{"id":"https://openalex.org/W4366425389","doi":"https://doi.org/10.3390/rs15082140","title":"Mapping Tree Species Using CNN from Bi-Seasonal High-Resolution Drone Optic and LiDAR Data","display_name":"Mapping Tree Species Using CNN from Bi-Seasonal High-Resolution Drone Optic and LiDAR Data","publication_year":2023,"publication_date":"2023-04-18","ids":{"openalex":"https://openalex.org/W4366425389","doi":"https://doi.org/10.3390/rs15082140"},"language":"en","primary_location":{"id":"doi:10.3390/rs15082140","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15082140","pdf_url":"https://www.mdpi.com/2072-4292/15/8/2140/pdf?version=1681895811","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/2072-4292/15/8/2140/pdf?version=1681895811","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014403872","display_name":"Eu-Ru Lee","orcid":"https://orcid.org/0000-0003-3026-0543"},"institutions":[{"id":"https://openalex.org/I124633538","display_name":"University of Seoul","ror":"https://ror.org/05en5nh73","country_code":"KR","type":"education","lineage":["https://openalex.org/I124633538"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Eu-Ru Lee","raw_affiliation_strings":["Department of Geoinformatics, University of Seoul, 163 Seoulsiripdae-ro, Dongdaemun-gu, Seoul 02504, Republic of Korea","Department of Smart Cities, University of Seoul, 163 Seoulsiripdae-ro, Dongdaemun-gu, Seoul 02504, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Geoinformatics, University of Seoul, 163 Seoulsiripdae-ro, Dongdaemun-gu, Seoul 02504, Republic of Korea","institution_ids":["https://openalex.org/I124633538"]},{"raw_affiliation_string":"Department of Smart Cities, University of Seoul, 163 Seoulsiripdae-ro, Dongdaemun-gu, Seoul 02504, Republic of Korea","institution_ids":["https://openalex.org/I124633538"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089849447","display_name":"Won-Kyung Baek","orcid":"https://orcid.org/0000-0002-9779-0752"},"institutions":[{"id":"https://openalex.org/I124633538","display_name":"University of Seoul","ror":"https://ror.org/05en5nh73","country_code":"KR","type":"education","lineage":["https://openalex.org/I124633538"]},{"id":"https://openalex.org/I133437993","display_name":"Korea Institute of Ocean Science and Technology","ror":"https://ror.org/032m55064","country_code":"KR","type":"facility","lineage":["https://openalex.org/I133437993"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Won-Kyung Baek","raw_affiliation_strings":["Department of Geoinformatics, University of Seoul, 163 Seoulsiripdae-ro, Dongdaemun-gu, Seoul 02504, Republic of Korea","Korea Ocean Satellite Center, Korea Institute of Ocean Science & Technology, Haeyang-ro, Yeongdo-gu, Busan 49111, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Geoinformatics, University of Seoul, 163 Seoulsiripdae-ro, Dongdaemun-gu, Seoul 02504, Republic of Korea","institution_ids":["https://openalex.org/I124633538"]},{"raw_affiliation_string":"Korea Ocean Satellite Center, Korea Institute of Ocean Science & Technology, Haeyang-ro, Yeongdo-gu, Busan 49111, Republic of Korea","institution_ids":["https://openalex.org/I133437993"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040012035","display_name":"Hyung-Sup Jung","orcid":"https://orcid.org/0000-0003-2335-8438"},"institutions":[{"id":"https://openalex.org/I124633538","display_name":"University of Seoul","ror":"https://ror.org/05en5nh73","country_code":"KR","type":"education","lineage":["https://openalex.org/I124633538"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hyung-Sup Jung","raw_affiliation_strings":["Department of Geoinformatics, University of Seoul, 163 Seoulsiripdae-ro, Dongdaemun-gu, Seoul 02504, Republic of Korea","Department of Smart Cities, University of Seoul, 163 Seoulsiripdae-ro, Dongdaemun-gu, Seoul 02504, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Geoinformatics, University of Seoul, 163 Seoulsiripdae-ro, Dongdaemun-gu, Seoul 02504, Republic of Korea","institution_ids":["https://openalex.org/I124633538"]},{"raw_affiliation_string":"Department of Smart Cities, University of Seoul, 163 Seoulsiripdae-ro, Dongdaemun-gu, Seoul 02504, Republic of Korea","institution_ids":["https://openalex.org/I124633538"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5040012035"],"corresponding_institution_ids":["https://openalex.org/I124633538"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":2.672,"has_fulltext":true,"cited_by_count":22,"citation_normalized_percentile":{"value":0.89380125,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"15","issue":"8","first_page":"2140","last_page":"2140"},"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/T13568","display_name":"Wood and Agarwood Research","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/1605","display_name":"Organic Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9940999746322632,"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/computer-science","display_name":"Computer science","score":0.758415937423706},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.6423356533050537},{"id":"https://openalex.org/keywords/drone","display_name":"Drone","score":0.6248559355735779},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6170122623443604},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5801827311515808},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5610102415084839},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.45625385642051697},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4501575529575348},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3706868886947632},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3488784432411194},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1149868369102478},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11096739768981934}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.758415937423706},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.6423356533050537},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.6248559355735779},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6170122623443604},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5801827311515808},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5610102415084839},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.45625385642051697},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4501575529575348},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3706868886947632},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3488784432411194},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1149868369102478},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11096739768981934},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","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},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs15082140","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15082140","pdf_url":"https://www.mdpi.com/2072-4292/15/8/2140/pdf?version=1681895811","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:556f90859e7a4b3b8b9a970b97dda8f4","is_oa":true,"landing_page_url":"https://doaj.org/article/556f90859e7a4b3b8b9a970b97dda8f4","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 15, Iss 8, p 2140 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/8/2140/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15082140","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 15; Issue 8; Pages: 2140","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs15082140","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15082140","pdf_url":"https://www.mdpi.com/2072-4292/15/8/2140/pdf?version=1681895811","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":[{"score":0.7799999713897705,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[{"id":"https://openalex.org/G5220339869","display_name":null,"funder_award_id":"22-CM-EO-02","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"},{"id":"https://openalex.org/G8439884929","display_name":null,"funder_award_id":"22-CM-EO-02","funder_id":"https://openalex.org/F4320329473","funder_display_name":"Institute of Civil-Military Technology Cooperation"},{"id":"https://openalex.org/G8722130826","display_name":null,"funder_award_id":"22-CM-EO-02","funder_id":"https://openalex.org/F4320334874","funder_display_name":"Defense Acquisition Program Administration"},{"id":"https://openalex.org/G992484961","display_name":null,"funder_award_id":"Korea","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"}],"funders":[{"id":"https://openalex.org/F4320321681","display_name":"Ministry of Trade, Industry and Energy","ror":"https://ror.org/008nkqk13"},{"id":"https://openalex.org/F4320329473","display_name":"Institute of Civil-Military Technology Cooperation","ror":null},{"id":"https://openalex.org/F4320334874","display_name":"Defense Acquisition Program Administration","ror":"https://ror.org/04bjg9m96"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4366425389.pdf"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1967621805","https://openalex.org/W1971024845","https://openalex.org/W2050652866","https://openalex.org/W2063396028","https://openalex.org/W2164948205","https://openalex.org/W2386027095","https://openalex.org/W2557829394","https://openalex.org/W2621384129","https://openalex.org/W2760244101","https://openalex.org/W2898152330","https://openalex.org/W2904029397","https://openalex.org/W2907071956","https://openalex.org/W2936503027","https://openalex.org/W2955795720","https://openalex.org/W2965101009","https://openalex.org/W2978760586","https://openalex.org/W3027477918","https://openalex.org/W3028628556","https://openalex.org/W3035803741","https://openalex.org/W3047190055","https://openalex.org/W3109821323","https://openalex.org/W3121566766","https://openalex.org/W3158592082","https://openalex.org/W3178600350","https://openalex.org/W3182952703","https://openalex.org/W3197961809","https://openalex.org/W3200303594","https://openalex.org/W3210207949","https://openalex.org/W4231109964","https://openalex.org/W6766279313","https://openalex.org/W6777895791","https://openalex.org/W7017493108"],"related_works":["https://openalex.org/W4229448053","https://openalex.org/W2059768187","https://openalex.org/W4247925126","https://openalex.org/W4312858960","https://openalex.org/W4386036939","https://openalex.org/W4327774218","https://openalex.org/W4379143281","https://openalex.org/W3206445629","https://openalex.org/W2605096541","https://openalex.org/W3200286695"],"abstract_inverted_index":{"As":[0],"the":[1,52,55,65,74,79,91,99,122,135,144,179,196,209,215,250,268,283],"importance":[2],"of":[3,22,30,51,54,78,124,146,159,181,211,285,287,299],"forests":[4,26],"has":[5,15],"increased,":[6],"continuously":[7],"monitoring":[8],"and":[9,20,46,76,177,199,214,233,236,241,243,246,249,276,290,305],"managing":[10],"information":[11],"on":[12,73],"forest":[13,31,269],"ecology":[14],"become":[16],"essential.":[17],"The":[18,227,258],"composition":[19],"distribution":[21],"tree":[23,40,60,147,182,265,304,331],"species":[24,41,61,266],"in":[25,62,134,255,267,281],"are":[27],"essential":[28],"indicators":[29],"ecosystems.":[32],"Several":[33],"studies":[34],"have":[35,110],"been":[36],"conducted":[37],"to":[38,89,208],"classify":[39],"using":[42,164,220,270],"remote":[43],"sensing":[44],"data":[45,82,126,131,187,201,212],"machine":[47,66],"learning":[48,67,103,320],"algorithms":[49,105],"because":[50],"constraints":[53],"traditional":[56],"approach":[57],"for":[58,224,301,307,326],"classifying":[59,264],"forests.":[63],"In":[64,98,138],"approach,":[68],"classification":[69,87,94,113,148,183,216,297,314],"accuracy":[70,145],"varies":[71],"based":[72],"characteristics":[75],"quantity":[77],"study":[80,136],"area":[81],"used.":[83],"Thus,":[84],"applying":[85],"various":[86,157,189,288],"models":[88,155,223],"achieve":[90],"most":[92],"accurate":[93],"results":[95,114,228,259],"is":[96,132,316],"necessary.":[97],"literature,":[100],"patch-based":[101],"deep":[102],"(DL)":[104],"that":[106,230,261],"use":[107],"feature":[108,161],"maps":[109],"shown":[111],"superior":[112,296],"than":[115],"point-based":[116],"techniques.":[117],"DL":[118,154],"techniques":[119],"substantially":[120],"affect":[121],"performance":[123,194,217,298,315],"input":[125,186],"but":[127],"gathering":[128],"highly":[129],"explanatory":[130],"difficult":[133],"area.":[137],"this":[139],"study,":[140],"we":[141],"analyzed":[142],"(1)":[143,262],"by":[149,184,321],"convolutional":[150],"neural":[151],"networks":[152],"(CNNs)-based":[153],"with":[156],"structures":[158],"CNN":[160],"extraction":[162],"areas":[163],"a":[165,174,279,295,302],"high-resolution":[166,271],"LiDAR-derived":[167],"digital":[168],"surface":[169],"model":[170,280,319],"(DSM)":[171],"acquired":[172],"from":[173],"drone":[175,197,273],"platform":[176],"(2)":[178,313],"impact":[180],"creating":[185],"via":[188],"geometric":[190],"augmentation":[191],"methods.":[192],"For":[193],"comparison,":[195],"optic":[198],"LiDAR":[200,277],"were":[202,238],"separated":[203],"into":[204],"two":[205,308,327],"groups":[206],"according":[207],"application":[210],"augmentation,":[213],"was":[218,253],"compared":[219],"three":[221],"CNN-based":[222],"each":[225],"group.":[226],"demonstrated":[229,294],"Groups":[231],"1":[232],"CNN-1,":[234],"CNN-2,":[235],"CNN-3":[237,254],"0.74,":[239],"0.79,":[240,244],"0.82":[242],"0.80,":[245],"0.84,":[247],"respectively,":[248],"best":[251],"mode":[252],"Group":[256],"2.":[257],"imply":[260],"when":[263],"bi-seasonal":[272],"optical":[274],"images":[275],"data,":[278,324],"which":[282],"number":[284],"filters":[286,291],"sizes":[289],"gradually":[292],"decreased":[293],"0.95":[300],"single":[303],"0.75":[306],"or":[309,328],"more":[310,329],"mixed":[311,330],"species;":[312],"enhanced":[317],"during":[318],"augmenting":[322],"training":[323],"especially":[325],"species.":[332]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2023-04-21T00:00:00"}