{"id":"https://openalex.org/W4387803206","doi":"https://doi.org/10.1109/igarss52108.2023.10283283","title":"Towards a Method for Taking Account of Uncertainties Through the Calculation of Masses in the Context of a Fusion of Heterogeneous Multi-Sensor Data on Air Pollution","display_name":"Towards a Method for Taking Account of Uncertainties Through the Calculation of Masses in the Context of a Fusion of Heterogeneous Multi-Sensor Data on Air Pollution","publication_year":2023,"publication_date":"2023-07-16","ids":{"openalex":"https://openalex.org/W4387803206","doi":"https://doi.org/10.1109/igarss52108.2023.10283283"},"language":"en","primary_location":{"id":"doi:10.1109/igarss52108.2023.10283283","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss52108.2023.10283283","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","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/A5093097228","display_name":"Aymeric Ambert","orcid":null},"institutions":[{"id":"https://openalex.org/I135117807","display_name":"Universit\u00e9 de Sherbrooke","ror":"https://ror.org/00kybxq39","country_code":"CA","type":"education","lineage":["https://openalex.org/I135117807"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Aymeric Ambert","raw_affiliation_strings":["Universit&#x00E9; de Sherbrooke,D&#x00E9;partement de G&#x00E9;omatique Appliqu&#x00E9;e,Sherbrooke,QC,Canada,J1K 2R1"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit&#x00E9; de Sherbrooke,D&#x00E9;partement de G&#x00E9;omatique Appliqu&#x00E9;e,Sherbrooke,QC,Canada,J1K 2R1","institution_ids":["https://openalex.org/I135117807"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055383221","display_name":"Micka\u00ebl Germain","orcid":"https://orcid.org/0000-0003-1867-7530"},"institutions":[{"id":"https://openalex.org/I135117807","display_name":"Universit\u00e9 de Sherbrooke","ror":"https://ror.org/00kybxq39","country_code":"CA","type":"education","lineage":["https://openalex.org/I135117807"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mickael Germain","raw_affiliation_strings":["Universit&#x00E9; de Sherbrooke,D&#x00E9;partement de G&#x00E9;omatique Appliqu&#x00E9;e,Sherbrooke,QC,Canada,J1K 2R1"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit&#x00E9; de Sherbrooke,D&#x00E9;partement de G&#x00E9;omatique Appliqu&#x00E9;e,Sherbrooke,QC,Canada,J1K 2R1","institution_ids":["https://openalex.org/I135117807"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5093097229","display_name":"Yacine Bourroubi","orcid":null},"institutions":[{"id":"https://openalex.org/I135117807","display_name":"Universit\u00e9 de Sherbrooke","ror":"https://ror.org/00kybxq39","country_code":"CA","type":"education","lineage":["https://openalex.org/I135117807"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Yacine Bourroubi","raw_affiliation_strings":["Universit&#x00E9; de Sherbrooke,D&#x00E9;partement de G&#x00E9;omatique Appliqu&#x00E9;e,Sherbrooke,QC,Canada,J1K 2R1"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit&#x00E9; de Sherbrooke,D&#x00E9;partement de G&#x00E9;omatique Appliqu&#x00E9;e,Sherbrooke,QC,Canada,J1K 2R1","institution_ids":["https://openalex.org/I135117807"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I135117807"],"apc_list":null,"apc_paid":null,"fwci":0.112,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.43572082,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"6826","last_page":"6828"},"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":0.9973999857902527,"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":0.9883999824523926,"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/sensor-fusion","display_name":"Sensor fusion","score":0.790266752243042},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6916143298149109},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6137030720710754},{"id":"https://openalex.org/keywords/air-pollution","display_name":"Air pollution","score":0.6050117015838623},{"id":"https://openalex.org/keywords/pollution","display_name":"Pollution","score":0.508131742477417},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.4869566857814789},{"id":"https://openalex.org/keywords/pollutant","display_name":"Pollutant","score":0.461794376373291},{"id":"https://openalex.org/keywords/data-integration","display_name":"Data integration","score":0.45729243755340576},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4333481192588806},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.4144173860549927},{"id":"https://openalex.org/keywords/risk-analysis","display_name":"Risk analysis (engineering)","score":0.4078303575515747},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.40777599811553955},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.34607261419296265},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3444645404815674},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.10209232568740845},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.0993407666683197},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08150723576545715}],"concepts":[{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.790266752243042},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6916143298149109},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6137030720710754},{"id":"https://openalex.org/C559116025","wikidata":"https://www.wikidata.org/wiki/Q131123","display_name":"Air pollution","level":2,"score":0.6050117015838623},{"id":"https://openalex.org/C521259446","wikidata":"https://www.wikidata.org/wiki/Q58734","display_name":"Pollution","level":2,"score":0.508131742477417},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.4869566857814789},{"id":"https://openalex.org/C82685317","wikidata":"https://www.wikidata.org/wiki/Q19829510","display_name":"Pollutant","level":2,"score":0.461794376373291},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.45729243755340576},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4333481192588806},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4144173860549927},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.4078303575515747},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.40777599811553955},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.34607261419296265},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3444645404815674},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.10209232568740845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.0993407666683197},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08150723576545715},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss52108.2023.10283283","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss52108.2023.10283283","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6700000166893005,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W2114463407","https://openalex.org/W2343114325","https://openalex.org/W2480078828","https://openalex.org/W3017269091"],"related_works":["https://openalex.org/W2389240616","https://openalex.org/W2384613820","https://openalex.org/W2169359190","https://openalex.org/W3094447531","https://openalex.org/W2388613575","https://openalex.org/W2362463548","https://openalex.org/W2062592733","https://openalex.org/W3030116098","https://openalex.org/W8795902","https://openalex.org/W2085627709"],"abstract_inverted_index":{"Air":[0],"pollution":[1,22,93,110,145],"has":[2],"become":[3],"a":[4,89,105],"major":[5],"challenge":[6],"in":[7],"the":[8,32,35,55,76,102,140,147],"context":[9,148],"of":[10,40,80,92,109,113,117,142,149,164],"climate":[11,150],"change.":[12,151],"Detecting":[13],"pollutants,":[14],"especially":[15],"fine":[16],"particles,":[17],"is":[18,47],"crucial":[19],"for":[20],"combating":[21],"and":[23,31,38,66,78,86,96,115,125,133,156,162],"mitigating":[24],"its":[25],"adverse":[26],"effects":[27],"on":[28],"human":[29],"health":[30],"environment.":[33],"However,":[34],"wide":[36],"variety":[37],"variability":[39],"data":[41,59,84,100,128,154],"sources":[42,65],"introduce":[43],"inherent":[44],"uncertainty":[45],"that":[46],"difficult":[48],"to":[49,62,74],"control.":[50],"To":[51],"address":[52],"this":[53,137,165],"challenge,":[54],"proposed":[56],"method":[57,103,138],"utilizes":[58],"fusion":[60,155],"techniques":[61],"integrate":[63],"diverse":[64],"heterogeneous":[67,157],"information.":[68],"By":[69,98,152],"doing":[70],"so,":[71],"it":[72,121,159],"aims":[73],"enhance":[75],"accuracy":[77],"reliability":[79],"pollutant":[81,118],"detection.":[82],"Advanced":[83],"analysis":[85,132],"modeling":[87],"provide":[88],"comprehensive":[90],"understanding":[91,163],"patterns,":[94],"sources,":[95,129],"impacts.":[97],"leveraging":[99],"fusion,":[101],"enables":[104],"more":[106],"effective":[107],"assessment":[108],"levels,":[111],"identification":[112],"hotspots,":[114],"evaluation":[116],"dispersion.":[119],"Additionally,":[120],"identifies":[122],"potential":[123],"correlations":[124],"conflicts":[126],"between":[127],"facilitating":[130],"robust":[131],"decision-making.":[134],"In":[135],"summary,":[136],"acknowledges":[139],"urgency":[141],"addressing":[143],"air":[144],"within":[146],"incorporating":[153],"data,":[158],"improves":[160],"monitoring":[161],"pressing":[166],"environmental":[167],"challenge.":[168]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
