{"id":"https://openalex.org/W3120340923","doi":"https://doi.org/10.1145/3429309.3429328","title":"U-net for learning and inference of dense representation of multiple air pollutants from satellite imagery","display_name":"U-net for learning and inference of dense representation of multiple air pollutants from satellite imagery","publication_year":2020,"publication_date":"2020-09-22","ids":{"openalex":"https://openalex.org/W3120340923","doi":"https://doi.org/10.1145/3429309.3429328","mag":"3120340923"},"language":"en","primary_location":{"id":"doi:10.1145/3429309.3429328","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3429309.3429328","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th International Conference on Climate Informatics","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/A5025481720","display_name":"Jacquelyn A. Shelton","orcid":null},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Jacquelyn Shelton","raw_affiliation_strings":["Hong Kong Polytechnic University, China"],"affiliations":[{"raw_affiliation_string":"Hong Kong Polytechnic University, China","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070500440","display_name":"Przemyslaw Polewski","orcid":"https://orcid.org/0000-0003-4763-6594"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]},{"id":"https://openalex.org/I4210122239","display_name":"TomTom (Germany)","ror":"https://ror.org/02pvy4b66","country_code":"DE","type":"company","lineage":["https://openalex.org/I2905213637","https://openalex.org/I4210122239"]}],"countries":["DE","HK"],"is_corresponding":false,"raw_author_name":"Przemyslaw Polewski","raw_affiliation_strings":["TomTom Location Technology, Germany, and Hong Kong Polytechnic University, China"],"affiliations":[{"raw_affiliation_string":"TomTom Location Technology, Germany, and Hong Kong Polytechnic University, China","institution_ids":["https://openalex.org/I14243506","https://openalex.org/I4210122239"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100647649","display_name":"Wei Yao","orcid":"https://orcid.org/0000-0001-7704-0615"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Wei Yao","raw_affiliation_strings":["Hong Kong Polytechnic University, China"],"affiliations":[{"raw_affiliation_string":"Hong Kong Polytechnic University, China","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5025481720"],"corresponding_institution_ids":["https://openalex.org/I14243506"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.14322773,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"128","last_page":"133"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9980000257492065,"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":0.9980000257492065,"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/T11588","display_name":"Atmospheric and Environmental Gas Dynamics","score":0.9749000072479248,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9621000289916992,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6103171110153198},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6046086549758911},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.6016630530357361},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.571668267250061},{"id":"https://openalex.org/keywords/satellite-imagery","display_name":"Satellite imagery","score":0.5400685667991638},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5196555852890015},{"id":"https://openalex.org/keywords/pollutant","display_name":"Pollutant","score":0.4457981288433075},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.39212656021118164},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35329461097717285},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.3531501889228821},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.16688838601112366},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.09733861684799194},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0789792537689209}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6103171110153198},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6046086549758911},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.6016630530357361},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.571668267250061},{"id":"https://openalex.org/C2778102629","wikidata":"https://www.wikidata.org/wiki/Q725252","display_name":"Satellite imagery","level":2,"score":0.5400685667991638},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5196555852890015},{"id":"https://openalex.org/C82685317","wikidata":"https://www.wikidata.org/wiki/Q19829510","display_name":"Pollutant","level":2,"score":0.4457981288433075},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.39212656021118164},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35329461097717285},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3531501889228821},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.16688838601112366},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.09733861684799194},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0789792537689209},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3429309.3429328","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3429309.3429328","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th International Conference on Climate Informatics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2525974879","https://openalex.org/W2605847660","https://openalex.org/W2613456556","https://openalex.org/W2624871570","https://openalex.org/W2786627679","https://openalex.org/W2791707925","https://openalex.org/W2796464444","https://openalex.org/W2807567802","https://openalex.org/W2912034185","https://openalex.org/W2951572255","https://openalex.org/W2963334029","https://openalex.org/W3015019427","https://openalex.org/W3015305783","https://openalex.org/W3015407791","https://openalex.org/W3105234146","https://openalex.org/W3122817556","https://openalex.org/W4256172916"],"related_works":["https://openalex.org/W2382027398","https://openalex.org/W4280559622","https://openalex.org/W3146724685","https://openalex.org/W2366937709","https://openalex.org/W2353066366","https://openalex.org/W2921193467","https://openalex.org/W2808054333","https://openalex.org/W4225133292","https://openalex.org/W1998137479","https://openalex.org/W2004432735"],"abstract_inverted_index":{"Air":[0],"pollution":[1,33],"is":[2,10,21],"an":[3,11,98],"important":[4],"topic":[5],"on":[6,113],"countless":[7],"fronts":[8],"and":[9,30,35,47,116,121],"active":[12],"area":[13],"of":[14,18,32,88],"research.":[15],"The":[16],"goal":[17],"this":[19,105],"work":[20],"to":[22,64,92],"provide":[23],"a":[24,84,94],"machine":[25],"learning":[26,29],"model":[27],"for":[28,97,128],"inference":[31],"concentrations":[34,112,120],"air":[36],"quality":[37],"measures,":[38],"namely":[39],"Particulate":[40],"Matter":[41],"2.5,":[42],"NO3":[43],",":[44,49],"Nitrate":[45],"Pollution,":[46],"NH4":[48],"Atmospheric":[50],"Ammonium,":[51],"with":[52],"high":[53],"granularity":[54],"by":[55],"using":[56],"easily":[57],"obtainable":[58],"satellite":[59],"imagery":[60],"data.":[61],"In":[62],"order":[63],"achieve":[65],"this,":[66],"we":[67,139],"propose":[68],"the":[69,109,119,131,142,151],"fully":[70],"convolutional":[71],"network":[72,132],"U-net":[73],"that,":[74],"unlike":[75],"previous":[76],"work,":[77],"can":[78,107,117,146],"predict":[79,93,118],"these":[80],"pollutant":[81,111,144],"values":[82],"at":[83],"pixel-level":[85],"high-resolution":[86],"instead":[87],"being":[89],"able":[90],"only":[91],"single":[95],"value":[96],"entire":[99],"geographical":[100],"region.":[101],"We":[102],"demonstrate":[103],"that":[104,130,141],"approach":[106],"reconstruct":[108],"considered":[110],"ground-truth":[114],"data":[115,129],"their":[122],"spatial":[123],"structure":[124],"reasonably":[125],"well,":[126],"even":[127],"has":[133],"temporally":[134],"not":[135],"yet":[136],"seen.":[137],"Finally,":[138],"illustrate":[140],"model\u2019s":[143],"predictions":[145],"offer":[147],"valuable":[148],"insights":[149],"into":[150],"current":[152],"COVID-19":[153],"pandemic.":[154]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}