large":[6],"geographical":[7],"areas":[8],"from":[9,65],"remote":[10,44],"sensing":[11,45],"images":[12],"represents":[13],"an":[14,35],"important":[15],"methodological":[16],"issue.":[17],"A":[18],"possible":[19],"approach":[20,61],"to":[21,38,58,70,81],"this":[22,54,60,149],"problem":[23,83],"consists":[24],"modeling":[26],"and":[27,47,103,113],"correcting":[28],"the":[29,40,43,48,73,82,94,97,122,131,144],"systematic":[30],"errors":[31],"(residues)":[32],"generated":[33],"by":[34,62],"estimator":[36],"trained":[37],"approximate":[39],"relationship":[41],"between":[42],"measurements":[46],"parameter":[50],"interest.":[52],"In":[53],"paper,":[55],"we":[56],"propose":[57],"extend":[59],"capturing":[63],"information":[64],"residues":[66,134],"higher":[68],"order":[69,136],"refine":[71],"further":[72],"approximated":[74],"model.":[75],"The":[76,125],"proposed":[77],"technique":[78],"was":[79],"applied":[80],"estimating":[85],"water":[86],"quality":[87],"with":[89],"a":[90],"particular":[91],"focus":[92],"on":[93,108],"chlorophyll":[98],"concentration.":[99],"Two":[100],"data":[101],"sets":[102],"two":[104,141],"regression":[105],"methods":[106],"(based":[107],"Support":[109],"vector":[110],"Machines":[111],"(SVM)":[112],"Multilayer":[114],"Perceptron":[115],"(MLP)":[116],"neural":[117],"networks)":[118],"were":[119],"considered":[120],"for":[121],"experimental":[123],"phase.":[124],"obtained":[126],"results":[127],"point":[128],"out":[129],"that":[130],"exploitation":[132],"smaller":[137],"or":[138],"equal":[139],"than":[140],"can":[142],"improve":[143],"accuracy":[146],"while,":[147],"above":[148],"order,":[150],"overfitting":[151],"problems":[152],"may":[153],"appear.":[154]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
