{"id":"https://openalex.org/W2963352149","doi":"https://doi.org/10.1109/lgrs.2019.2900270","title":"Deep Learning Architecture for Estimating Hourly Ground-Level PM<sub>2.5</sub> Using Satellite Remote Sensing","display_name":"Deep Learning Architecture for Estimating Hourly Ground-Level PM<sub>2.5</sub> Using Satellite Remote Sensing","publication_year":2019,"publication_date":"2019-08-27","ids":{"openalex":"https://openalex.org/W2963352149","doi":"https://doi.org/10.1109/lgrs.2019.2900270","mag":"2963352149"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2019.2900270","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2019.2900270","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/A5054116340","display_name":"Yibo Sun","orcid":"https://orcid.org/0000-0002-9916-9863"},"institutions":[{"id":"https://openalex.org/I4210123392","display_name":"Beijing Municipal Ecological and Environmental Monitoring Center","ror":"https://ror.org/02ygbbs43","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210123392"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yibo Sun","raw_affiliation_strings":["Integrated Ecological Observation and Research Station, Jinggangshan, China"],"raw_orcid":"https://orcid.org/0000-0002-9916-9863","affiliations":[{"raw_affiliation_string":"Integrated Ecological Observation and Research Station, Jinggangshan, China","institution_ids":["https://openalex.org/I4210123392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000388086","display_name":"Qiaolin Zeng","orcid":"https://orcid.org/0000-0002-4208-5132"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiaolin Zeng","raw_affiliation_strings":["College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066324063","display_name":"Bing Geng","orcid":"https://orcid.org/0000-0001-5572-6675"},"institutions":[{"id":"https://openalex.org/I114218197","display_name":"Chinese Academy of Social Sciences","ror":"https://ror.org/05bxbmy32","country_code":"CN","type":"facility","lineage":["https://openalex.org/I114218197"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing Geng","raw_affiliation_strings":["Chinese Academy of Social Sciences, Institute for Urban and Environment Studies, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Social Sciences, Institute for Urban and Environment Studies, Beijing, China","institution_ids":["https://openalex.org/I114218197"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069319449","display_name":"Xingwen Lin","orcid":"https://orcid.org/0000-0002-4189-7366"},"institutions":[{"id":"https://openalex.org/I135237710","display_name":"Zhejiang Normal University","ror":"https://ror.org/01vevwk45","country_code":"CN","type":"education","lineage":["https://openalex.org/I135237710"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinwen Lin","raw_affiliation_strings":["College of Geography and Environment Science, Zhejiang Normal University, Zhejiang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Geography and Environment Science, Zhejiang Normal University, Zhejiang, China","institution_ids":["https://openalex.org/I135237710"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059964524","display_name":"Bilige Sude","orcid":null},"institutions":[{"id":"https://openalex.org/I4210123392","display_name":"Beijing Municipal Ecological and Environmental Monitoring Center","ror":"https://ror.org/02ygbbs43","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210123392"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bilige Sude","raw_affiliation_strings":["Integrated Ecological Observation and Research Station, Jinggangshan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Integrated Ecological Observation and Research Station, Jinggangshan, China","institution_ids":["https://openalex.org/I4210123392"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115588562","display_name":"Liangfu Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liangfu Chen","raw_affiliation_strings":["Chinese Academy of Sciences, Aerospace Information Research Institute, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Aerospace Information Research Institute, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.4631,"has_fulltext":false,"cited_by_count":72,"citation_normalized_percentile":{"value":0.92747198,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"16","issue":"9","first_page":"1343","last_page":"1347"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T10190","display_name":"Air Quality and Health Impacts","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2307","display_name":"Health, Toxicology and Mutagenesis"},"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":0.9948999881744385,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.6686223149299622},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.6331703662872314},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6331325173377991},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5812132358551025},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5622180700302124},{"id":"https://openalex.org/keywords/beijing","display_name":"Beijing","score":0.5380558371543884},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4550815522670746},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.4272671937942505},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4271705746650696},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.3652196526527405},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3176369071006775},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19958847761154175},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.19554653763771057},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15935149788856506},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.10095974802970886}],"concepts":[{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6686223149299622},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.6331703662872314},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6331325173377991},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5812132358551025},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5622180700302124},{"id":"https://openalex.org/C2778304055","wikidata":"https://www.wikidata.org/wiki/Q657474","display_name":"Beijing","level":3,"score":0.5380558371543884},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4550815522670746},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.4272671937942505},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4271705746650696},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3652196526527405},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3176369071006775},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19958847761154175},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.19554653763771057},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15935149788856506},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.10095974802970886},{"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/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"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/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2019.2900270","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2019.2900270","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1568887324","display_name":null,"funder_award_id":"2016YFC0502702","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G4876142843","display_name":null,"funder_award_id":"2018M631684","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1173523477","https://openalex.org/W1665214252","https://openalex.org/W1976991085","https://openalex.org/W2053785149","https://openalex.org/W2072128103","https://openalex.org/W2081990052","https://openalex.org/W2085260550","https://openalex.org/W2108079253","https://openalex.org/W2119362352","https://openalex.org/W2162982697","https://openalex.org/W2301552301","https://openalex.org/W2480175994","https://openalex.org/W2497200023","https://openalex.org/W2588978790","https://openalex.org/W2620300958","https://openalex.org/W2736216772","https://openalex.org/W2737242952","https://openalex.org/W2802727924","https://openalex.org/W2951572255","https://openalex.org/W3122817556","https://openalex.org/W4231109964","https://openalex.org/W6637242042"],"related_works":["https://openalex.org/W2015747722","https://openalex.org/W2362050182","https://openalex.org/W2382418233","https://openalex.org/W2369897927","https://openalex.org/W3031731056","https://openalex.org/W4293167957","https://openalex.org/W2361035307","https://openalex.org/W2380455807","https://openalex.org/W4382982879","https://openalex.org/W4311044000"],"abstract_inverted_index":{"The":[0,88,122,209],"prediction":[1,55,109,144,149],"of":[2,14,42,62,101,136,218],"PM2.5":[3,32,54,64,175,195,219,228],"concentration":[4],"is":[5,33],"a":[6,34,49,224],"canonical":[7],"predictive":[8],"challenge":[9],"due":[10],"to":[11,29,57,170],"the":[12,59,66,75,80,96,108,112,115,126,129,133,164,172,184,189,216],"distribution":[13,192],"$PM_{2.5}$":[15],"appears":[16],"serious":[17],"spatiotemporal":[18,39,60,191],"variability":[19,61],"at":[20],"multiple":[21],"scales.":[22],"Currently,":[23],"using":[24,65,95,197,230],"satellite-based":[25],"remote":[26,67],"sensing":[27,68],"data":[28,73,97,199],"estimate":[30,171],"ground-level":[31,63],"promising":[35],"method":[36],"for":[37,227],"providing":[38],"continuous":[40],"information":[41],"PM2.5.":[43],"In":[44],"this":[45,120],"letter,":[46],"we":[47,106],"proposed":[48,210],"deep":[50,232],"neural":[51],"network":[52],"(DNN)-based":[53],"model":[56,90,167,212],"capture":[58,188],"aerosol":[69],"optical":[70],"depth":[71],"(AOD)":[72],"from":[74,98],"Himawari-8":[76],"satellite":[77],"along":[78],"with":[79,132,176,194],"conventional":[81,201],"meteorological":[82,202],"observation":[83],"variables":[84,204],"(denoted":[85],"as":[86],"PM25-DNN).":[87],"PM25-DNN":[89,113,127,166,211],"was":[91,168],"trained":[92,165],"and":[93,105,114,147,160,200,221],"tested":[94],"Beijing-Tianjin-Hebei":[99],"region":[100],"China":[102],"in":[103,119],"2017,":[104],"compared":[107],"performance":[110],"between":[111],"current":[116],"state-of-the-art":[117],"methods":[118],"field.":[121],"results":[123,181],"show":[124],"that":[125,183],"outperforms":[128],"other":[130],"models":[131],"cross-validated":[134],"coefficient":[135],"determination":[137],"($\\text{R}^{2}$":[138],"),":[139],"root-mean-square":[140],"error":[141,145,150],"(RMSE),":[142],"mean":[143],"(MPE),":[146],"relative":[148],"(RPE)":[151],"were":[152],"0.84,":[153],"$19.9~\\mu":[154],"\\text{g}/\\text{m}^{3}$":[155,158],",":[156,159],"$11.89~\\mu":[157],"41.21%,":[161],"respectively.":[162],"Then,":[163],"applied":[169],"hourly":[173],"gridded":[174],"1-km":[177],"spatial":[178],"resolution.":[179],"Our":[180],"indicate":[182],"DNN":[185],"architecture":[186],"can":[187,213],"essential":[190],"associated":[193],"only":[196],"AOD":[198],"observational":[203],"without":[205],"more":[206],"handcrafted":[207],"features.":[208],"greatly":[214],"improve":[215],"accuracy":[217],"estimation,":[220],"it":[222],"provides":[223],"new":[225],"perspective":[226],"monitoring":[229],"end-to-end":[231],"learning":[233],"method.":[234]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}