{"id":"https://openalex.org/W2069483264","doi":"https://doi.org/10.1109/tgrs.2015.2395722","title":"Evaluation of a MISR-Based High-Resolution Aerosol Retrieval Method Using AERONET DRAGON Campaign Data","display_name":"Evaluation of a MISR-Based High-Resolution Aerosol Retrieval Method Using AERONET DRAGON Campaign Data","publication_year":2015,"publication_date":"2015-02-24","ids":{"openalex":"https://openalex.org/W2069483264","doi":"https://doi.org/10.1109/tgrs.2015.2395722","mag":"2069483264"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2015.2395722","doi":"https://doi.org/10.1109/tgrs.2015.2395722","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2015.2395722","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","ccf-b","cwts-core","dongbi-b","jufo-3","norway-2","poland-200","russia-white-list-1","vabb-shw"],"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 Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},"volume":null,"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/A5080346989","display_name":"Taesup Moon","orcid":"https://orcid.org/0000-0002-9257-6503","observed_orcids":["https://orcid.org/0000-0002-9257-6503"]},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]},{"id":"https://openalex.org/I4405259277","display_name":"Samsung Electronics (South Korea)","ror":"https://ror.org/020m7t761","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4405259277"]},{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["KR","US"],"is_corresponding":false,"raw_author_name":"Taesup Moon","raw_affiliation_strings":["Department of Statistics, College of Letters and Science, Samsung Electronics, Inc., Suwon, CA, Korea","Dept. of Stat., Univ. of California Berkeley, Berkeley, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, College of Letters and Science, Samsung Electronics, Inc., Suwon, CA, Korea","institution_ids":["https://openalex.org/I2250650973","https://openalex.org/I4405259277"]},{"raw_affiliation_string":"Dept. of Stat., Univ. of California Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010859006","display_name":"Yueqing Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yueqing Wang","raw_affiliation_strings":["Google Inc., Mountain View, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Inc., Mountain View, CA, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100355638","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0001-5477-2186","observed_orcids":["https://orcid.org/0000-0001-5477-2186","https://orcid.org/0009-0004-2020-2870"]},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yang Liu","raw_affiliation_strings":["Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA","Dept. of Environ. Health, Emory Univ., Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA","institution_ids":["https://openalex.org/I150468666"]},{"raw_affiliation_string":"Dept. of Environ. Health, Emory Univ., Atlanta, GA, USA","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112583535","display_name":"Bin Yu","orcid":"https://orcid.org/0009-0007-1607-9285","observed_orcids":["https://orcid.org/0009-0007-1607-9285"]},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Bin Yu","raw_affiliation_strings":["Department of Statistics, College of Letters and Science and the Department of Electrical Engineering and Computer Sciences, College of Engineering, Peking University, Beijing, CA, China","Dept. of Stat., Univ. of California Berkeley, Berkeley, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, College of Letters and Science and the Department of Electrical Engineering and Computer Sciences, College of Engineering, Peking University, Beijing, CA, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Dept. of Stat., Univ. of California Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":0.7871,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.74998609,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":96},"biblio":{"volume":"53","issue":"8","first_page":"4328","last_page":"4339"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10347","display_name":"Atmospheric aerosols and clouds","score":0.9980000257492065,"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":0.9980000257492065,"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":0.0017999999690800905,"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":0.0,"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/aerosol-optical-depth-retrieval","display_name":"aerosol optical depth retrieval","score":0.9810000061988831},{"id":"https://openalex.org/keywords/misr","display_name":"MISR","score":0.7480000257492065},{"id":"https://openalex.org/keywords/bayesian-hierarchical-model","display_name":"Bayesian hierarchical model","score":0.9459999799728394},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.8790000081062317},{"id":"https://openalex.org/keywords/urban-air-pollution","display_name":"urban air pollution","score":0.7549999952316284},{"id":"https://openalex.org/keywords/satellite-aerosol-products","display_name":"satellite aerosol products","score":0.5019999742507935}],"concepts":[{"id":"https://openalex.org/C2777634575","wikidata":"https://www.wikidata.org/wiki/Q291476","display_name":"AERONET","level":3,"score":0.9423560500144958},{"id":"https://openalex.org/C2779345167","wikidata":"https://www.wikidata.org/wiki/Q104541","display_name":"Aerosol","level":2,"score":0.7662304639816284},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.6637687683105469},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6414633393287659},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.5513866543769836},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.47414514422416687},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4553431272506714},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4300786256790161},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.418832927942276},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3529188632965088},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.2839643955230713},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.19275739789009094},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16012322902679443},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13058578968048096},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.08157801628112793}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tgrs.2015.2395722","doi":"https://doi.org/10.1109/tgrs.2015.2395722","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2015.2395722","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","ccf-b","cwts-core","dongbi-b","jufo-3","norway-2","poland-200","russia-white-list-1","vabb-shw"],"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 Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:escholarship.org/ark:/13030/qt8339d9rc","doi":null,"is_oa":false,"landing_page_url":"https://escholarship.org/uc/item/8339d9rc","pdf_url":null,"source":{"id":"https://openalex.org/S4306400115","display_name":"eScholarship (California Digital Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2801248553","host_organization_name":"California Digital Library","host_organization_lineage":["https://openalex.org/I2801248553"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing, vol 53, iss 8","raw_type":"article"},{"id":"pmh:oai:escholarship.org:ark:/13030/qt8339d9rc","doi":null,"is_oa":false,"landing_page_url":"https://escholarship.org/uc/item/8339d9rc","pdf_url":null,"source":{"id":"https://openalex.org/S4306400115","display_name":"eScholarship (California Digital Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2801248553","host_organization_name":"California Digital Library","host_organization_lineage":["https://openalex.org/I2801248553"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing, vol 53, iss 8","raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G6803761678","display_name":"Sparse and structured networks: Statistical theory and algorithms","funder_award_id":"1107000","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8539225115","display_name":"CDI Type II:     Collaborative Research:    Sparse Inference:   New Tools for Structural Knowledge Discovery","funder_award_id":"0835531","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W814297792","https://openalex.org/W847452387","https://openalex.org/W1537424266","https://openalex.org/W1964519625","https://openalex.org/W1972585310","https://openalex.org/W1985093013","https://openalex.org/W1993814425","https://openalex.org/W2004910629","https://openalex.org/W2005017395","https://openalex.org/W2011740524","https://openalex.org/W2017742916","https://openalex.org/W2026317156","https://openalex.org/W2048512417","https://openalex.org/W2050250373","https://openalex.org/W2067609356","https://openalex.org/W2069389213","https://openalex.org/W2069977802","https://openalex.org/W2074749767","https://openalex.org/W2075462283","https://openalex.org/W2084564677","https://openalex.org/W2087526861","https://openalex.org/W2089433206","https://openalex.org/W2098065523","https://openalex.org/W2109277197","https://openalex.org/W2110052313","https://openalex.org/W2110673467","https://openalex.org/W2129479849","https://openalex.org/W2135973421","https://openalex.org/W2136796925","https://openalex.org/W2139937607","https://openalex.org/W2140282454","https://openalex.org/W2148534890","https://openalex.org/W2160045805","https://openalex.org/W2167604263","https://openalex.org/W4292691288"],"related_works":["https://openalex.org/W1964519625","https://openalex.org/W2605772517","https://openalex.org/W2744179832","https://openalex.org/W2915275133","https://openalex.org/W2620778567","https://openalex.org/W4321995232","https://openalex.org/W2896823820","https://openalex.org/W2011922020","https://openalex.org/W4309918176","https://openalex.org/W2995734596"],"abstract_inverted_index":{"Satellite-retrieved":[0],"aerosol":[1,69,208],"optical":[2],"depth":[3],"(AOD)":[4],"can":[5,103],"potentially":[6],"provide":[7],"an":[8],"effective":[9],"way":[10],"to":[11,72,76],"complement":[12],"the":[13,26,36,43,67,95,109,138,158,164,184,204,212,220,231,238,250,258,265,269,274,277],"spatial":[14,58,85,100],"coverage":[15,228],"limitation":[16],"of":[17,35,60,120,157,186,203,252,268,276],"a":[18,57,81,112,118,195],"ground":[19,201],"particulate":[20],"air-pollution":[21],"monitoring":[22,32],"network":[23],"such":[24],"as":[25],"U.S.":[27],"Environment":[28],"Protection":[29],"Agency's":[30],"regulatory":[31],"network.":[33],"One":[34],"current":[37],"state-of-the-art":[38],"AOD":[39,114,205,226],"retrieval":[40,115,227,270],"methods":[41],"is":[42,87,131,162,255],"National":[44],"Aeronautics":[45],"and":[46,102,108,137,154,206,229,261],"Space":[47],"Administration's":[48],"Multiangle":[49],"Imaging":[50],"SpectroRadiometer":[51],"(MISR)":[52],"operational":[53,240],"algorithm,":[54,160,166],"which":[55,130,161,190],"has":[56,98,126,223],"resolution":[59,86,119],"17.6":[61,64],"km":[62,122,125],"\u00d7":[63,123],"km.":[65],"Although":[66],"MISR's":[68],"products":[70],"lead":[71],"exciting":[73],"research":[74],"opportunities":[75],"study":[77],"particle":[78,209],"composition":[79],"at":[80],"regional":[82],"scale,":[83],"its":[84],"too":[88],"coarse":[89],"for":[90],"analyzing":[91],"urban":[92],"areas,":[93],"where":[94],"air":[96],"pollution":[97],"stronger":[99],"variations":[101],"severely":[104],"impact":[105],"public":[106],"health":[107],"environment.":[110],"Accordingly,":[111],"novel":[113,259],"algorithm":[116,222],"with":[117,237,245],"4.4":[121,124],"been":[127],"recently":[128],"developed,":[129],"based":[132],"on":[133],"hierarchical":[134],"Bayesian":[135],"modeling":[136,260],"Monte":[139],"Carlo":[140],"Markov":[141],"chain":[142],"(MCMC)":[143],"inference":[144,262],"method.":[145,263],"In":[146],"this":[147],"paper,":[148],"we":[149],"carry":[150],"out":[151],"detailed":[152,243],"quantitative":[153,278],"qualitative":[155],"evaluations":[156],"new":[159],"called":[163],"HB-MCMC":[165,221],"using":[167],"recent":[168],"AErosol":[169],"RObotic":[170],"NETwork":[171],"(AERONET)":[172],"Distributed":[173],"Regional":[174],"Aerosol":[175],"Gridded":[176],"Observation":[177],"Networks":[178],"(DRAGON)":[179],"campaign":[180],"data":[181],"obtained":[182],"in":[183,194],"summer":[185],"2011.":[187],"These":[188],"data,":[189],"were":[191],"not":[192],"available":[193],"previous":[196],"study,":[197],"contain":[198],"spatially":[199],"dense":[200],"measurements":[202],"other":[207],"characteristics":[210],"from":[211,257],"Baltimore-Washington,":[213],"DC":[214],"region.":[215],"Our":[216,242],"results":[217,271],"show":[218,248],"that":[219,249],"16.2%":[224],"more":[225],"improves":[230],"root-mean-square":[232],"error":[233],"by":[234],"38.3%":[235],"compared":[236],"MISR":[239],"algorithm.":[241],"analyses":[244],"various":[246],"metrics":[247],"improvement":[251],"our":[253],"scheme":[254],"coming":[256],"Furthermore,":[264],"map":[266],"overlay":[267],"qualitatively":[272],"confirms":[273],"findings":[275],"analyses.":[279]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2016-06-24T00:00:00"}