{"id":"https://openalex.org/W4224920436","doi":"https://doi.org/10.3390/rs14030648","title":"Effectiveness of Semi-Supervised Learning and Multi-Source Data in Detailed Urban Landuse Mapping with a Few Labeled Samples","display_name":"Effectiveness of Semi-Supervised Learning and Multi-Source Data in Detailed Urban Landuse Mapping with a Few Labeled Samples","publication_year":2022,"publication_date":"2022-01-29","ids":{"openalex":"https://openalex.org/W4224920436","doi":"https://doi.org/10.3390/rs14030648"},"language":"en","primary_location":{"id":"doi:10.3390/rs14030648","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14030648","pdf_url":"https://www.mdpi.com/2072-4292/14/3/648/pdf?version=1644394326","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/14/3/648/pdf?version=1644394326","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009999617","display_name":"Bo Sun","orcid":"https://orcid.org/0000-0001-9860-0546"},"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/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Sun","raw_affiliation_strings":["Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China","institution_ids":["https://openalex.org/I4210145761","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100354653","display_name":"Yang Zhang","orcid":"https://orcid.org/0000-0002-2442-2916"},"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/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Zhang","raw_affiliation_strings":["Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China","institution_ids":["https://openalex.org/I4210145761","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085099069","display_name":"Qiming Zhou","orcid":"https://orcid.org/0000-0003-0934-0602"},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]},{"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/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN","HK"],"is_corresponding":true,"raw_author_name":"Qiming Zhou","raw_affiliation_strings":["Centre for Geocomputation Studies and Department of Geography, Hong Kong Baptist University, Kowloon, Hong Kong, China","Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China"],"raw_orcid":"https://orcid.org/0000-0003-0934-0602","affiliations":[{"raw_affiliation_string":"Centre for Geocomputation Studies and Department of Geography, Hong Kong Baptist University, Kowloon, Hong Kong, China","institution_ids":["https://openalex.org/I141568987"]},{"raw_affiliation_string":"Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China","institution_ids":["https://openalex.org/I4210145761","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037230519","display_name":"Xinchang Zhang","orcid":"https://orcid.org/0000-0001-8463-9757"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinchang Zhang","raw_affiliation_strings":["School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China"],"raw_orcid":"https://orcid.org/0000-0001-8463-9757","affiliations":[{"raw_affiliation_string":"School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China","institution_ids":["https://openalex.org/I37987034"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5085099069"],"corresponding_institution_ids":["https://openalex.org/I141568987","https://openalex.org/I19820366","https://openalex.org/I4210145761"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.9735,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.85564534,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"14","issue":"3","first_page":"648","last_page":"648"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10226","display_name":"Land Use and Ecosystem Services","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/T10226","display_name":"Land Use and Ecosystem Services","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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":0.9944999814033508,"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"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9934999942779541,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.682780921459198},{"id":"https://openalex.org/keywords/geospatial-analysis","display_name":"Geospatial analysis","score":0.6049200296401978},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5729122757911682},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5630499720573425},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.49997949600219727},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.38958531618118286},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3678134083747864},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34058693051338196},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.199873685836792}],"concepts":[{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.682780921459198},{"id":"https://openalex.org/C9770341","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geospatial analysis","level":2,"score":0.6049200296401978},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5729122757911682},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5630499720573425},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.49997949600219727},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.38958531618118286},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3678134083747864},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34058693051338196},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.199873685836792},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs14030648","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14030648","pdf_url":"https://www.mdpi.com/2072-4292/14/3/648/pdf?version=1644394326","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:95d44f0bdcd649078d78ce2f6304e81e","is_oa":true,"landing_page_url":"https://doaj.org/article/95d44f0bdcd649078d78ce2f6304e81e","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":"Remote Sensing, Vol 14, Iss 3, p 648 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/3/648/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14030648","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 14; Issue 3; Pages: 648","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs14030648","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14030648","pdf_url":"https://www.mdpi.com/2072-4292/14/3/648/pdf?version=1644394326","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.8199999928474426}],"awards":[{"id":"https://openalex.org/G5102604763","display_name":"\u4e2d\u4e9a\u5e72\u65f1\u533a\u9646\u5730\u6c34\u8d44\u6e90\u8bc4\u4f30\u53ca\u5176\u5bf9\u6c14\u5019\u53d8\u5316\u7684\u54cd\u5e94","funder_award_id":"41971386","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320320955","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322392","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549"},{"id":"https://openalex.org/F4320329174","display_name":"Shenzhen Municipal Science and Technology Innovation Council","ror":"https://ror.org/017n8df75"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4224920436.pdf","grobid_xml":"https://content.openalex.org/works/W4224920436.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W1968817125","https://openalex.org/W1972631516","https://openalex.org/W1996777760","https://openalex.org/W2008947716","https://openalex.org/W2010797227","https://openalex.org/W2019400799","https://openalex.org/W2048679005","https://openalex.org/W2051135580","https://openalex.org/W2059775642","https://openalex.org/W2063907334","https://openalex.org/W2085443648","https://openalex.org/W2114828048","https://openalex.org/W2152640741","https://openalex.org/W2153538582","https://openalex.org/W2534538876","https://openalex.org/W2613571842","https://openalex.org/W2748337466","https://openalex.org/W2771038928","https://openalex.org/W2791260466","https://openalex.org/W2791924394","https://openalex.org/W2793327769","https://openalex.org/W2888979938","https://openalex.org/W2902746003","https://openalex.org/W2911660248","https://openalex.org/W2955283378","https://openalex.org/W2964287450","https://openalex.org/W2990453078","https://openalex.org/W2993303109","https://openalex.org/W2996758582","https://openalex.org/W3007796610","https://openalex.org/W3010383195","https://openalex.org/W3011147769","https://openalex.org/W3013028075","https://openalex.org/W3014372673","https://openalex.org/W3022527331","https://openalex.org/W3034942609","https://openalex.org/W3072767238","https://openalex.org/W3116394266","https://openalex.org/W3163106223","https://openalex.org/W3185297562","https://openalex.org/W3197958969","https://openalex.org/W3216156171","https://openalex.org/W6779930420","https://openalex.org/W6801092314"],"related_works":["https://openalex.org/W4367313141","https://openalex.org/W2004086023","https://openalex.org/W2733999579","https://openalex.org/W2910751785","https://openalex.org/W2110217573","https://openalex.org/W4283374591","https://openalex.org/W4366547507","https://openalex.org/W4387891126","https://openalex.org/W4390100400","https://openalex.org/W2074396925"],"abstract_inverted_index":{"Detailed":[0],"urban":[1,29,67,102,157],"landuse":[2,30,41,68,103,154,158],"information":[3],"plays":[4],"a":[5,20,54,74,93,106,164,194,203],"fundamental":[6],"role":[7],"in":[8,24,57,160,220],"smart":[9],"city":[10],"management.":[11],"A":[12,110],"sufficient":[13],"sample":[14,205],"size":[15,76],"has":[16],"been":[17],"identified":[18],"as":[19,163],"very":[21,81],"crucial":[22],"pre-request":[23],"machine":[25],"learning":[26,113],"algorithms":[27],"for":[28,100],"classification.":[31],"However,":[32],"it":[33],"is":[34,51,234],"often":[35,71],"difficult":[36],"to":[37,88,192,210],"recognize":[38],"and":[39,60,119,128,137,142,150,186,251,267],"label":[40],"categories":[42],"from":[43],"remote":[44,140,254,270],"sensing":[45,141,255,271],"images":[46],"alone.":[47],"Alternatively,":[48],"field":[49],"investigation":[50],"time-consuming":[52],"with":[53,80,97,105,121,180,213,239],"high":[55],"demand":[56],"human":[58],"resources":[59],"monetary":[61],"cost.":[62],"Therefore,":[63],"previous":[64],"studies":[65],"on":[66,73,178,260],"classification":[69,95,104,159,170,228],"have":[70],"relied":[72],"small":[75,204],"of":[77,92,153,172,182],"labeled":[78,108,188],"samples":[79,189,215],"uneven":[82],"spatial":[83],"distribution.":[84],"This":[85],"study":[86],"aims":[87],"explore":[89],"the":[90,115,148,169,173,207,227,261],"effectiveness":[91],"semi-supervised":[94,112,174],"framework":[96],"multi-source":[98,232],"data":[99,132,233,242,256,266],"detailed":[101],"few":[107],"samples.":[109],"disagreement-based":[111],"approach,":[114],"Co-Forest,":[116],"was":[117],"employed":[118],"compared":[120],"traditional":[122,183],"supervised":[123,184],"methods":[124],"(e.g.,":[125],"random":[126],"forest":[127],"XGBoost).":[129],"Multi-source":[130],"geospatial":[131,143],"were":[133],"utilized":[134],"including":[135],"optical":[136,253],"nighttime":[138,268],"light":[139,269],"big":[144],"data,":[145,248],"which":[146],"present":[147],"physical":[149],"socio-economic":[151],"features":[152],"categories.":[155],"Taking":[156],"Shenzhen":[161],"City":[162],"case,":[165],"results":[166,223],"show":[167],"that":[168,181,226,238],"accuracy":[171,208,229],"method":[175],"are":[176,190],"generally":[177],"par":[179],"methods,":[185],"less":[187,217],"needed":[191],"achieve":[193],"comparable":[195],"result":[196],"under":[197],"different":[198],"training":[199,214],"set":[200],"ratios.":[201],"Given":[202],"size,":[206],"tends":[209],"be":[211],"stable":[212],"no":[216],"than":[218,237],"5%":[219],"total.":[221],"Our":[222],"also":[224],"indicate":[225],"by":[230,264],"using":[231],"significantly":[235],"higher":[236],"any":[240],"single":[241],"source":[243],"being":[244],"applied.":[245],"Among":[246],"these":[247],"map":[249],"POI":[250],"high-resolution":[252],"make":[257],"larger":[258],"contributions":[259],"classification,":[262],"followed":[263],"mobile":[265],"data.":[272]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}