{"id":"https://openalex.org/W2769616159","doi":"https://doi.org/10.3390/rs9111180","title":"Tree-Species Classification in Subtropical Forests Using Airborne Hyperspectral and LiDAR Data","display_name":"Tree-Species Classification in Subtropical Forests Using Airborne Hyperspectral and LiDAR Data","publication_year":2017,"publication_date":"2017-11-17","ids":{"openalex":"https://openalex.org/W2769616159","doi":"https://doi.org/10.3390/rs9111180","mag":"2769616159"},"language":"en","primary_location":{"id":"doi:10.3390/rs9111180","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs9111180","pdf_url":"https://www.mdpi.com/2072-4292/9/11/1180/pdf?version=1510994710","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/2072-4292/9/11/1180/pdf?version=1510994710","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031929340","display_name":"Xin Shen","orcid":"https://orcid.org/0000-0002-5517-277X"},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Shen","raw_affiliation_strings":["Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"],"affiliations":[{"raw_affiliation_string":"Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China","institution_ids":["https://openalex.org/I167027274"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083073196","display_name":"Lin Cao","orcid":"https://orcid.org/0000-0001-5195-0477"},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lin Cao","raw_affiliation_strings":["Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"],"affiliations":[{"raw_affiliation_string":"Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China","institution_ids":["https://openalex.org/I167027274"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5083073196"],"corresponding_institution_ids":["https://openalex.org/I167027274"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":5.0788,"has_fulltext":false,"cited_by_count":125,"citation_normalized_percentile":{"value":0.95930444,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"9","issue":"11","first_page":"1180","last_page":"1180"},"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":0.9947999715805054,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8271118998527527},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.8260538578033447},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6687104105949402},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6631094813346863},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.5645948648452759},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4777792692184448},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.46053364872932434},{"id":"https://openalex.org/keywords/tropical-and-subtropical-moist-broadleaf-forests","display_name":"Tropical and subtropical moist broadleaf forests","score":0.4468749165534973},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.38902077078819275},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26480910181999207},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23915094137191772},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.21075138449668884},{"id":"https://openalex.org/keywords/subtropics","display_name":"Subtropics","score":0.15610891580581665},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.08008119463920593}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8271118998527527},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.8260538578033447},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6687104105949402},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6631094813346863},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.5645948648452759},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4777792692184448},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.46053364872932434},{"id":"https://openalex.org/C149095469","wikidata":"https://www.wikidata.org/wiki/Q158579","display_name":"Tropical and subtropical moist broadleaf forests","level":3,"score":0.4468749165534973},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.38902077078819275},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26480910181999207},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23915094137191772},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.21075138449668884},{"id":"https://openalex.org/C14168384","wikidata":"https://www.wikidata.org/wiki/Q16305538","display_name":"Subtropics","level":2,"score":0.15610891580581665},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.08008119463920593},{"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/rs9111180","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs9111180","pdf_url":"https://www.mdpi.com/2072-4292/9/11/1180/pdf?version=1510994710","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:a269b173de9345f28c2e7de67c275048","is_oa":true,"landing_page_url":"https://doaj.org/article/a269b173de9345f28c2e7de67c275048","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 9, Iss 11, p 1180 (2017)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/9/11/1180/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs9111180","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 9; Issue 11; Pages: 1180","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs9111180","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs9111180","pdf_url":"https://www.mdpi.com/2072-4292/9/11/1180/pdf?version=1510994710","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":0.5699999928474426,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320327518","display_name":"Priority Academic Program Development of Jiangsu Higher Education Institutions","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2769616159.pdf","grobid_xml":"https://content.openalex.org/works/W2769616159.grobid-xml"},"referenced_works_count":121,"referenced_works":["https://openalex.org/W51106753","https://openalex.org/W172260869","https://openalex.org/W818076710","https://openalex.org/W1530609470","https://openalex.org/W1554230853","https://openalex.org/W1584308190","https://openalex.org/W1964217023","https://openalex.org/W1964697047","https://openalex.org/W1967621805","https://openalex.org/W1969568499","https://openalex.org/W1970437612","https://openalex.org/W1976416886","https://openalex.org/W1977944376","https://openalex.org/W1979678339","https://openalex.org/W1981590796","https://openalex.org/W1982369897","https://openalex.org/W1985700403","https://openalex.org/W1989401377","https://openalex.org/W1992979930","https://openalex.org/W1999856162","https://openalex.org/W2000861278","https://openalex.org/W2005885990","https://openalex.org/W2012564082","https://openalex.org/W2016776156","https://openalex.org/W2017517123","https://openalex.org/W2018239548","https://openalex.org/W2020708554","https://openalex.org/W2023303051","https://openalex.org/W2024649846","https://openalex.org/W2024869078","https://openalex.org/W2025330625","https://openalex.org/W2029534599","https://openalex.org/W2029545808","https://openalex.org/W2029567272","https://openalex.org/W2031126473","https://openalex.org/W2033535916","https://openalex.org/W2036003376","https://openalex.org/W2036061791","https://openalex.org/W2037225341","https://openalex.org/W2038498697","https://openalex.org/W2039810213","https://openalex.org/W2042891401","https://openalex.org/W2048061433","https://openalex.org/W2055734610","https://openalex.org/W2058822610","https://openalex.org/W2059217921","https://openalex.org/W2059854942","https://openalex.org/W2063396028","https://openalex.org/W2069793096","https://openalex.org/W2076143808","https://openalex.org/W2078296814","https://openalex.org/W2080640904","https://openalex.org/W2084291846","https://openalex.org/W2084857239","https://openalex.org/W2084958926","https://openalex.org/W2089441588","https://openalex.org/W2090624115","https://openalex.org/W2090858999","https://openalex.org/W2096996101","https://openalex.org/W2097337758","https://openalex.org/W2098057602","https://openalex.org/W2098919237","https://openalex.org/W2099400014","https://openalex.org/W2100507486","https://openalex.org/W2101051003","https://openalex.org/W2101907415","https://openalex.org/W2107543999","https://openalex.org/W2109006150","https://openalex.org/W2109191549","https://openalex.org/W2111947859","https://openalex.org/W2113410727","https://openalex.org/W2116674621","https://openalex.org/W2118146322","https://openalex.org/W2121102297","https://openalex.org/W2125574854","https://openalex.org/W2125724410","https://openalex.org/W2129350970","https://openalex.org/W2130774035","https://openalex.org/W2130868979","https://openalex.org/W2134717732","https://openalex.org/W2135550335","https://openalex.org/W2136251662","https://openalex.org/W2141544611","https://openalex.org/W2145994233","https://openalex.org/W2147197381","https://openalex.org/W2148964762","https://openalex.org/W2149471024","https://openalex.org/W2150434735","https://openalex.org/W2150489395","https://openalex.org/W2151362686","https://openalex.org/W2152575904","https://openalex.org/W2152778181","https://openalex.org/W2161746820","https://openalex.org/W2161815745","https://openalex.org/W2165148193","https://openalex.org/W2165796970","https://openalex.org/W2167894638","https://openalex.org/W2168508773","https://openalex.org/W2169103225","https://openalex.org/W2171683008","https://openalex.org/W2182128045","https://openalex.org/W2253886175","https://openalex.org/W2270715058","https://openalex.org/W2302803999","https://openalex.org/W2327650336","https://openalex.org/W2383860596","https://openalex.org/W2494022581","https://openalex.org/W2523353497","https://openalex.org/W2559726834","https://openalex.org/W2574404198","https://openalex.org/W2748857187","https://openalex.org/W3116281389","https://openalex.org/W3213429084","https://openalex.org/W4319289039","https://openalex.org/W6665363120","https://openalex.org/W6684815264","https://openalex.org/W6691857744","https://openalex.org/W6723122182","https://openalex.org/W6727755562","https://openalex.org/W6849296793","https://openalex.org/W7043800957"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2072166414","https://openalex.org/W2956374172","https://openalex.org/W3209970181","https://openalex.org/W2070598848","https://openalex.org/W4319837668","https://openalex.org/W4308071650","https://openalex.org/W4293094720","https://openalex.org/W2739701376"],"abstract_inverted_index":{"Accurate":[0],"classification":[1,166,186,213],"of":[2,41,66,78,90,138,203,234,242],"tree-species":[3,37,134,180,252],"is":[4],"essential":[5],"for":[6,154,177],"sustainably":[7],"managing":[8],"forest":[9],"resources":[10],"and":[11,24,31,62,80,85,95,115,118,123,190],"effectively":[12,253],"monitoring":[13],"species":[14],"diversity.":[15],"In":[16,208],"this":[17,159],"study,":[18],"we":[19],"used":[20,124,249],"simultaneously":[21],"acquired":[22],"hyperspectral":[23,73,79,109,189,199],"LiDAR":[25,30,53,81,119,191],"data":[26,54],"from":[27,103],"LiCHy":[28],"(Hyperspectral,":[29],"CCD)":[32],"airborne":[33],"system":[34],"to":[35,127,131,250],"classify":[36,251],"in":[38,99,158,181,194],"subtropical":[39],"forests":[40],"southeast":[42],"China.":[43],"First,":[44],"each":[45,67],"individual":[46,156],"tree":[47,145,157],"crown":[48,68,114,216,224],"was":[49,69,152],"extracted":[50,84],"using":[51,71,187,214,222],"the":[52,63,72,88,96,144,182,212,231,243],"by":[55,87],"a":[56,169],"point":[57],"cloud":[58,149],"segmentation":[59,150],"algorithm":[60],"(PCS)":[61],"sunlit":[64,116,223],"portion":[65],"selected":[70,86],"data.":[74],"Second,":[75],"different":[76],"suites":[77],"metrics":[82,110,120,192,200,217,225,246],"were":[83,121],"indices":[89],"Principal":[91],"Component":[92],"Analysis":[93],"(PCA)":[94],"mean":[97],"decrease":[98],"Gini":[100],"index":[101],"(MDG)":[102],"Random":[104,128],"Forest":[105,129],"(RF).":[106],"Finally,":[107],"both":[108,188],"(based":[111],"on":[112],"whole":[113,215],"crown)":[117],"assessed":[122],"as":[125],"inputs":[126],"classifier":[130],"discriminate":[132],"five":[133,179],"at":[135],"two":[136],"levels":[137],"classification.":[139],"The":[140,165,185,236],"results":[141,237],"showed":[142],"that":[143,240],"delineation":[146],"approach":[147,167],"(point":[148],"algorithm)":[151],"suitable":[153],"detecting":[155],"study":[160,183],"(overall":[161,173,218,226,254],"accuracy":[162,172,174],"=":[163,206,220,228,256],"82.9%).":[164],"provided":[168],"relatively":[170],"high":[171],">":[175],"85.4%)":[176],"classifying":[178],"site.":[184],"resulted":[193],"higher":[195],"accuracies":[196,205,219,227,233,255],"than":[197],"only":[198],"(the":[201],"improvement":[202],"overall":[204,232],"0.4\u20135.6%).":[207],"addition,":[209],"compared":[210],"with":[211],"85.4\u201389.3%),":[221],"87.1\u201391.5%)":[229],"improved":[230],"2.3%.":[235],"also":[238],"suggested":[239],"fewer":[241],"most":[244],"important":[245],"can":[247],"be":[248],"85.8\u201391.0%).":[257]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":21},{"year":2021,"cited_by_count":22},{"year":2020,"cited_by_count":16},{"year":2019,"cited_by_count":13},{"year":2018,"cited_by_count":4}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2017-12-04T00:00:00"}