{"id":"https://openalex.org/W7081915082","doi":"https://doi.org/10.1109/jstars.2025.3608777","title":"TerraDA: A Domain-Adaptive Framework With Dynamic Multimodal Remote Sensing Data Fusion and Consistency Learning for Cross-City Land Cover Classification","display_name":"TerraDA: A Domain-Adaptive Framework With Dynamic Multimodal Remote Sensing Data Fusion and Consistency Learning for Cross-City Land Cover Classification","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7081915082","doi":"https://doi.org/10.1109/jstars.2025.3608777"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2025.3608777","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3608777","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/jstars.2025.3608777","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Wenfu Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenfu Wu","raw_affiliation_strings":["College of Computer and Information Engineering, Henan University, Kaifeng, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer and Information Engineering, Henan University, Kaifeng, China","institution_ids":["https://openalex.org/I173899330"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yingchen Lyu","orcid":"https://orcid.org/0009-0004-4142-1589"},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingchen Lyu","raw_affiliation_strings":["School of Software, Henan University, Kaifeng, China"],"raw_orcid":"https://orcid.org/0009-0004-4142-1589","affiliations":[{"raw_affiliation_string":"School of Software, Henan University, Kaifeng, China","institution_ids":["https://openalex.org/I173899330"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wenkui Zheng","orcid":"https://orcid.org/0009-0008-8503-7289"},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenkui Zheng","raw_affiliation_strings":["School of Software, Henan University, Kaifeng, China"],"raw_orcid":"https://orcid.org/0009-0008-8503-7289","affiliations":[{"raw_affiliation_string":"School of Software, Henan University, Kaifeng, China","institution_ids":["https://openalex.org/I173899330"]}]},{"author_position":"last","author":{"id":null,"display_name":"Zhenfeng Shao","orcid":"https://orcid.org/0000-0003-4587-6826"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenfeng Shao","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0003-4587-6826","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.56543977,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":null,"first_page":"23189","last_page":"23209"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.6729999780654907,"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"}},"topics":[{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.6729999780654907,"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/T13067","display_name":"Geological Modeling and Analysis","score":0.026200000196695328,"subfield":{"id":"https://openalex.org/subfields/1906","display_name":"Geochemistry and Petrology"},"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/T14311","display_name":"Electrical and Electromagnetic Research","score":0.017500000074505806,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.6608999967575073},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46619999408721924},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.46070000529289246},{"id":"https://openalex.org/keywords/remote-sensing-application","display_name":"Remote sensing application","score":0.42879998683929443},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.4115999937057495},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.39800000190734863},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.39559999108314514},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.3887999951839447},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.3763999938964844}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7774999737739563},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6852999925613403},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.6608999967575073},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46619999408721924},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.46070000529289246},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4366999864578247},{"id":"https://openalex.org/C183365957","wikidata":"https://www.wikidata.org/wiki/Q17140402","display_name":"Remote sensing application","level":3,"score":0.42879998683929443},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.4115999937057495},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.39800000190734863},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.39559999108314514},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.3887999951839447},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3763999938964844},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.37459999322891235},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.362199991941452},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.3240000009536743},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.31049999594688416},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3059000074863434},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2985000014305115},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.2928999960422516},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2773999869823456},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.2745000123977661},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.2603999972343445},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2596000134944916},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.25940001010894775},{"id":"https://openalex.org/C104541649","wikidata":"https://www.wikidata.org/wiki/Q6935090","display_name":"Multispectral pattern recognition","level":3,"score":0.25929999351501465},{"id":"https://openalex.org/C39399123","wikidata":"https://www.wikidata.org/wiki/Q1348989","display_name":"Earth observation","level":3,"score":0.25450000166893005}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2025.3608777","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3608777","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c52094423aad440b9bdbf4088cd4813f","is_oa":true,"landing_page_url":"https://doaj.org/article/c52094423aad440b9bdbf4088cd4813f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 23189-23209 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2025.3608777","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3608777","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.7341553568840027,"display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G4645999178","display_name":null,"funder_award_id":"242102321155","funder_id":"https://openalex.org/F4320327051","funder_display_name":"Science and Technology Department of Henan Province"},{"id":"https://openalex.org/G7492304042","display_name":null,"funder_award_id":"42501537","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8831580691","display_name":null,"funder_award_id":"2024M760787","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320327051","display_name":"Science and Technology Department of Henan Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1981213426","https://openalex.org/W2006929658","https://openalex.org/W2077570405","https://openalex.org/W2170535121","https://openalex.org/W2469938794","https://openalex.org/W2616755213","https://openalex.org/W2752782242","https://openalex.org/W2760340275","https://openalex.org/W2764034829","https://openalex.org/W2774320778","https://openalex.org/W2783363232","https://openalex.org/W2803825432","https://openalex.org/W2902746003","https://openalex.org/W2916798096","https://openalex.org/W2964288524","https://openalex.org/W2969899502","https://openalex.org/W2989738275","https://openalex.org/W2990323597","https://openalex.org/W3003727719","https://openalex.org/W3040988483","https://openalex.org/W3048631361","https://openalex.org/W3090679658","https://openalex.org/W3112751649","https://openalex.org/W3138516171","https://openalex.org/W3188524028","https://openalex.org/W3209540366","https://openalex.org/W4200556575","https://openalex.org/W4214763222","https://openalex.org/W4220833120","https://openalex.org/W4229058281","https://openalex.org/W4281863163","https://openalex.org/W4283450732","https://openalex.org/W4312954132","https://openalex.org/W4377090452","https://openalex.org/W4388157208","https://openalex.org/W4392543906","https://openalex.org/W4402665270","https://openalex.org/W4406416235"],"related_works":[],"abstract_inverted_index":{"Land":[0],"cover":[1,26,72,183],"classification":[2],"plays":[3],"a":[4,63,85,94,127,141],"critical":[5],"role":[6],"in":[7,17,43,53,180],"urban":[8,30],"planning,":[9],"resource":[10],"management,":[11],"and":[12,49,93,112,140,154,166,178],"disaster":[13],"assessment.":[14],"Recent":[15],"advances":[16],"deep":[18],"learning":[19],"have":[20],"substantially":[21],"enhanced":[22],"remote":[23,44,69],"sensing-based":[24],"land":[25,71,182],"classification,":[27],"particularly":[28],"for":[29,66],"environments.":[31],"However,":[32],"cross-city":[33,67,181],"generalization":[34],"of":[35,107,164],"existing":[36],"models":[37],"is":[38],"constrained":[39],"by":[40],"distribution":[41],"shifts":[42],"sensing":[45,70],"data,":[46],"multimodal":[47,68,124],"heterogeneity,":[48],"scarce":[50],"semantic":[51],"annotations":[52],"target":[54],"cities.":[55],"To":[56],"address":[57],"these":[58],"challenges,":[59],"we":[60],"propose":[61],"TerraDA,":[62],"novel":[64],"framework":[65],"classification.":[73,184],"TerraDA":[74],"systematically":[75],"integrates":[76],"three":[77],"core":[78],"modules:":[79],"A":[80],"Fine-Grained":[81],"Attention-Modulated":[82],"Encoder":[83],"(FAME),":[84],"Multi-Scale":[86],"Dynamic":[87,95],"Gated":[88],"Feature":[89],"Fusion":[90],"Module":[91,98],"(MS-DGF),":[92],"Consistency-Adversarial":[96],"Adaptation":[97],"(DCAA).":[99],"Specifically,":[100],"FAME":[101],"enhances":[102],"the":[103,152],"modality-specific":[104],"feature":[105],"representations":[106],"hyperspectral":[108],"imaging,":[109,111],"multispectral":[110],"synthetic":[113],"aperture":[114],"radar":[115],"data":[116],"through":[117],"fine-grained":[118],"spatial":[119,134],"attention;":[120],"MS-DGF":[121],"adaptively":[122],"fuses":[123],"features":[125],"via":[126],"dynamic":[128,138],"gating":[129],"mechanism":[130],"while":[131],"capturing":[132],"multiscale":[133],"context;":[135],"DCAA":[136],"introduces":[137],"weighting":[139],"joint":[142],"consistency-adversarial":[143],"loss":[144],"to":[145],"robustly":[146],"align":[147],"cross-domain":[148],"features.":[149],"Experiments":[150],"on":[151],"C2Seg-AB":[153],"C2Seg-BW":[155],"datasets":[156],"demonstrate":[157],"TerraDA\u2019s":[158],"superior":[159],"performance,":[160],"achieving":[161],"mIoU/F1/OA/Kappa":[162],"scores":[163],"26.36/37.02/59.71/50.14%":[165],"11.66/17.64/38.45/29.06%,":[167],"respectively,":[168],"surpassing":[169],"state-of-the-art":[170],"methods,":[171],"including":[172],"SegNet,":[173],"PSPNet,":[174],"DeepLabV3+,":[175],"FastFCN,":[176],"SegFormer,":[177],"HighDAN,":[179]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
