{"id":"https://openalex.org/W3132666576","doi":"https://doi.org/10.1109/igarss39084.2020.9324011","title":"CNN-Based Tree Species Classification Using Airborne Lidar Data and High-Resolution Satellite Image","display_name":"CNN-Based Tree Species Classification Using Airborne Lidar Data and High-Resolution Satellite Image","publication_year":2020,"publication_date":"2020-09-26","ids":{"openalex":"https://openalex.org/W3132666576","doi":"https://doi.org/10.1109/igarss39084.2020.9324011","mag":"3132666576"},"language":"en","primary_location":{"id":"doi:10.1109/igarss39084.2020.9324011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9324011","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100774715","display_name":"Hui Li","orcid":"https://orcid.org/0000-0002-3565-1773"},"institutions":[{"id":"https://openalex.org/I192455969","display_name":"York University","ror":"https://ror.org/05fq50484","country_code":"CA","type":"education","lineage":["https://openalex.org/I192455969"]},{"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"]}],"countries":["CA","CN"],"is_corresponding":false,"raw_author_name":"Hui Li","raw_affiliation_strings":["Hainan Key Laboratory of Earth Observation, Sanya, China","Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","York University, Toronto, ON, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hainan Key Laboratory of Earth Observation, Sanya, China","institution_ids":[]},{"raw_affiliation_string":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]},{"raw_affiliation_string":"York University, Toronto, ON, Canada","institution_ids":["https://openalex.org/I192455969"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011464681","display_name":"Baoxin Hu","orcid":"https://orcid.org/0000-0002-1858-6922"},"institutions":[{"id":"https://openalex.org/I192455969","display_name":"York University","ror":"https://ror.org/05fq50484","country_code":"CA","type":"education","lineage":["https://openalex.org/I192455969"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Baoxin Hu","raw_affiliation_strings":["York University, Toronto, ON, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"York University, Toronto, ON, Canada","institution_ids":["https://openalex.org/I192455969"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101945802","display_name":"Qian Li","orcid":"https://orcid.org/0000-0003-3562-1627"},"institutions":[{"id":"https://openalex.org/I192455969","display_name":"York University","ror":"https://ror.org/05fq50484","country_code":"CA","type":"education","lineage":["https://openalex.org/I192455969"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Qian Li","raw_affiliation_strings":["York University, Toronto, ON, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"York University, Toronto, ON, Canada","institution_ids":["https://openalex.org/I192455969"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107852476","display_name":"Linhai Jing","orcid":null},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linhai Jing","raw_affiliation_strings":["Hainan Key Laboratory of Earth Observation, Sanya, China","Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hainan Key Laboratory of Earth Observation, Sanya, China","institution_ids":[]},{"raw_affiliation_string":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9715,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.88365001,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2679","last_page":"2682"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9991999864578247,"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/T10895","display_name":"Species Distribution and Climate Change","score":0.9890000224113464,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"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/multispectral-image","display_name":"Multispectral image","score":0.7852745056152344},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7652658224105835},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.7638880014419556},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.7129005789756775},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.7018282413482666},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6612703800201416},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5998560190200806},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.5848531723022461},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5839220285415649},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5311497449874878},{"id":"https://openalex.org/keywords/vegetation","display_name":"Vegetation (pathology)","score":0.4975126087665558},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4759756624698639},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4708537459373474},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.20781147480010986},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2010083794593811},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12572187185287476}],"concepts":[{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.7852745056152344},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7652658224105835},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.7638880014419556},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7129005789756775},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.7018282413482666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6612703800201416},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5998560190200806},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.5848531723022461},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5839220285415649},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5311497449874878},{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.4975126087665558},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4759756624698639},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4708537459373474},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.20781147480010986},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2010083794593811},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12572187185287476},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"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":1,"locations":[{"id":"doi:10.1109/igarss39084.2020.9324011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9324011","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.7300000190734863}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1994434338","https://openalex.org/W1994668970","https://openalex.org/W2013234343","https://openalex.org/W2194775991","https://openalex.org/W2513504913","https://openalex.org/W2515306179","https://openalex.org/W2566956493","https://openalex.org/W2748857187","https://openalex.org/W2761482986","https://openalex.org/W2764034829","https://openalex.org/W2769616159","https://openalex.org/W2770429219","https://openalex.org/W2782522152","https://openalex.org/W2803946774","https://openalex.org/W2945472816"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2072166414","https://openalex.org/W2956374172","https://openalex.org/W2022304901","https://openalex.org/W2018850895","https://openalex.org/W1987483041","https://openalex.org/W2988577871","https://openalex.org/W4391030644","https://openalex.org/W4205174160"],"abstract_inverted_index":{"Spatial":[0],"information":[1],"of":[2,6,56,111,151],"tree":[3,101,106,158],"species":[4,21,102,159],"composition":[5],"forest":[7,15,127],"and":[8,17,39,61,86,117,129,137],"urban":[9,18],"vegetation":[10],"is":[11,27],"very":[12],"important":[13],"for":[14,100,157],"protection":[16],"management.":[19],"Tree":[20],"classification":[22,32,84,90,103,124],"using":[23,30,108,125],"remote":[24,70],"sensing":[25,71],"data":[26],"mainly":[28],"conducted":[29],"such":[31],"methods":[33,85],"as":[34],"SVM":[35],"(Support":[36],"Vector":[37],"Machine)":[38],"Random":[40],"Forest.":[41],"Images":[42],"used":[43,156],"include":[44],"multispectral/hyperspectral":[45],"images,":[46],"LiDAR":[47,118],"(Light":[48],"Detection":[49],"And":[50],"Ranging)":[51],"data,":[52],"or":[53],"the":[54,109,121,134,138,149,152],"combination":[55,110],"them.":[57],"As":[58],"a":[59,77],"fast-growing":[60],"powerful":[62],"tool":[63],"having":[64],"obtained":[65],"state-of-the-art":[66],"results":[67,147],"in":[68,80],"many":[69],"applications,":[72],"Deep":[73],"learning":[74],"(DL)":[75],"has":[76],"great":[78],"potential":[79],"outperforming":[81],"these":[82],"existing":[83],"obtaining":[87],"more":[88],"accurate":[89],"maps.":[91],"In":[92],"this":[93],"work,":[94],"three":[95],"CNN":[96,154],"models":[97,155],"were":[98],"employed":[99],"at":[104],"individual":[105],"level,":[107],"high-resolution":[112],"multispectral":[113],"image":[114],"(i.e.,":[115],"WorldView-2)":[116],"data.":[119],"Compared":[120],"traditional":[122],"object-based":[123],"random":[126],"(RF)":[128],"support":[130],"vector":[131],"machine":[132],"(SVM),":[133],"18-layer":[135],"ResNet":[136],"40-layer":[139],"DenseNet":[140],"provided":[141],"significant":[142],"higher":[143],"accuracies.":[144],"The":[145],"experimental":[146],"indicate":[148],"advantages":[150],"two":[153],"classification.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
