{"id":"https://openalex.org/W2899315938","doi":"https://doi.org/10.3390/s18113717","title":"Urban Land Use and Land Cover Classification Using Novel Deep Learning Models Based on High Spatial Resolution Satellite Imagery","display_name":"Urban Land Use and Land Cover Classification Using Novel Deep Learning Models Based on High Spatial Resolution Satellite Imagery","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2899315938","doi":"https://doi.org/10.3390/s18113717","mag":"2899315938","pmid":"https://pubmed.ncbi.nlm.nih.gov/30388781"},"language":"en","primary_location":{"id":"doi:10.3390/s18113717","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s18113717","pdf_url":"https://www.mdpi.com/1424-8220/18/11/3717/pdf?version=1541058133","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/18/11/3717/pdf?version=1541058133","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072009924","display_name":"Pengbin Zhang","orcid":"https://orcid.org/0000-0002-1228-2821"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengbin Zhang","raw_affiliation_strings":["EarthSTAR Inc., Beijing 100101, China","Laboratory Cultivation Base of Environment Process and Digital Simulation, Capital Normal University, Beijing 100048, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EarthSTAR Inc., Beijing 100101, China","institution_ids":[]},{"raw_affiliation_string":"Laboratory Cultivation Base of Environment Process and Digital Simulation, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089180563","display_name":"Yinghai Ke","orcid":"https://orcid.org/0000-0002-1121-1378"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yinghai Ke","raw_affiliation_strings":["Beijing Laboratory of Water Resource Security, Capital Normal University, Beijing 100048, China","Laboratory Cultivation Base of Environment Process and Digital Simulation, Capital Normal University, Beijing 100048, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Laboratory of Water Resource Security, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"Laboratory Cultivation Base of Environment Process and Digital Simulation, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101584424","display_name":"Zhenxin Zhang","orcid":"https://orcid.org/0000-0002-4070-9415"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhenxin Zhang","raw_affiliation_strings":["Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing 100048, China","Laboratory Cultivation Base of Environment Process and Digital Simulation, Capital Normal University, Beijing 100048, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"Laboratory Cultivation Base of Environment Process and Digital Simulation, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100678361","display_name":"Mingli Wang","orcid":"https://orcid.org/0000-0001-8376-808X"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingli Wang","raw_affiliation_strings":["Beijing Laboratory of Water Resource Security, Capital Normal University, Beijing 100048, China","Laboratory Cultivation Base of Environment Process and Digital Simulation, Capital Normal University, Beijing 100048, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Laboratory of Water Resource Security, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"Laboratory Cultivation Base of Environment Process and Digital Simulation, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100432613","display_name":"Peng Li","orcid":"https://orcid.org/0000-0001-5026-5347"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Li","raw_affiliation_strings":["Beijing Laboratory of Water Resource Security, Capital Normal University, Beijing 100048, China","Laboratory Cultivation Base of Environment Process and Digital Simulation, Capital Normal University, Beijing 100048, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Laboratory of Water Resource Security, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"Laboratory Cultivation Base of Environment Process and Digital Simulation, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083558440","display_name":"Shuangyue Zhang","orcid":"https://orcid.org/0009-0000-4502-2463"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuangyue Zhang","raw_affiliation_strings":["Beijing Laboratory of Water Resource Security, Capital Normal University, Beijing 100048, China","Laboratory Cultivation Base of Environment Process and Digital Simulation, Capital Normal University, Beijing 100048, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Laboratory of Water Resource Security, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"Laboratory Cultivation Base of Environment Process and Digital Simulation, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5089180563","https://openalex.org/A5101584424"],"corresponding_institution_ids":["https://openalex.org/I96852419"],"apc_list":{"value":2600,"currency":"CHF","value_usd":3137},"apc_paid":{"value":2600,"currency":"CHF","value_usd":3137},"fwci":9.6035,"has_fulltext":true,"cited_by_count":206,"citation_normalized_percentile":{"value":0.98183978,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"18","issue":"11","first_page":"3717","last_page":"3717"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9972000122070312,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/satellite-imagery","display_name":"Satellite imagery","score":0.7198930978775024},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6047899127006531},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.59958815574646},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5900160670280457},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5691472291946411},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.5653741955757141},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5375608205795288},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.5361338257789612},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5158674120903015},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.4994370937347412},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4801861047744751},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47337955236434937},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4356761872768402},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.28992995619773865},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.2573888599872589},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.24178701639175415},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18075451254844666},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1056469976902008}],"concepts":[{"id":"https://openalex.org/C2778102629","wikidata":"https://www.wikidata.org/wiki/Q725252","display_name":"Satellite imagery","level":2,"score":0.7198930978775024},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6047899127006531},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.59958815574646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5900160670280457},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5691472291946411},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.5653741955757141},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5375608205795288},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.5361338257789612},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5158674120903015},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.4994370937347412},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4801861047744751},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47337955236434937},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4356761872768402},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.28992995619773865},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.2573888599872589},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.24178701639175415},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18075451254844666},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1056469976902008},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.3390/s18113717","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s18113717","pdf_url":"https://www.mdpi.com/1424-8220/18/11/3717/pdf?version=1541058133","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},{"id":"pmid:30388781","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30388781","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":"Journal Article"},{"id":"pmh:oai:europepmc.org:5257650","is_oa":true,"landing_page_url":"http://europepmc.org/pmc/articles/PMC6263528","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:6263528","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6263528","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:596c51baaea942278b76052816417024","is_oa":true,"landing_page_url":"https://doaj.org/article/596c51baaea942278b76052816417024","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":"Sensors, Vol 18, Iss 11, p 3717 (2018)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/18/11/3717/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/s18113717","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":"Sensors","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s18113717","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s18113717","pdf_url":"https://www.mdpi.com/1424-8220/18/11/3717/pdf?version=1541058133","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7699999809265137,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G2354040022","display_name":null,"funder_award_id":"5172002","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G2723613431","display_name":null,"funder_award_id":"41401493, 41701533","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3879756750","display_name":null,"funder_award_id":"41701533","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G52513219","display_name":null,"funder_award_id":"41401493","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G564947085","display_name":null,"funder_award_id":"2016-04","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6508602044","display_name":null,"funder_award_id":"xx2015B060","funder_id":"https://openalex.org/F4320334978","funder_display_name":"Beijing Nova Program"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null},{"id":"https://openalex.org/F4320334978","display_name":"Beijing Nova Program","ror":"https://ror.org/034k14f91"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2899315938.pdf","grobid_xml":"https://content.openalex.org/works/W2899315938.grobid-xml"},"referenced_works_count":55,"referenced_works":["https://openalex.org/W73112891","https://openalex.org/W1535289548","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1909515874","https://openalex.org/W1980287119","https://openalex.org/W1994790229","https://openalex.org/W2022686119","https://openalex.org/W2027319213","https://openalex.org/W2082137420","https://openalex.org/W2095705004","https://openalex.org/W2098676252","https://openalex.org/W2108581046","https://openalex.org/W2119879130","https://openalex.org/W2123822317","https://openalex.org/W2150986124","https://openalex.org/W2153635508","https://openalex.org/W2158899491","https://openalex.org/W2163605009","https://openalex.org/W2167510172","https://openalex.org/W2206762869","https://openalex.org/W2267317359","https://openalex.org/W2273664412","https://openalex.org/W2295859130","https://openalex.org/W2340897893","https://openalex.org/W2341130385","https://openalex.org/W2412588858","https://openalex.org/W2538244214","https://openalex.org/W2548390752","https://openalex.org/W2551751523","https://openalex.org/W2589503469","https://openalex.org/W2616755213","https://openalex.org/W2740144340","https://openalex.org/W2744274881","https://openalex.org/W2764276316","https://openalex.org/W2774038444","https://openalex.org/W2774116070","https://openalex.org/W2774320778","https://openalex.org/W2787614951","https://openalex.org/W2790444446","https://openalex.org/W2792057679","https://openalex.org/W2890554434","https://openalex.org/W2919115771","https://openalex.org/W2952230511","https://openalex.org/W2963859992","https://openalex.org/W2963995737","https://openalex.org/W2964309882","https://openalex.org/W2981849677","https://openalex.org/W3102850314","https://openalex.org/W4239510810","https://openalex.org/W6674330103","https://openalex.org/W6676242389","https://openalex.org/W6683738474","https://openalex.org/W6687483927","https://openalex.org/W6743636814"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2797752778"],"abstract_inverted_index":{"Urban":[0],"land":[1,4,32,247],"cover":[2,33,248],"and":[3,14,26,57,112,118,132,168,185,210,229,238,241,244],"use":[5],"mapping":[6],"plays":[7],"an":[8,58],"important":[9],"role":[10],"in":[11,79,83,149],"urban":[12,31,246],"planning":[13],"management.":[15],"In":[16],"this":[17],"paper,":[18],"novel":[19],"multi-scale":[20,87],"deep":[21,88],"learning":[22],"models,":[23,222],"namely":[24],"ASPP-Unet":[25,45,191],"ResASPP-Unet":[27,95,163],"are":[28],"proposed":[29,44,217],"for":[30,182,187,207,212],"classification":[34,179,249],"based":[35,114,171],"on":[36,115,154,172],"very":[37],"high":[38],"resolution":[39],"(VHR)":[40],"satellite":[41],"imagery.":[42,214],"The":[43,70,94,108,190],"model":[46,96,156,164,192,234],"consists":[47],"of":[48,125,135,151,205],"a":[49,67,91],"contracting":[50],"path":[51],"which":[52,61],"extracts":[53],"the":[54,63,80,99,123,133,143,155,162,177,194,216,220],"high-level":[55],"features,":[56],"expansive":[59],"path,":[60],"up-samples":[62],"features":[64,89],"to":[65,85],"create":[66],"high-resolution":[68],"output.":[69],"atrous":[71],"spatial":[72],"pyramid":[73],"pooling":[74],"(ASPP)":[75],"technique":[76],"is":[77,159],"utilized":[78],"bottom":[81],"layer":[82,104,130],"order":[84],"incorporate":[86],"into":[90],"discriminative":[92],"feature.":[93],"further":[97],"improves":[98],"architecture":[100],"by":[101],"replacing":[102],"each":[103],"with":[105,165,193,202],"residual":[106],"unit.":[107],"models":[109,218],"were":[110,147],"trained":[111],"tested":[113],"WorldView-2":[116],"(WV2)":[117],"WorldView-3":[119],"(WV3)":[120],"imageries":[121],"over":[122,235],"city":[124],"Beijing.":[126],"Model":[127],"parameters":[128],"including":[129],"depth":[131],"number":[134],"initial":[136],"feature":[137],"maps":[138],"(IFMs)":[139],"as":[140,142],"well":[141],"input":[144],"image":[145],"bands":[146],"evaluated":[148],"terms":[150],"their":[152],"impact":[153],"performances.":[157],"It":[158],"shown":[160],"that":[161],"11":[166],"layers":[167],"64":[169],"IFMs":[170],"8-band":[173],"WV2":[174,183,208,237],"imagery":[175,184,209],"produced":[176,198],"highest":[178],"accuracy":[180,204],"(87.1%":[181],"84.0%":[186],"WV3":[188,213,239],"imagery).":[189],"same":[195],"parameter":[196],"setting":[197],"slightly":[199],"lower":[200],"accuracy,":[201],"overall":[203],"85.2%":[206],"83.2%":[211],"Overall,":[215],"outperformed":[219],"state-of-the-art":[221],"e.g.,":[223],"U-Net,":[224],"convolutional":[225],"neural":[226],"network":[227],"(CNN)":[228],"Support":[230],"Vector":[231],"Machine":[232],"(SVM)":[233],"both":[236],"images,":[240],"yielded":[242],"robust":[243],"efficient":[245],"results.":[250]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":27},{"year":2024,"cited_by_count":33},{"year":2023,"cited_by_count":33},{"year":2022,"cited_by_count":48},{"year":2021,"cited_by_count":24},{"year":2020,"cited_by_count":23},{"year":2019,"cited_by_count":10}],"updated_date":"2026-08-22T07:34:49.880490","created_date":"2025-10-10T00:00:00"}
