{"id":"https://openalex.org/W4308063232","doi":"https://doi.org/10.1109/igarss46834.2022.9884094","title":"Unsupervised Domain Adaptation Methods for Land Cover Mapping with Optical Satellite Image Time Series","display_name":"Unsupervised Domain Adaptation Methods for Land Cover Mapping with Optical Satellite Image Time Series","publication_year":2022,"publication_date":"2022-07-17","ids":{"openalex":"https://openalex.org/W4308063232","doi":"https://doi.org/10.1109/igarss46834.2022.9884094"},"language":"en","primary_location":{"id":"doi:10.1109/igarss46834.2022.9884094","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9884094","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 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/A5022455368","display_name":"E. Capliez","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136436","display_name":"Institut Agro Montpelier","ror":null,"country_code":"FR","type":null,"lineage":["https://openalex.org/I4210136436"]},{"id":"https://openalex.org/I19894307","display_name":"Universit\u00e9 de Montpellier","ror":"https://ror.org/051escj72","country_code":"FR","type":"education","lineage":["https://openalex.org/I19894307"]},{"id":"https://openalex.org/I112991645","display_name":"Airbus (France)","ror":"https://ror.org/023qdcg29","country_code":"FR","type":"company","lineage":["https://openalex.org/I112991645","https://openalex.org/I4210121748"]},{"id":"https://openalex.org/I4210088668","display_name":"Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement","ror":"https://ror.org/003vg9w96","country_code":"FR","type":"funder","lineage":["https://openalex.org/I4210088668"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"E. Capliez","raw_affiliation_strings":["INRAE, UMR TETIS, Univ. Montpellier,France","Airbus Defence and Space, Toulouse, France","INRAE, UMR TETIS, Univ. Montpellier, France"],"affiliations":[{"raw_affiliation_string":"INRAE, UMR TETIS, Univ. Montpellier,France","institution_ids":["https://openalex.org/I4210136436","https://openalex.org/I19894307","https://openalex.org/I4210088668"]},{"raw_affiliation_string":"Airbus Defence and Space, Toulouse, France","institution_ids":["https://openalex.org/I112991645"]},{"raw_affiliation_string":"INRAE, UMR TETIS, Univ. Montpellier, France","institution_ids":["https://openalex.org/I4210088668","https://openalex.org/I19894307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018231294","display_name":"Dino Ienco","orcid":"https://orcid.org/0000-0002-8736-3132"},"institutions":[{"id":"https://openalex.org/I4210136436","display_name":"Institut Agro Montpelier","ror":null,"country_code":"FR","type":null,"lineage":["https://openalex.org/I4210136436"]},{"id":"https://openalex.org/I4210088668","display_name":"Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement","ror":"https://ror.org/003vg9w96","country_code":"FR","type":"funder","lineage":["https://openalex.org/I4210088668"]},{"id":"https://openalex.org/I19894307","display_name":"Universit\u00e9 de Montpellier","ror":"https://ror.org/051escj72","country_code":"FR","type":"education","lineage":["https://openalex.org/I19894307"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"D. Ienco","raw_affiliation_strings":["INRAE, UMR TETIS, Univ. Montpellier,France","INRAE, UMR TETIS, Univ. Montpellier, France"],"affiliations":[{"raw_affiliation_string":"INRAE, UMR TETIS, Univ. Montpellier,France","institution_ids":["https://openalex.org/I4210136436","https://openalex.org/I19894307","https://openalex.org/I4210088668"]},{"raw_affiliation_string":"INRAE, UMR TETIS, Univ. Montpellier, France","institution_ids":["https://openalex.org/I4210088668","https://openalex.org/I19894307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068424399","display_name":"Raffaele Gaetano","orcid":"https://orcid.org/0000-0002-9470-4791"},"institutions":[{"id":"https://openalex.org/I131077856","display_name":"Centre de Coop\u00e9ration Internationale en Recherche Agronomique pour le D\u00e9veloppement","ror":"https://ror.org/05kpkpg04","country_code":"FR","type":"facility","lineage":["https://openalex.org/I131077856"]},{"id":"https://openalex.org/I19894307","display_name":"Universit\u00e9 de Montpellier","ror":"https://ror.org/051escj72","country_code":"FR","type":"education","lineage":["https://openalex.org/I19894307"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"R. Gaetano","raw_affiliation_strings":["CIRAD, UMR TETIS, Univ. Montpellier,France","CIRAD, UMR TETIS, Univ. Montpellier, France"],"affiliations":[{"raw_affiliation_string":"CIRAD, UMR TETIS, Univ. Montpellier,France","institution_ids":["https://openalex.org/I131077856","https://openalex.org/I19894307"]},{"raw_affiliation_string":"CIRAD, UMR TETIS, Univ. Montpellier, France","institution_ids":["https://openalex.org/I131077856","https://openalex.org/I19894307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005595654","display_name":"Nicolas Baghdadi","orcid":"https://orcid.org/0000-0002-9461-4120"},"institutions":[{"id":"https://openalex.org/I19894307","display_name":"Universit\u00e9 de Montpellier","ror":"https://ror.org/051escj72","country_code":"FR","type":"education","lineage":["https://openalex.org/I19894307"]},{"id":"https://openalex.org/I4210088668","display_name":"Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement","ror":"https://ror.org/003vg9w96","country_code":"FR","type":"funder","lineage":["https://openalex.org/I4210088668"]},{"id":"https://openalex.org/I4210136436","display_name":"Institut Agro Montpelier","ror":null,"country_code":"FR","type":null,"lineage":["https://openalex.org/I4210136436"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"N. Baghdadi","raw_affiliation_strings":["INRAE, UMR TETIS, Univ. Montpellier,France","INRAE, UMR TETIS, Univ. Montpellier, France"],"affiliations":[{"raw_affiliation_string":"INRAE, UMR TETIS, Univ. Montpellier,France","institution_ids":["https://openalex.org/I4210136436","https://openalex.org/I19894307","https://openalex.org/I4210088668"]},{"raw_affiliation_string":"INRAE, UMR TETIS, Univ. Montpellier, France","institution_ids":["https://openalex.org/I4210088668","https://openalex.org/I19894307"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009756079","display_name":"Adrien Hadj Salah","orcid":null},"institutions":[{"id":"https://openalex.org/I112991645","display_name":"Airbus (France)","ror":"https://ror.org/023qdcg29","country_code":"FR","type":"company","lineage":["https://openalex.org/I112991645","https://openalex.org/I4210121748"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"A. Hadj Salah","raw_affiliation_strings":["Airbus Defence and Space,Toulouse,France","Airbus Defence and Space, Toulouse, France"],"affiliations":[{"raw_affiliation_string":"Airbus Defence and Space,Toulouse,France","institution_ids":["https://openalex.org/I112991645"]},{"raw_affiliation_string":"Airbus Defence and Space, Toulouse, France","institution_ids":["https://openalex.org/I112991645"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5022455368"],"corresponding_institution_ids":["https://openalex.org/I112991645","https://openalex.org/I19894307","https://openalex.org/I4210088668","https://openalex.org/I4210136436"],"apc_list":null,"apc_paid":null,"fwci":1.4537,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.7968094,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"11","issue":null,"first_page":"275","last_page":"278"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.991100013256073,"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"}},"topics":[{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.991100013256073,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9898999929428101,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9717000126838684,"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":0.71727454662323},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6316624283790588},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5963704586029053},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.5941120982170105},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5762648582458496},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.574264645576477},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.481008380651474},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47442808747291565},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.45890799164772034},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4412746727466583},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.43146488070487976},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3812897503376007},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.338573694229126},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1998148262500763},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.17266049981117249},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10799485445022583}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.71727454662323},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6316624283790588},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5963704586029053},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.5941120982170105},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5762648582458496},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.574264645576477},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.481008380651474},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47442808747291565},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.45890799164772034},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4412746727466583},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.43146488070487976},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3812897503376007},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.338573694229126},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1998148262500763},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.17266049981117249},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10799485445022583},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/igarss46834.2022.9884094","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9884094","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:agritrop.cirad.fr:607079","is_oa":false,"landing_page_url":"http://agritrop.cirad.fr/607079/","pdf_url":null,"source":{"id":"https://openalex.org/S4306402311","display_name":"Agritrop (Cirad)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I131077856","host_organization_name":"Centre de Coop\u00e9ration Internationale en Recherche Agronomique pour le D\u00e9veloppement","host_organization_lineage":["https://openalex.org/I131077856"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:HAL:hal-03836642v1","is_oa":false,"landing_page_url":"https://hal.inrae.fr/hal-03836642","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Jul 2022, Kuala Lumpur, Malaysia. pp.275-278, &#x27E8;10.1109/IGARSS46834.2022.9884094&#x27E9;","raw_type":"Conference papers"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Zero hunger","score":0.5600000023841858,"id":"https://metadata.un.org/sdg/2"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1731081199","https://openalex.org/W2149466042","https://openalex.org/W2176673053","https://openalex.org/W2307094448","https://openalex.org/W2593768305","https://openalex.org/W2767524800","https://openalex.org/W2963131120","https://openalex.org/W2976120863","https://openalex.org/W2979509742","https://openalex.org/W3080108946","https://openalex.org/W3129582811","https://openalex.org/W6637618735","https://openalex.org/W6681637710"],"related_works":["https://openalex.org/W4295532600","https://openalex.org/W2063823869","https://openalex.org/W2047973478","https://openalex.org/W2067569035","https://openalex.org/W2090985514","https://openalex.org/W2997567050","https://openalex.org/W2113666009","https://openalex.org/W3201126466","https://openalex.org/W2145649715","https://openalex.org/W2020734820"],"abstract_inverted_index":{"Nowadays,":[0],"Satellite":[1],"Image":[2],"Time":[3],"Series":[4],"(SITS)":[5],"are":[6,49,144],"employed":[7],"as":[8],"input":[9],"to":[10,16,40,58,69,81,117,158],"derive":[11],"land":[12],"cover":[13],"maps":[14],"(LCM)":[15],"support":[17],"decision":[18],"makers":[19],"in":[20,103,217],"several":[21],"application":[22],"domains":[23],"like":[24],"agriculture":[25],"and":[26,177],"biodiversity.":[27],"The":[28,114,146],"generation":[29],"of":[30,72,96,107,163,187,196,203],"LCM":[31],"largely":[32],"relies":[33],"on":[34,63,136,173,180],"available":[35,127],"ground":[36],"truth":[37],"(GT)":[38],"data":[39,48,176,182],"calibrate":[41],"supervised":[42],"ma-chine":[43],"learning":[44,110,166],"models.":[45],"Unfortunately,":[46],"this":[47,54,89],"not":[50],"always":[51],"accessible.":[52,145],"In":[53,88],"scenario,":[55],"the":[56,84,104,161,174,189],"possibility":[57],"transfer":[59,109,132,165],"a":[60,64,78,119,123,134,137,154,170],"model":[61,121,135,171],"learnt":[62,172],"particular":[65],"year":[66,125,139],"(source":[67],"domain)":[68,75],"another":[70],"period":[71],"time":[73],"(target":[74],"could":[76],"be":[77,215],"valuable":[79],"tool":[80],"deal":[82],"with":[83,160,198],"previously":[85],"mentioned":[86],"restrictions.":[87],"paper,":[90],"we":[91],"provide":[92],"an":[93,184,194],"experimental":[94],"evaluation":[95],"recent":[97],"Unsupervised":[98],"Domain":[99],"Adaptation":[100],"(UDA)":[101],"methods":[102,152],"specific":[105],"context":[106],"temporal":[108,164],"for":[111,167,211],"SITS-based":[112],"LCM.":[113,168],"objective":[115],"is":[116,208],"learn":[118],"classification":[120],"at":[122],"certain":[124],"(exploiting":[126],"GT":[128],"data)":[129],"and,":[130],"successively,":[131],"such":[133],"subsequent":[138],"where":[140],"no":[141],"labelled":[142],"samples":[143],"obtained":[147],"findings":[148],"reveal":[149],"that":[150,213],"UDA":[151,191],"represent":[153],"promising":[155],"research":[156],"direction":[157],"cope":[159],"problem":[162],"While":[169],"source":[175],"directly":[178],"applied":[179],"target":[181],"achieves":[183],"weighted":[185],"F1-score":[186,195],"67.1,":[188],"best":[190],"method":[192],"obtains":[193],"83.7":[197],"more":[199],"than":[200],"15":[201],"points":[202],"positive":[204],"gap.":[205],"Nevertheless,":[206],"there":[207],"still":[209],"room":[210],"improvement":[212],"should":[214],"explored":[216],"future":[218],"works.":[219]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
