{"id":"https://openalex.org/W4411408457","doi":"https://doi.org/10.1109/tgrs.2025.3580895","title":"Thick Cloud Removal of Landsat Time-Series Using Convolutional LSTM With Embedded Residual Modules","display_name":"Thick Cloud Removal of Landsat Time-Series Using Convolutional LSTM With Embedded Residual Modules","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4411408457","doi":"https://doi.org/10.1109/tgrs.2025.3580895"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2025.3580895","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3580895","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":true,"oa_status":"green","oa_url":"https://eprints.lancs.ac.uk/id/eprint/230718/1/Res-cLSTM_TGRS2_final.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063000248","display_name":"Lanxing Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lanxing Wang","raw_affiliation_strings":["College of Surveying and Geo-Informatics, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0004-0845-6456","affiliations":[{"raw_affiliation_string":"College of Surveying and Geo-Informatics, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005729523","display_name":"Qunming Wang","orcid":"https://orcid.org/0000-0002-5188-0939"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qunming Wang","raw_affiliation_strings":["College of Surveying and Geo-Informatics, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-5188-0939","affiliations":[{"raw_affiliation_string":"College of Surveying and Geo-Informatics, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000622487","display_name":"Peter M. Atkinson","orcid":"https://orcid.org/0000-0002-5489-6880"},"institutions":[{"id":"https://openalex.org/I67415387","display_name":"Lancaster University","ror":"https://ror.org/04f2nsd36","country_code":"GB","type":"education","lineage":["https://openalex.org/I67415387"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Peter M. Atkinson","raw_affiliation_strings":["Faculty of Science and Technology, Lancaster University, Lancaster, U.K","Faculty of Science and Technology, Lancaster University, Lancaster, UK"],"raw_orcid":"https://orcid.org/0000-0002-5489-6880","affiliations":[{"raw_affiliation_string":"Faculty of Science and Technology, Lancaster University, Lancaster, U.K","institution_ids":["https://openalex.org/I67415387"]},{"raw_affiliation_string":"Faculty of Science and Technology, Lancaster University, Lancaster, UK","institution_ids":["https://openalex.org/I67415387"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1002,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.85997923,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9168000221252441,"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":0.9168000221252441,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.8371548056602478},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6745374202728271},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6621323823928833},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6394817233085632},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.6288043856620789},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5606597661972046},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4212658107280731},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3480703830718994},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.2509072422981262},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2438206970691681},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.13279619812965393}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.8371548056602478},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6745374202728271},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6621323823928833},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6394817233085632},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6288043856620789},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5606597661972046},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4212658107280731},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3480703830718994},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.2509072422981262},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2438206970691681},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.13279619812965393},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2025.3580895","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3580895","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"},{"id":"pmh:oai:eprints.lancs.ac.uk:230718","is_oa":true,"landing_page_url":null,"pdf_url":"https://eprints.lancs.ac.uk/id/eprint/230718/1/Res-cLSTM_TGRS2_final.pdf","source":{"id":"https://openalex.org/S4306401916","display_name":"Lancaster EPrints (Lancaster University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67415387","host_organization_name":"Lancaster University","host_organization_lineage":["https://openalex.org/I67415387"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal Article"}],"best_oa_location":{"id":"pmh:oai:eprints.lancs.ac.uk:230718","is_oa":true,"landing_page_url":null,"pdf_url":"https://eprints.lancs.ac.uk/id/eprint/230718/1/Res-cLSTM_TGRS2_final.pdf","source":{"id":"https://openalex.org/S4306401916","display_name":"Lancaster EPrints (Lancaster University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67415387","host_organization_name":"Lancaster University","host_organization_lineage":["https://openalex.org/I67415387"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal Article"},"sustainable_development_goals":[{"score":0.47999998927116394,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G1993716853","display_name":null,"funder_award_id":"42222108","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8971197728","display_name":null,"funder_award_id":"42171345","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411408457.pdf","grobid_xml":"https://content.openalex.org/works/W4411408457.grobid-xml"},"referenced_works_count":61,"referenced_works":["https://openalex.org/W1968378717","https://openalex.org/W1982121855","https://openalex.org/W2028191110","https://openalex.org/W2149676023","https://openalex.org/W2194775991","https://openalex.org/W2776526448","https://openalex.org/W2895942690","https://openalex.org/W2905637703","https://openalex.org/W2908512565","https://openalex.org/W2997860833","https://openalex.org/W3038579873","https://openalex.org/W3041334470","https://openalex.org/W3080368312","https://openalex.org/W3096720627","https://openalex.org/W3115007495","https://openalex.org/W3134373832","https://openalex.org/W3153500217","https://openalex.org/W3163222380","https://openalex.org/W3165549846","https://openalex.org/W3194927568","https://openalex.org/W3210002208","https://openalex.org/W3210579416","https://openalex.org/W3215865232","https://openalex.org/W4206822653","https://openalex.org/W4226039856","https://openalex.org/W4226074214","https://openalex.org/W4226181542","https://openalex.org/W4285198998","https://openalex.org/W4292702164","https://openalex.org/W4293876741","https://openalex.org/W4296916599","https://openalex.org/W4313270591","https://openalex.org/W4318954132","https://openalex.org/W4319166471","https://openalex.org/W4366132032","https://openalex.org/W4376851534","https://openalex.org/W4385627111","https://openalex.org/W4387763069","https://openalex.org/W4390242405","https://openalex.org/W4391235300","https://openalex.org/W4391425208","https://openalex.org/W4392806026","https://openalex.org/W4392940059","https://openalex.org/W4396680444","https://openalex.org/W4396712951","https://openalex.org/W4399169053","https://openalex.org/W4399686814","https://openalex.org/W4400646831","https://openalex.org/W4400877979","https://openalex.org/W4401317708","https://openalex.org/W4401392834","https://openalex.org/W4402623744","https://openalex.org/W4402900220","https://openalex.org/W4403183158","https://openalex.org/W4403480146","https://openalex.org/W4403674927","https://openalex.org/W4404093718","https://openalex.org/W4404441138","https://openalex.org/W4404741820","https://openalex.org/W4407407958","https://openalex.org/W6628877408"],"related_works":["https://openalex.org/W4244478748","https://openalex.org/W3150465815","https://openalex.org/W4223488648","https://openalex.org/W2134969820","https://openalex.org/W2251605416","https://openalex.org/W1997222214","https://openalex.org/W2119012848","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"Extensive":[0],"cloud":[1,13,124,143,224,232],"contamination":[2],"severely":[3],"hinders":[4],"the":[5,19,29,51,60,95,105,118,161,169,173,186,211,215],"interpretation":[6],"of":[7,21,31,160,164,172,185,204,218],"optical":[8],"remote":[9],"sensing":[10],"images.":[11,34,78],"Existing":[12],"removal":[14,125,144],"methods":[15,37],"focus":[16],"primarily":[17],"on":[18,127],"reconstruction":[20,30,159],"individual":[22],"cloudy":[23,32,52,62,76,162,167,219],"images,":[24],"with":[25,113],"few":[26],"studies":[27],"addressing":[28],"time-series":[33,77,81,131,163,220],"Furthermore,":[35],"current":[36],"tend":[38],"to":[39,59,74,93,222,230],"prioritize":[40],"using":[41,84,108],"cloud-free":[42],"auxiliary":[43,53],"images":[44,54,82,221],"while":[45],"overlooking":[46],"valuable":[47,212],"information":[48,213],"present":[49],"in":[50,117,214],"that":[55,138,184],"are":[56],"temporally":[57],"closer":[58],"target":[61],"image.":[63],"In":[64],"this":[65],"paper,":[66],"we":[67],"proposed":[68],"a":[69,109,195,236],"deep":[70],"network":[71],"called":[72],"Res-cLSTM":[73,79,102,139,174,198,227],"reconstruct":[75],"processes":[80],"sequentially":[83],"convolutional":[85],"LSTM,":[86],"synthesizing":[87],"long-":[88],"and":[89,122,180,207,234],"short-term":[90],"memory":[91],"streams":[92],"match":[94],"complex":[96],"temporal":[97],"relationships":[98],"amongst":[99],"them.":[100],"Then,":[101],"further":[103],"decodes":[104],"feature":[106],"maps":[107],"refined":[110],"residual":[111],"module":[112],"skip":[114],"connections,":[115],"resulting":[116],"final":[119],"output.":[120],"Simulated":[121],"real":[123],"experiments":[126],"Landsat":[128],"8":[129],"OLI":[130],"data":[132,206],"across":[133],"five":[134],"different":[135],"regions":[136,217],"demonstrated":[137],"is":[140,176],"an":[141],"effective":[142],"method,":[145],"which":[146],"can":[147,208],"produce":[148],"more":[149],"accurate":[150,189],"predictions":[151],"than":[152,183],"three":[153,165],"benchmark":[154],"approaches.":[155],"For":[156],"example,":[157],"for":[158,244],"simulated":[166],"areas,":[168],"average":[170],"CC":[171],"prediction":[175],"about":[177],"0.01,":[178],"0.04":[179,181],"larger":[182],"second":[187],"most":[188],"method":[190],"(i.e.,":[191],"autoencoder":[192],"(AE)).":[193],"As":[194],"lightweight":[196],"network,":[197],"does":[199],"not":[200],"require":[201],"global":[202],"sampling":[203],"training":[205],"fully":[209],"exploit":[210],"non-cloud":[216],"facilitate":[223],"removal.":[225],"Moreover,":[226],"demonstrates":[228],"robustness":[229],"thin":[231],"omission":[233],"exhibits":[235],"faster":[237],"convergence":[238],"rate,":[239],"thus,":[240],"holds":[241],"great":[242],"potential":[243],"practical":[245],"applications":[246],"requiring":[247],"real-time":[248],"processing.":[249]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}