{"id":"https://openalex.org/W2386380824","doi":"https://doi.org/10.1109/whispers.2015.8075403","title":"Optimized feature fusion of LiDAR and hyperspectral data for tree species mapping in closed forest canopies","display_name":"Optimized feature fusion of LiDAR and hyperspectral data for tree species mapping in closed forest canopies","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W2386380824","doi":"https://doi.org/10.1109/whispers.2015.8075403","mag":"2386380824"},"language":"en","primary_location":{"id":"doi:10.1109/whispers.2015.8075403","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2015.8075403","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","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/A5112613245","display_name":"Frieke M.B. Van Coillie","orcid":null},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"F. M. B. Van Coillie","raw_affiliation_strings":["Faculty of Bioscience Engineering, Ghent University, Gent, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Bioscience Engineering, Ghent University, Gent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015582924","display_name":"Wenzhi Liao","orcid":"https://orcid.org/0000-0002-2183-0324"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]},{"id":"https://openalex.org/I39327780","display_name":"iMinds","ror":"https://ror.org/03baec336","country_code":"BE","type":"nonprofit","lineage":["https://openalex.org/I39327780"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"W. Liao","raw_affiliation_strings":["Department of Telecommunications and Information Processing, Ghent University - iMinds - Image Processing and Interpretation, Ghent, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Telecommunications and Information Processing, Ghent University - iMinds - Image Processing and Interpretation, Ghent, Belgium","institution_ids":["https://openalex.org/I32597200","https://openalex.org/I39327780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000964900","display_name":"Pieter Kempeneers","orcid":"https://orcid.org/0000-0002-4317-4807"},"institutions":[{"id":"https://openalex.org/I68522396","display_name":"Flemish Institute for Technological Research","ror":"https://ror.org/04gq0w522","country_code":"BE","type":"facility","lineage":["https://openalex.org/I68522396"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"P. Kempeneers","raw_affiliation_strings":["Flemish Institute for Technological Research - VITO, Mol, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Flemish Institute for Technological Research - VITO, Mol, Belgium","institution_ids":["https://openalex.org/I68522396"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040814961","display_name":"Kris Vandekerkhove","orcid":"https://orcid.org/0000-0003-1954-692X"},"institutions":[{"id":"https://openalex.org/I202500258","display_name":"Research Institute for Nature and Forest","ror":"https://ror.org/00j54wy13","country_code":"BE","type":"facility","lineage":["https://openalex.org/I202500258"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"K. Vandekerkhove","raw_affiliation_strings":["Research Institute for Nature and Forest - INBO, Geraardsbergen, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Institute for Nature and Forest - INBO, Geraardsbergen, Belgium","institution_ids":["https://openalex.org/I202500258"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078286523","display_name":"Sidharta Gautama","orcid":"https://orcid.org/0000-0001-5628-6974"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]},{"id":"https://openalex.org/I39327780","display_name":"iMinds","ror":"https://ror.org/03baec336","country_code":"BE","type":"nonprofit","lineage":["https://openalex.org/I39327780"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"S. Gautama","raw_affiliation_strings":["Department of Telecommunications and Information Processing, Ghent University - iMinds - Image Processing and Interpretation, Ghent, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Telecommunications and Information Processing, Ghent University - iMinds - Image Processing and Interpretation, Ghent, Belgium","institution_ids":["https://openalex.org/I32597200","https://openalex.org/I39327780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071483672","display_name":"Wilfried Philips","orcid":"https://orcid.org/0000-0003-4456-4353"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]},{"id":"https://openalex.org/I39327780","display_name":"iMinds","ror":"https://ror.org/03baec336","country_code":"BE","type":"nonprofit","lineage":["https://openalex.org/I39327780"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"W. Philips","raw_affiliation_strings":["Department of Telecommunications and Information Processing, Ghent University - iMinds - Image Processing and Interpretation, Ghent, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Telecommunications and Information Processing, Ghent University - iMinds - Image Processing and Interpretation, Ghent, Belgium","institution_ids":["https://openalex.org/I32597200","https://openalex.org/I39327780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035395460","display_name":"Robert R. De Wulf","orcid":null},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"R. R. De Wulf","raw_affiliation_strings":["Faculty of Bioscience Engineering, Ghent University, Gent, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Bioscience Engineering, Ghent University, Gent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":1.0,"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":1.0,"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":0.9908999800682068,"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/beech","display_name":"Beech","score":0.8405343890190125},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.7728264927864075},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7137208580970764},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5860224962234497},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5625438094139099},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5579833984375},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.527080237865448},{"id":"https://openalex.org/keywords/larch","display_name":"Larch","score":0.5014317035675049},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4936595857143402},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42981332540512085},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.41581711173057556},{"id":"https://openalex.org/keywords/fagus-sylvatica","display_name":"Fagus sylvatica","score":0.41311225295066833},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4053487479686737},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4025714695453644},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36671286821365356},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.19042333960533142},{"id":"https://openalex.org/keywords/forestry","display_name":"Forestry","score":0.14997059106826782},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.09776410460472107},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.08126240968704224}],"concepts":[{"id":"https://openalex.org/C2776500793","wikidata":"https://www.wikidata.org/wiki/Q25403","display_name":"Beech","level":2,"score":0.8405343890190125},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.7728264927864075},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7137208580970764},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5860224962234497},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5625438094139099},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5579833984375},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.527080237865448},{"id":"https://openalex.org/C2778551664","wikidata":"https://www.wikidata.org/wiki/Q25618","display_name":"Larch","level":2,"score":0.5014317035675049},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4936595857143402},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42981332540512085},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.41581711173057556},{"id":"https://openalex.org/C2780144066","wikidata":"https://www.wikidata.org/wiki/Q146149","display_name":"Fagus sylvatica","level":3,"score":0.41311225295066833},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4053487479686737},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4025714695453644},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36671286821365356},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.19042333960533142},{"id":"https://openalex.org/C97137747","wikidata":"https://www.wikidata.org/wiki/Q38112","display_name":"Forestry","level":1,"score":0.14997059106826782},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.09776410460472107},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.08126240968704224},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/whispers.2015.8075403","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2015.8075403","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","raw_type":"proceedings-article"},{"id":"pmh:oai:archive.ugent.be:7011592","is_oa":false,"landing_page_url":"https://biblio.ugent.be/publication/7011592","pdf_url":null,"source":{"id":"https://openalex.org/S4306400477","display_name":"Ghent University Academic Bibliography (Ghent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32597200","host_organization_name":"Ghent University","host_organization_lineage":["https://openalex.org/I32597200"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"7th workshop on hyperspectral image and signal processing : evolution in remote sensing, Proceedings","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:oai:archive.ugent.be:8627708","is_oa":false,"landing_page_url":"http://hdl.handle.net/1854/LU-8627708","pdf_url":null,"source":{"id":"https://openalex.org/S4306400478","display_name":"Ghent University Academic Bibliography (Ghent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32597200","host_organization_name":"Ghent University","host_organization_lineage":["https://openalex.org/I32597200"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISSN: 2158-6268","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.7699999809265137}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1967621805","https://openalex.org/W2017517123","https://openalex.org/W2018639934","https://openalex.org/W2027781877","https://openalex.org/W2032247947","https://openalex.org/W2063396028","https://openalex.org/W2089806346","https://openalex.org/W2165796970","https://openalex.org/W2315855208","https://openalex.org/W6655211182"],"related_works":["https://openalex.org/W4251521063","https://openalex.org/W2414022095","https://openalex.org/W2155838196","https://openalex.org/W2046792826","https://openalex.org/W2046610420","https://openalex.org/W2071880458","https://openalex.org/W4389177551","https://openalex.org/W3087222845","https://openalex.org/W2975652934","https://openalex.org/W2460548044"],"abstract_inverted_index":{"This":[0],"study":[1],"deals":[2],"with":[3],"data":[4,45,53,108],"fusion":[5,102],"of":[6,41,73,95,103,122],"hyperspectral":[7],"and":[8,36,75,92,106],"LiDAR":[9,42,107],"sensors":[10],"for":[11,112],"tree":[12,25,47,98],"species":[13,26,48,99],"mapping":[14,49],"in":[15,20,56],"complex,":[16],"closed":[17],"forest":[18],"canopies":[19],"Belgium.":[21],"In":[22],"particular,":[23],"seven":[24],"were":[27,54,87],"mapped:":[28],"Beech,":[29],"Ash,":[30],"Larch,":[31],"Poplar,":[32],"Copper":[33],"beech,":[34],"Chestnut":[35],"Oak.":[37],"The":[38],"added":[39],"value":[40],"height":[43],"profile":[44],"on":[46,79],"was":[50,64,109],"assessed.":[51],"Sensor":[52],"fused":[55],"the":[57,67],"PCA":[58],"domain,":[59],"while":[60],"optimal":[61],"feature":[62],"combination":[63],"derived":[65],"from":[66],"best":[68],"classification":[69],"performance":[70],"(in":[71],"terms":[72],"Kappa":[74,119],"producer's":[76],"accuracy)":[77],"based":[78],"5-fold":[80],"cross-validation.":[81],"Besides,":[82],"varying":[83],"training":[84],"set":[85,115],"sizes":[86,116],"tested":[88],"(resp.":[89],"10%,":[90],"30%":[91],"50%":[93],"number":[94],"samples":[96],"per":[97],"class).":[100],"Feature":[101],"PCA-transformed":[104],"HS":[105],"most":[110],"effective":[111],"small":[113],"sample":[114],"reaching":[117],"a":[118],"accuracy":[120],"improvement":[121],"10.51%.":[123]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}