{"id":"https://openalex.org/W2101936384","doi":"https://doi.org/10.1109/lgrs.2009.2037720","title":"A Data-Mining Technique for Aerosol Retrieval Across Multiple Accuracy Measures","display_name":"A Data-Mining Technique for Aerosol Retrieval Across Multiple Accuracy Measures","publication_year":2010,"publication_date":"2010-02-11","ids":{"openalex":"https://openalex.org/W2101936384","doi":"https://doi.org/10.1109/lgrs.2009.2037720","mag":"2101936384"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2009.2037720","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2009.2037720","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-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/A5085497926","display_name":"Vladan Radosavljevi\u0107","orcid":"https://orcid.org/0009-0006-9128-1101"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Vladan Radosavljevic","raw_affiliation_strings":["Information Science and Technology Center, Temple University, Philadelphia, PA, USA","[Information Science and Technology Center, Temple University, Philadelphia, PA, USA]"],"affiliations":[{"raw_affiliation_string":"Information Science and Technology Center, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]},{"raw_affiliation_string":"[Information Science and Technology Center, Temple University, Philadelphia, PA, USA]","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059847153","display_name":"Slobodan Vu\u010deti\u0107","orcid":"https://orcid.org/0000-0001-5884-6293"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Slobodan Vucetic","raw_affiliation_strings":["Information Science and Technology Center, Temple University, Philadelphia, PA, USA","[Information Science and Technology Center, Temple University, Philadelphia, PA, USA]"],"affiliations":[{"raw_affiliation_string":"Information Science and Technology Center, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]},{"raw_affiliation_string":"[Information Science and Technology Center, Temple University, Philadelphia, PA, USA]","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044038055","display_name":"Zoran Obradovi\u0107","orcid":"https://orcid.org/0000-0002-2051-0142"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zoran Obradovic","raw_affiliation_strings":["Information Science and Technology Center, Temple University, Philadelphia, PA, USA","[Information Science and Technology Center, Temple University, Philadelphia, PA, USA]"],"affiliations":[{"raw_affiliation_string":"Information Science and Technology Center, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]},{"raw_affiliation_string":"[Information Science and Technology Center, Temple University, Philadelphia, PA, USA]","institution_ids":["https://openalex.org/I84392919"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5085497926"],"corresponding_institution_ids":["https://openalex.org/I84392919"],"apc_list":null,"apc_paid":null,"fwci":2.0247,"has_fulltext":false,"cited_by_count":33,"citation_normalized_percentile":{"value":0.86455857,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"7","issue":"2","first_page":"411","last_page":"415"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10347","display_name":"Atmospheric aerosols and clouds","score":0.9998999834060669,"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/T10347","display_name":"Atmospheric aerosols and clouds","score":0.9998999834060669,"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/T10075","display_name":"Atmospheric chemistry and aerosols","score":0.9968000054359436,"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"}},{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/aeronet","display_name":"AERONET","score":0.8766016960144043},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6224117875099182},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5836648344993591},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5713948011398315},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4737609028816223},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.41937994956970215},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41754838824272156},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.4164135158061981},{"id":"https://openalex.org/keywords/aerosol","display_name":"Aerosol","score":0.3876127004623413},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35795801877975464},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19680452346801758},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19378921389579773},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.13880592584609985}],"concepts":[{"id":"https://openalex.org/C2777634575","wikidata":"https://www.wikidata.org/wiki/Q291476","display_name":"AERONET","level":3,"score":0.8766016960144043},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6224117875099182},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5836648344993591},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5713948011398315},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4737609028816223},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.41937994956970215},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41754838824272156},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.4164135158061981},{"id":"https://openalex.org/C2779345167","wikidata":"https://www.wikidata.org/wiki/Q104541","display_name":"Aerosol","level":2,"score":0.3876127004623413},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35795801877975464},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19680452346801758},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19378921389579773},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.13880592584609985},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lgrs.2009.2037720","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2009.2037720","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.221.3861","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.221.3861","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ist.temple.edu/%7Evucetic/documents/radosavljevic10grsl.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W1260295744","https://openalex.org/W2089433206","https://openalex.org/W2123162799","https://openalex.org/W2134631034"],"related_works":["https://openalex.org/W1988447094","https://openalex.org/W2418673772","https://openalex.org/W1996782635","https://openalex.org/W2014316009","https://openalex.org/W2145265567","https://openalex.org/W2750830902","https://openalex.org/W2086153848","https://openalex.org/W2592638685","https://openalex.org/W220012687","https://openalex.org/W2727061298"],"abstract_inverted_index":{"A":[0],"typical":[1],"approach":[2],"in":[3,23,181],"supervised":[4],"learning":[5],"is":[6,29],"to":[7,47,196,208],"select":[8],"an":[9],"accuracy":[10,35,52,73,110,240],"measure":[11],"and":[12,83,112,140,143,155,186,207,230],"train":[13],"a":[14,93,108],"predictor":[15,27],"that":[16,42,215,231],"maximizes":[17],"it.":[18],"This":[19],"can":[20,44],"be":[21,45],"insufficient":[22],"remote-sensing":[24],"applications":[25],"where":[26,96],"performance":[28,49],"often":[30],"evaluated":[31],"over":[32,50,178,238],"multiple":[33,51,72,102,239],"domain-specific":[34],"measures.":[36,53,241],"Here,":[37],"we":[38,57,127],"test":[39,223],"the":[40,63,97,113,119,163,179,182,197,222,226],"hypothesis":[41],"predictors":[43,232],"trained":[46,106],"maximize":[48],"To":[54,123],"do":[55],"this,":[56],"evaluate":[58,124],"several":[59,209],"metalearning":[60,90,235],"algorithms":[61,91],"on":[62],"problem":[64],"of":[65,85,101,118,191],"aerosol":[66],"optical":[67],"depth":[68],"(AOD)":[69],"retrieval.":[70],"The":[71,88,170],"measures":[74],"included":[75],"mean":[76],"squared":[77,81],"error,":[78,82],"correlation,":[79],"relative":[80],"fraction":[84],"satisfactory":[86],"predictions.":[87],"proposed":[89],"have":[92],"two-layer":[94],"architecture,":[95],"first":[98,120],"layer":[99,115,121],"consists":[100],"neural":[103,192,216],"networks,":[104],"each":[105],"using":[107],"different":[109],"measure,":[111],"second":[114],"aggregates":[116],"decisions":[117],"predictors.":[122],"AOD":[125,158,188],"predictors,":[126],"used":[128],"nearly":[129],"70":[130],"000":[131],"collocated":[132],"data":[133,171,224],"points":[134],"whose":[135,156],"attributes":[136],"were":[137,172,194],"radiances,":[138],"solar":[139],"view":[141],"angles,":[142],"terrain":[144],"elevation":[145],"from":[146,162],"MODerate":[147],"resolution":[148],"Imaging":[149],"Spectrometer":[150],"(MODIS)":[151],"instrument":[152],"satellite":[153],"observations":[154],"target":[157],"variable":[159],"was":[160],"obtained":[161,233],"ground-based":[164],"AEROsol":[165],"robotic":[166],"NETwork":[167],"(AERONET)":[168],"instruments.":[169],"collected":[173],"at":[174,220],"221":[175],"AERONET":[176],"locations":[177],"globe":[180],"period":[183],"between":[184],"2005":[185],"2007.":[187],"prediction":[189],"accuracies":[190],"networks":[193,217],"compared":[195],"recently":[198],"developed":[199],"operational":[200,227],"MODIS":[201],"<i":[202],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[203],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">C005</i>":[204],"retrieval":[205,228],"algorithm":[206,229],"other":[210],"data-mining":[211],"methods.":[212],"Results":[213],"showed":[214],"are":[218,236],"better":[219],"reproducing":[221],"than":[225],"by":[234],"robust":[237]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
