{"id":"https://openalex.org/W4408446194","doi":"https://doi.org/10.5194/egusphere-egu25-1408","title":"A Knowledge-Guided Deep Learning Model for Extracting Pollution-free Seismic Microwave Brightness Temperature Anomalies","display_name":"A Knowledge-Guided Deep Learning Model for Extracting Pollution-free Seismic Microwave Brightness Temperature Anomalies","publication_year":2025,"publication_date":"2025-03-14","ids":{"openalex":"https://openalex.org/W4408446194","doi":"https://doi.org/10.5194/egusphere-egu25-1408"},"language":"en","primary_location":{"id":"doi:10.5194/egusphere-egu25-1408","doi":"https://doi.org/10.5194/egusphere-egu25-1408","is_oa":true,"landing_page_url":"https://doi.org/10.5194/egusphere-egu25-1408","pdf_url":null,"source":{"id":"https://openalex.org/S4306508951","display_name":"EGU General Assembly Conference Abstracts","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"},"volume":null,"type":"conference-abstract","is_traditional":false,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.5194/egusphere-egu25-1408","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044246378","display_name":"Yuan Qi","orcid":"https://orcid.org/0000-0001-7935-5397","observed_orcids":["https://orcid.org/0000-0001-7935-5397","https://orcid.org/0009-0008-2447-1444"]},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Yuan Qi","raw_affiliation_strings":["The University of Hong Kong, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-7935-5397","affiliations":[{"raw_affiliation_string":"The University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054722054","display_name":"Wenfei Mao","orcid":"https://orcid.org/0000-0001-8536-9007","observed_orcids":["https://orcid.org/0000-0001-8536-9007"]},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenfei Mao","raw_affiliation_strings":["Central South University, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090637514","display_name":"Lixin Wu","orcid":"https://orcid.org/0000-0001-5860-3371","observed_orcids":["https://orcid.org/0000-0001-5860-3371"]},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lixin Wu","raw_affiliation_strings":["Central South University, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100705731","display_name":"Bo Huang","orcid":"https://orcid.org/0000-0002-5063-3522","observed_orcids":["https://orcid.org/0000-0002-5063-3522"]},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Bo Huang","raw_affiliation_strings":["The University of Hong Kong, Hong Kong, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5044246378"],"corresponding_institution_ids":["https://openalex.org/I889458895"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12424","display_name":"Earthquake Detection and Analysis","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12424","display_name":"Earthquake Detection and Analysis","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"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/T13018","display_name":"Seismology and Earthquake Studies","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11312","display_name":"Soil Moisture and Remote Sensing","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/earthquake-precursors","display_name":"earthquake precursors","score":0.796999990940094},{"id":"https://openalex.org/keywords/seismic-anomaly-detection","display_name":"seismic anomaly detection","score":0.4059999883174896},{"id":"https://openalex.org/keywords/land-surface-temperature","display_name":"land surface temperature","score":0.621999979019165},{"id":"https://openalex.org/keywords/multi-source-remote-sensing-data","display_name":"multi-source remote sensing data","score":0.7570000290870667},{"id":"https://openalex.org/keywords/soil-moisture","display_name":"soil moisture","score":0.7149999737739563},{"id":"https://openalex.org/keywords/vegetation-index","display_name":"vegetation indices","score":0.8820000290870667},{"id":"https://openalex.org/keywords/water-vapor-content","display_name":"water vapor concentration","score":0.6700000166893005},{"id":"https://openalex.org/keywords/cloud-cover","display_name":"cloud cover","score":0.777999997138977},{"id":"https://openalex.org/keywords/digital-elevation-model","display_name":"digital elevation model","score":0.8169999718666077},{"id":"https://openalex.org/keywords/short-term-earthquake-prediction","display_name":"short-term earthquake prediction","score":0.8650000095367432},{"id":"https://openalex.org/keywords/tibetan-plateau","display_name":"Tibetan Plateau","score":0.9900000095367432}],"concepts":[{"id":"https://openalex.org/C125245961","wikidata":"https://www.wikidata.org/wiki/Q221656","display_name":"Brightness","level":2,"score":0.6732516884803772},{"id":"https://openalex.org/C53802167","wikidata":"https://www.wikidata.org/wiki/Q4538627","display_name":"Brightness temperature","level":3,"score":0.6246911287307739},{"id":"https://openalex.org/C44838205","wikidata":"https://www.wikidata.org/wiki/Q127995","display_name":"Microwave","level":2,"score":0.5812378525733948},{"id":"https://openalex.org/C521259446","wikidata":"https://www.wikidata.org/wiki/Q58734","display_name":"Pollution","level":2,"score":0.5664898157119751},{"id":"https://openalex.org/C2989390135","wikidata":"https://www.wikidata.org/wiki/Q466500","display_name":"Microwave heating","level":3,"score":0.4955257177352905},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.43061307072639465},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4276723861694336},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4244527816772461},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.35879021883010864},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.3446299731731415},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25242364406585693},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.17587316036224365},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.14422988891601562},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09134519100189209},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5194/egusphere-egu25-1408","doi":"https://doi.org/10.5194/egusphere-egu25-1408","is_oa":true,"landing_page_url":"https://doi.org/10.5194/egusphere-egu25-1408","pdf_url":null,"source":{"id":"https://openalex.org/S4306508951","display_name":"EGU General Assembly Conference Abstracts","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.5194/egusphere-egu25-1408","doi":"https://doi.org/10.5194/egusphere-egu25-1408","is_oa":true,"landing_page_url":"https://doi.org/10.5194/egusphere-egu25-1408","pdf_url":null,"source":{"id":"https://openalex.org/S4306508951","display_name":"EGU General Assembly Conference Abstracts","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7204250305","https://openalex.org/W3011003631","https://openalex.org/W3177484620","https://openalex.org/W4221020506","https://openalex.org/W7165546769","https://openalex.org/W4390752913","https://openalex.org/W2596922662","https://openalex.org/W3003361601","https://openalex.org/W3038909277","https://openalex.org/W2095619506"],"abstract_inverted_index":{"There":[0],"has":[1,52],"long":[2,271],"been":[3,53],"research":[4],"on":[5,270,289,348],"the":[6,14,22,65,108,170,188,197,200,209,219,225,232,241,251,254,259,264,276,280,284,290,293,295,302,306,330,340,352,363],"phenomenon":[7],"of":[8,35,93,103,114,191,235,279,286,305],"abnormal":[9],"microwave":[10,24,120],"radiation":[11,25],"emitted":[12],"from":[13],"Earth's":[15],"surface":[16,39,44,119,125,128,160,291],"before":[17,194],"a":[18,33,83,90,111,153,334,345],"major":[19],"earthquake.":[20],"However,":[21],"enhanced":[23],"received":[26],"by":[27,32,183,204,249,301],"satellite":[28],"sensors":[29],"is":[30,268,318,366],"affected":[31,300],"combination":[34],"factors":[36,158,288],"such":[37,117,338],"as":[38,118,339,362],"vegetation,":[40],"soil":[41,131],"moisture,":[42],"land":[43,124,140],"temperature,":[45],"and":[46,73,147,152,159,181,195,213,275,328,375,380],"atmospheric":[47,134],"environment.":[48],"So":[49],"far,":[50],"it":[51,217],"difficult":[54],"to":[55,223,246,292,321,326,373],"remove":[56],"non-seismic":[57,331],"interference":[58],"through":[59,165,208],"quantitative":[60],"physical":[61],"modeling,":[62],"leaving":[63],"only":[64],"earthquake-related":[66,260],"additional":[67,233,242,303,323],"components":[68],"for":[69,98,382],"earthquake":[70,75,104,359,378,384],"precursor":[71],"analysis":[72],"short-term":[74,383],"prediction.":[76,385],"To":[77],"tackle":[78],"with":[79,253],"this,":[80],"we":[81,238,355],"developed":[82,177],"knowledge-guided":[84],"deep":[85,166,265],"learning":[86,167],"model":[87,145,155,175,222,281,346],"that":[88,228],"leverages":[89],"large":[91,112],"amount":[92,113],"remote":[94],"sensing":[95],"observation":[96],"data":[97,207,274,325,350,365],"training,":[99],"incorporating":[100],"prior":[101],"knowledge":[102],"anomaly":[105],"analysis.":[106],"In":[107,169,314],"modelling":[109],"process,":[110],"multi-source":[115],"data,":[116],"brightness":[121],"temperature":[122,126],"(MBT),":[123],"(LST),":[127],"vegetation":[129],"index,":[130,133],"moisture":[132],"water":[135],"vapor":[136],"content,":[137],"cloud":[138],"cover,":[139],"cover":[141],"type,":[142,149],"digital":[143],"elevation":[144],"(DEM),":[146],"geological":[148],"were":[150,162],"collected,":[151],"regression":[154,174,211,221],"between":[156,178],"multiple":[157,287],"MBT":[161,226,243,261,360],"firstly":[163],"established":[164],"methods.":[168],"same":[171],"way,":[172],"another":[173],"was":[176,202,215],"non-temperature":[179,206],"parameters":[180],"LST":[182,201],"using":[184,205,351],"historical":[185,349],"records.":[186],"During":[187],"seismic":[189,247],"window":[190],"one":[192],"month":[193],"after":[196,343],"target":[198,336],"earthquake,":[199,307],"obtained":[203],"second":[210],"model,":[212],"then":[214],"substituted":[216],"into":[218],"first":[220],"get":[224],"value":[227,244],"does":[229],"not":[230],"include":[231,283],"effects":[234],"earthquakes.":[236],"Eventually,":[237],"can":[239,310,356,370],"obtain":[240,357],"due":[245],"activity":[248],"calculating":[250],"difference":[252],"actual":[255],"observation,":[256],"which":[257],"represents":[258],"anomaly.":[262],"Since":[263],"learning-based":[266],"modeling":[267],"based":[269,347],"time":[272],"series":[273],"output":[277],"results":[278,297],"already":[282],"contribution":[285],"MBT,":[294],"differential":[296],"are":[298],"mainly":[299],"impacts":[304],"so":[308],"they":[309],"be":[311,371],"considered":[312],"'pollution-free'.":[313],"other":[315],"words,":[316],"there":[317],"no":[319],"need":[320],"use":[322],"auxiliary":[324],"discriminate":[327],"separate":[329],"disturbances.":[332],"For":[333],"specific":[335],"area,":[337],"Tibetan":[341],"Plateau,":[342],"establishing":[344],"aforementioned":[353],"method,":[354],"real-time":[358],"variations":[361],"input":[364],"continuously":[367],"updated.":[368],"This":[369],"used":[372],"analyze":[374],"identify":[376],"potential":[377],"precursors,":[379],"consequently,":[381]},"counts_by_year":[],"updated_date":"2026-11-09T13:22:03.289127","created_date":"2025-03-15T00:00:00"}
