{"id":"https://openalex.org/W4388286252","doi":"https://doi.org/10.1109/tgrs.2023.3329709","title":"Semantic Segmentation of Land Cover in Urban Areas by Fusing Multisource Satellite Image Time Series","display_name":"Semantic Segmentation of Land Cover in Urban Areas by Fusing Multisource Satellite Image Time Series","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4388286252","doi":"https://doi.org/10.1109/tgrs.2023.3329709"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3329709","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3329709","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,"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"},"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/A5047516173","display_name":"Jining Yan","orcid":"https://orcid.org/0000-0003-0680-5427"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jining Yan","raw_affiliation_strings":["School of Computer Science, China University of Geosciences, Wuhan, China","State Environmental Protection Key Laboratory of Source Apportionment and Control of Aquatic Pollution, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]},{"raw_affiliation_string":"State Environmental Protection Key Laboratory of Source Apportionment and Control of Aquatic Pollution, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100326769","display_name":"Jingwei Liu","orcid":"https://orcid.org/0000-0002-4685-0196"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingwei Liu","raw_affiliation_strings":["School of Computer Science and the Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan, China","School of Computer Science, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and the Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]},{"raw_affiliation_string":"School of Computer Science, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074098507","display_name":"Dong Liang","orcid":"https://orcid.org/0000-0001-9147-7792"},"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/I4210096250","display_name":"Beijing Institute of Big Data Research","ror":"https://ror.org/00s1sz824","country_code":"CN","type":"facility","lineage":["https://openalex.org/I20231570","https://openalex.org/I37796252","https://openalex.org/I4210096250"]},{"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":"Dong Liang","raw_affiliation_strings":["International Research Center of Big Data for Sustainable Development Goals, Beijing, China","Aerospace Information Research Institute, Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"International Research Center of Big Data for Sustainable Development Goals, Beijing, China","institution_ids":["https://openalex.org/I4210096250"]},{"raw_affiliation_string":"Aerospace Information Research Institute, Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100364886","display_name":"Yi Wang","orcid":"https://orcid.org/0000-0002-1347-7030"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Wang","raw_affiliation_strings":["Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100362041","display_name":"Jun Li","orcid":"https://orcid.org/0000-0003-1613-9448"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Li","raw_affiliation_strings":["School of Computer Science and the Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan, China","School of Computer Science, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and the Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]},{"raw_affiliation_string":"School of Computer Science, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009116003","display_name":"Lizhe Wang","orcid":"https://orcid.org/0000-0003-2766-0845"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lizhe Wang","raw_affiliation_strings":["School of Computer Science and the Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan, China","School of Computer Science, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and the Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]},{"raw_affiliation_string":"School of Computer Science, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5047516173"],"corresponding_institution_ids":["https://openalex.org/I3124059619"],"apc_list":null,"apc_paid":null,"fwci":4.4355,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.9515506,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.998199999332428,"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"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.998199999332428,"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"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9896000027656555,"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/computer-science","display_name":"Computer science","score":0.7705305814743042},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6509824991226196},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6010306477546692},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5653073787689209},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.5143104791641235},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.4854634404182434},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4666431248188019},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4382636845111847},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4370511472225189},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4138632118701935},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3204862177371979},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.19480380415916443},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1332721710205078}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7705305814743042},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6509824991226196},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6010306477546692},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5653073787689209},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.5143104791641235},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.4854634404182434},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4666431248188019},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4382636845111847},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4370511472225189},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4138632118701935},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3204862177371979},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.19480380415916443},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1332721710205078},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3329709","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3329709","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,"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"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G4288132589","display_name":null,"funder_award_id":"2642022009","funder_id":"https://openalex.org/F4320328899","funder_display_name":"China University of Geosciences"},{"id":"https://openalex.org/G509352352","display_name":null,"funder_award_id":"41925007","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7082693669","display_name":null,"funder_award_id":"CCF-AFSG RF20220215","funder_id":"https://openalex.org/F4320318398","funder_display_name":"Ant Group"}],"funders":[{"id":"https://openalex.org/F4320318398","display_name":"Ant Group","ror":null},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320328899","display_name":"China University of Geosciences","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1544574920","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1915168785","https://openalex.org/W1991361881","https://openalex.org/W2011485235","https://openalex.org/W2063273127","https://openalex.org/W2074222846","https://openalex.org/W2105090634","https://openalex.org/W2531168480","https://openalex.org/W2560023338","https://openalex.org/W2587031013","https://openalex.org/W2589453516","https://openalex.org/W2595044712","https://openalex.org/W2630837129","https://openalex.org/W2783608381","https://openalex.org/W2890443177","https://openalex.org/W2953757725","https://openalex.org/W2961745803","https://openalex.org/W2963131120","https://openalex.org/W2976120863","https://openalex.org/W2981830988","https://openalex.org/W2984033187","https://openalex.org/W3000802654","https://openalex.org/W3006945815","https://openalex.org/W3009518842","https://openalex.org/W3080797347","https://openalex.org/W3082077183","https://openalex.org/W3095867871","https://openalex.org/W3174408035","https://openalex.org/W3175001099","https://openalex.org/W3183600011","https://openalex.org/W3193179900","https://openalex.org/W3194112386","https://openalex.org/W3205209293","https://openalex.org/W3206751403","https://openalex.org/W3209745495","https://openalex.org/W3212022090","https://openalex.org/W3217764757","https://openalex.org/W4200550577","https://openalex.org/W4206511152","https://openalex.org/W4220708699","https://openalex.org/W4220917101","https://openalex.org/W4226227310","https://openalex.org/W4283213578","https://openalex.org/W4285725870","https://openalex.org/W4295308209","https://openalex.org/W4321601151","https://openalex.org/W4385245566","https://openalex.org/W6739696289","https://openalex.org/W6765001775","https://openalex.org/W6796707148"],"related_works":["https://openalex.org/W2356597680","https://openalex.org/W2093471820","https://openalex.org/W50079190","https://openalex.org/W2114846443","https://openalex.org/W3102147106","https://openalex.org/W2347460059","https://openalex.org/W2111726165","https://openalex.org/W3136048405","https://openalex.org/W1984858032","https://openalex.org/W2088899772"],"abstract_inverted_index":{"Due":[0],"to":[1,58,63,91,109,118,132,150,185],"the":[2,12,103,111,126,144,159,187,197,223,227,245],"complex":[3,139],"and":[4,15,40,52,80,154,164,192,231,242],"highly":[5],"heterogeneous":[6],"land":[7,94,121,215],"cover":[8,95,122,216],"in":[9,97,134,138,234],"urban":[10,98],"areas,":[11],"single-temporal":[13],"pixel-wise":[14],"parcel-wise":[16],"classification":[17,96,137],"cannot":[18,169,206],"realize":[19,119,226],"high-precision":[20,93,214],"recognition":[21],"of":[22,27,48,115,161,174,190,199,210,229,236,247],"ground":[23,116],"objects.":[24],"Semantic":[25],"segmentation":[26,75,107],"satellite":[28],"image":[29],"time":[30,66,146],"series":[31,67],"(SITS),":[32],"can":[33,225],"distinguish":[34],"objects":[35,117],"with":[36],"similar":[37],"spectral":[38],"reflection":[39],"temporal":[41,181],"evolution.":[42],"But":[43],"optical":[44,79,191,232],"SITS":[45,233,248],"have":[46],"problems":[47],"uneven":[49],"time-frequency":[50],"distribution":[51],"incomplete,":[53],"which":[54,124,195],"makes":[55],"it":[56],"impossible":[57],"directly":[59],"use":[60,209],"existing":[61],"models":[62],"carry":[64],"out":[65],"semantic":[68,74,106,156],"segmentation.":[69],"This":[70],"study":[71],"proposes":[72],"a":[73,179],"network":[76],"that":[77,129,168,205,222],"combines":[78],"radar":[81,193,230],"SITS,":[82,194],"named":[83],"Multi-Source":[84],"Temporal":[85],"Attention":[86],"Fusion-Based":[87],"Temporal-Spatial":[88],"Transformer":[89,104,145],"(MTAF-TST),":[90],"achieve":[92],"areas.":[99],"Firstly,":[100],"MTAF-TST":[101,142,177,224],"uses":[102,143,178],"spatial":[105,112],"module":[108,149,184],"extract":[110],"context":[113],"information":[114],"pixel-level":[120],"classification,":[123],"relieves":[125],"salt-and-pepper":[127],"phenomenon":[128],"is":[130],"easy":[131],"occur":[133],"traditional":[135,162,200],"pixel-by-pixel":[136],"scenes.":[140],"Secondly,":[141],"feature":[147,202],"extraction":[148],"mine":[151,170],"long-range":[152,171],"time-dependent":[153,172],"high-level":[155],"information,":[157],"overcoming":[158],"drawbacks":[160],"convolutional":[163],"recurrent":[165],"neural":[166],"networks":[167],"features":[173,189],"SITS.":[175],"Finally,":[176],"multi-source":[180],"attention":[182],"fusion":[183],"fuse":[186],"depth":[188],"overcomes":[196],"shortcomings":[198],"direct":[201],"stitching":[203],"methods":[204],"make":[207],"full":[208],"time-correlated":[211],"features,":[212],"achieving":[213],"classification.":[217,249],"The":[218],"experimental":[219],"results":[220],"show":[221],"complementarity":[228],"terms":[235],"timing":[237],"integrity,":[238],"color,":[239],"texture,":[240],"etc.,":[241],"effectively":[243],"improve":[244],"accuracy":[246]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":2}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}
