{"id":"https://openalex.org/W3154461244","doi":"https://doi.org/10.1109/tgrs.2021.3068280","title":"High-Resolution Land Cover Mapping Through Learning With Noise Correction","display_name":"High-Resolution Land Cover Mapping Through Learning With Noise Correction","publication_year":2021,"publication_date":"2021-04-09","ids":{"openalex":"https://openalex.org/W3154461244","doi":"https://doi.org/10.1109/tgrs.2021.3068280","mag":"3154461244"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2021.3068280","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3068280","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/A5068349823","display_name":"Runmin Dong","orcid":"https://orcid.org/0000-0002-2999-2029"},"institutions":[{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]},{"id":"https://openalex.org/I4401727009","display_name":"Sensetime (China)","ror":"https://ror.org/049wsmj07","country_code":"CN","type":"company","lineage":["https://openalex.org/I4401727009"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runmin Dong","raw_affiliation_strings":["Department of Earth System Science, Tsinghua University, Beijing, China","SenseTime Group Ltd, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2999-2029","affiliations":[{"raw_affiliation_string":"Department of Earth System Science, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"SenseTime Group Ltd, Beijing, China","institution_ids":["https://openalex.org/I4210128910","https://openalex.org/I4401727009"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102895369","display_name":"Weizhen Fang","orcid":"https://orcid.org/0000-0003-0155-012X"},"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/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weizhen Fang","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0155-012X","affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031545295","display_name":"Haohuan Fu","orcid":"https://orcid.org/0000-0002-6982-2235"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haohuan Fu","raw_affiliation_strings":["Department of Earth System Science, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6982-2235","affiliations":[{"raw_affiliation_string":"Department of Earth System Science, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038750675","display_name":"Lin Gan","orcid":"https://orcid.org/0000-0003-1297-4462"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Gan","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1297-4462","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100440145","display_name":"Jie Wang","orcid":"https://orcid.org/0000-0002-9663-3165"},"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/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"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Wang","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366","https://openalex.org/I4210166112"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059264917","display_name":"Peng Gong","orcid":"https://orcid.org/0000-0003-1513-3765"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Gong","raw_affiliation_strings":["Department of Earth System Science, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Earth System Science, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.0399,"has_fulltext":false,"cited_by_count":48,"citation_normalized_percentile":{"value":0.91729841,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9980000257492065,"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":0.9980000257492065,"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":0.9958000183105469,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.964900016784668,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.80925452709198},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6836905479431152},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.565418004989624},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5652663707733154},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.5623435974121094},{"id":"https://openalex.org/keywords/cover","display_name":"Cover (algebra)","score":0.5223456621170044},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5176025629043579},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.48348313570022583},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4541378617286682},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4508225917816162},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4209159314632416},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.4189664125442505},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4174245595932007},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39632347226142883},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.15498876571655273}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.80925452709198},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6836905479431152},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.565418004989624},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5652663707733154},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.5623435974121094},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.5223456621170044},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5176025629043579},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.48348313570022583},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4541378617286682},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4508225917816162},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4209159314632416},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.4189664125442505},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4174245595932007},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39632347226142883},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.15498876571655273},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2021.3068280","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3068280","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":[{"id":"https://metadata.un.org/sdg/15","score":0.5600000023841858,"display_name":"Life in Land"}],"awards":[{"id":"https://openalex.org/G4420523167","display_name":null,"funder_award_id":"2017YFA0604401","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6040666115","display_name":null,"funder_award_id":"2017YFB0202204","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7321677127","display_name":null,"funder_award_id":"2017YFA0604500","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8368203158","display_name":null,"funder_award_id":"U1839206","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G914177327","display_name":null,"funder_award_id":"2020YFB0204700","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1836465849","https://openalex.org/W1866072925","https://openalex.org/W1901129140","https://openalex.org/W1975128126","https://openalex.org/W1985864794","https://openalex.org/W2001510610","https://openalex.org/W2118246710","https://openalex.org/W2161236525","https://openalex.org/W2167460663","https://openalex.org/W2256456552","https://openalex.org/W2312198368","https://openalex.org/W2412782625","https://openalex.org/W2470948946","https://openalex.org/W2502312327","https://openalex.org/W2538244214","https://openalex.org/W2546735785","https://openalex.org/W2559597482","https://openalex.org/W2618574054","https://openalex.org/W2737129951","https://openalex.org/W2885139206","https://openalex.org/W2891256940","https://openalex.org/W2895694115","https://openalex.org/W2916798096","https://openalex.org/W2920254659","https://openalex.org/W2935128472","https://openalex.org/W2940726923","https://openalex.org/W2962762068","https://openalex.org/W2963697299","https://openalex.org/W2964274690","https://openalex.org/W2967052791","https://openalex.org/W2969012750","https://openalex.org/W2973660294","https://openalex.org/W2979901318","https://openalex.org/W2981508914","https://openalex.org/W2981873476","https://openalex.org/W2982507557","https://openalex.org/W2982631194","https://openalex.org/W2988966271","https://openalex.org/W2991488782","https://openalex.org/W3011578373","https://openalex.org/W3021167903","https://openalex.org/W3035600434","https://openalex.org/W3047067521","https://openalex.org/W3132186014","https://openalex.org/W3156669901","https://openalex.org/W6638667902","https://openalex.org/W6639331287","https://openalex.org/W6724804524","https://openalex.org/W6737985840","https://openalex.org/W6751420435","https://openalex.org/W6757459799","https://openalex.org/W6761549460"],"related_works":["https://openalex.org/W3108403339","https://openalex.org/W2162712524","https://openalex.org/W2023005931","https://openalex.org/W2142924612","https://openalex.org/W4287867034","https://openalex.org/W3005783148","https://openalex.org/W4312518509","https://openalex.org/W383418545","https://openalex.org/W4367628250","https://openalex.org/W2004821155"],"abstract_inverted_index":{"High-resolution":[0],"land":[1,33,164],"cover":[2,34,165],"mapping":[3],"over":[4],"large":[5],"areas":[6],"is":[7,21],"a":[8,77,84,95,125,160,168],"challenging":[9],"task":[10],"due":[11],"to":[12,22,48,97,109,181,196],"the":[13,24,29,37,45,54,57,63,68,73,91,99,103,114,122,136,142,155,176],"lack":[14],"of":[15,44,56,113],"high-quality":[16],"labels.":[17,131],"A":[18],"potential":[19,198],"solution":[20],"leverage":[23],"existing":[25,204],"knowledge":[26,205],"contained":[27],"in":[28,172],"freely":[30],"available":[31],"lower-resolution":[32,169],"products.":[35],"However,":[36],"relatively":[38],"low":[39,42],"resolution":[40],"and":[41,71,83,119,145,174,202,206],"accuracy":[43,177],"products":[46],"lead":[47],"numerous":[49],"inaccurate":[50],"labels,":[51,102],"which":[52],"harms":[53],"performance":[55,123],"neural":[58],"network.":[59],"This":[60],"article":[61],"addresses":[62],"challenge":[64],"by":[65],"jointly":[66],"optimizing":[67],"network":[69,151],"parameters":[70],"correcting":[72],"noisy":[74,115,130,143,192],"labels":[75,116,144],"with":[76,124],"novel":[78],"online":[79],"noise":[80,86,105],"correction":[81,87,106,112],"approach":[82,107,186],"synergistic":[85],"loss.":[88],"By":[89,153],"incorporating":[90],"information":[92],"entropy":[93],"as":[94],"measurement":[96],"determine":[98],"probable":[100],"correct":[101,141],"proposed":[104,137,156],"learns":[108],"make":[110],"effective":[111],"during":[117],"training":[118,126],"eventually":[120],"boosts":[121],"set":[127],"containing":[128],"less":[129],"Experimental":[132],"results":[133],"show":[134],"that":[135,187],"method":[138],"can":[139,188],"effectively":[140,189],"reduce":[146],"their":[147],"negative":[148],"impact":[149],"on":[150],"training.":[152],"employing":[154],"method,":[157],"we":[158],"produce":[159],"refined":[161],"high-resolution":[162],"(3-m)":[163],"map":[166],"from":[167,178,191],"(10-m)":[170,180],"product":[171],"China":[173],"improve":[175],"74.96%":[179],"81.32%":[182],"(3-m).":[183],"Such":[184],"an":[185],"learn":[190],"data":[193],"sets":[194],"leads":[195],"many":[197],"opportunities":[199],"for":[200],"using":[201],"magnifying":[203],"results.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}