{"id":"https://openalex.org/W2566956493","doi":"https://doi.org/10.3390/rs8121034","title":"Comparison of Tree Species Classifications at the Individual Tree Level by Combining ALS Data and RGB Images Using Different Algorithms","display_name":"Comparison of Tree Species Classifications at the Individual Tree Level by Combining ALS Data and RGB Images Using Different Algorithms","publication_year":2016,"publication_date":"2016-12-19","ids":{"openalex":"https://openalex.org/W2566956493","doi":"https://doi.org/10.3390/rs8121034","mag":"2566956493"},"language":"en","primary_location":{"id":"doi:10.3390/rs8121034","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs8121034","pdf_url":"https://www.mdpi.com/2072-4292/8/12/1034/pdf?version=1482146594","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/2072-4292/8/12/1034/pdf?version=1482146594","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103022460","display_name":"Songqiu Deng","orcid":"https://orcid.org/0000-0002-0502-6424"},"institutions":[{"id":"https://openalex.org/I137975476","display_name":"Shinshu University","ror":"https://ror.org/0244rem06","country_code":"JP","type":"education","lineage":["https://openalex.org/I137975476"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Songqiu Deng","raw_affiliation_strings":["Institute of Mountain Science, Shinshu University, Nagano 399-4598, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Mountain Science, Shinshu University, Nagano 399-4598, Japan","institution_ids":["https://openalex.org/I137975476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113821103","display_name":"Masato Katoh","orcid":null},"institutions":[{"id":"https://openalex.org/I137975476","display_name":"Shinshu University","ror":"https://ror.org/0244rem06","country_code":"JP","type":"education","lineage":["https://openalex.org/I137975476"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masato Katoh","raw_affiliation_strings":["Institute of Mountain Science, Shinshu University, Nagano 399-4598, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Mountain Science, Shinshu University, Nagano 399-4598, Japan","institution_ids":["https://openalex.org/I137975476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018804090","display_name":"Xiaowei Yu","orcid":"https://orcid.org/0000-0001-5545-0613"},"institutions":[{"id":"https://openalex.org/I33876163","display_name":"Finnish Geospatial Research Institute","ror":"https://ror.org/01zv3gf04","country_code":"FI","type":"facility","lineage":["https://openalex.org/I33876163"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Xiaowei Yu","raw_affiliation_strings":["Finnish Geospatial Research Institute, Geodeetinrinne 2, 02430 Masala, Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Finnish Geospatial Research Institute, Geodeetinrinne 2, 02430 Masala, Finland","institution_ids":["https://openalex.org/I33876163"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033042071","display_name":"Juha Hyypp\u00e4","orcid":"https://orcid.org/0000-0001-5360-4017"},"institutions":[{"id":"https://openalex.org/I33876163","display_name":"Finnish Geospatial Research Institute","ror":"https://ror.org/01zv3gf04","country_code":"FI","type":"facility","lineage":["https://openalex.org/I33876163"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Juha Hyypp\u00e4","raw_affiliation_strings":["Finnish Geospatial Research Institute, Geodeetinrinne 2, 02430 Masala, Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Finnish Geospatial Research Institute, Geodeetinrinne 2, 02430 Masala, Finland","institution_ids":["https://openalex.org/I33876163"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110918324","display_name":"Tian Gao","orcid":"https://orcid.org/0000-0002-2804-4780"},"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/I4210110024","display_name":"Institute of Applied Ecology","ror":"https://ror.org/01thb7525","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210110024"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tian Gao","raw_affiliation_strings":["Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China","institution_ids":["https://openalex.org/I4210110024","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103022460"],"corresponding_institution_ids":["https://openalex.org/I137975476"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":3.6699,"has_fulltext":false,"cited_by_count":57,"citation_normalized_percentile":{"value":0.92481102,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"8","issue":"12","first_page":"1034","last_page":"1034"},"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/T11880","display_name":"Forest ecology and management","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2309","display_name":"Nature and Landscape Conservation"},"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":0.9977999925613403,"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/larix-kaempferi","display_name":"Larix kaempferi","score":0.7581809759140015},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5425503849983215},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.519053041934967},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5169986486434937},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4878289997577667},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.48762431740760803},{"id":"https://openalex.org/keywords/convex-hull","display_name":"Convex hull","score":0.4750621020793915},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.47465020418167114},{"id":"https://openalex.org/keywords/pinus-densiflora","display_name":"Pinus densiflora","score":0.4588968753814697},{"id":"https://openalex.org/keywords/forest-inventory","display_name":"Forest inventory","score":0.4332565665245056},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4063960313796997},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.39322710037231445},{"id":"https://openalex.org/keywords/forestry","display_name":"Forestry","score":0.3164505362510681},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.16124427318572998},{"id":"https://openalex.org/keywords/forest-management","display_name":"Forest management","score":0.14115822315216064},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.12330713868141174},{"id":"https://openalex.org/keywords/larch","display_name":"Larch","score":0.11321401596069336},{"id":"https://openalex.org/keywords/botany","display_name":"Botany","score":0.0828520655632019}],"concepts":[{"id":"https://openalex.org/C2778954545","wikidata":"https://www.wikidata.org/wiki/Q147439","display_name":"Larix kaempferi","level":3,"score":0.7581809759140015},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5425503849983215},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.519053041934967},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5169986486434937},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4878289997577667},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.48762431740760803},{"id":"https://openalex.org/C206194317","wikidata":"https://www.wikidata.org/wiki/Q1138624","display_name":"Convex hull","level":3,"score":0.4750621020793915},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.47465020418167114},{"id":"https://openalex.org/C2779676560","wikidata":"https://www.wikidata.org/wiki/Q1044186","display_name":"Pinus densiflora","level":2,"score":0.4588968753814697},{"id":"https://openalex.org/C147103442","wikidata":"https://www.wikidata.org/wiki/Q1423188","display_name":"Forest inventory","level":3,"score":0.4332565665245056},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4063960313796997},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39322710037231445},{"id":"https://openalex.org/C97137747","wikidata":"https://www.wikidata.org/wiki/Q38112","display_name":"Forestry","level":1,"score":0.3164505362510681},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.16124427318572998},{"id":"https://openalex.org/C28631016","wikidata":"https://www.wikidata.org/wiki/Q372561","display_name":"Forest management","level":2,"score":0.14115822315216064},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.12330713868141174},{"id":"https://openalex.org/C2778551664","wikidata":"https://www.wikidata.org/wiki/Q25618","display_name":"Larch","level":2,"score":0.11321401596069336},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0828520655632019},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/rs8121034","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs8121034","pdf_url":"https://www.mdpi.com/2072-4292/8/12/1034/pdf?version=1482146594","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:8edff0279b644e13b7dfd0bdeb691293","is_oa":true,"landing_page_url":"https://doaj.org/article/8edff0279b644e13b7dfd0bdeb691293","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":"Remote Sensing, Vol 8, Iss 12, p 1034 (2016)","raw_type":"article"},{"id":"pmh:oai:helda.helsinki.fi:10138/224936","is_oa":true,"landing_page_url":"http://hdl.handle.net/10138/224936","pdf_url":null,"source":{"id":"https://openalex.org/S4210213322","display_name":"Ty\u00f6v\u00e4entutkimus Vuosikirja","issn_l":"0784-1272","issn":["0784-1272","1459-7780"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"A1 Journal article \u2013 refereed"},{"id":"pmh:oai:mdpi.com:/2072-4292/8/12/1034/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs8121034","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 8; Issue 12; Pages: 1034","raw_type":"Text"},{"id":"pmh:oai:soar-ir.repo.nii.ac.jp:00021961","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306402150","display_name":"SOAR (Shinshu University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I137975476","host_organization_name":"Shinshu University","host_organization_lineage":["https://openalex.org/I137975476"],"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":""}],"best_oa_location":{"id":"doi:10.3390/rs8121034","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs8121034","pdf_url":"https://www.mdpi.com/2072-4292/8/12/1034/pdf?version=1482146594","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":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.7900000214576721}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W2566956493.pdf"},"referenced_works_count":81,"referenced_works":["https://openalex.org/W1144368330","https://openalex.org/W1483493965","https://openalex.org/W1492020934","https://openalex.org/W1496825334","https://openalex.org/W1942861091","https://openalex.org/W1969607685","https://openalex.org/W1970535395","https://openalex.org/W1979678339","https://openalex.org/W1983967760","https://openalex.org/W1984839778","https://openalex.org/W1984956136","https://openalex.org/W1985291094","https://openalex.org/W1990763871","https://openalex.org/W1993956929","https://openalex.org/W1994585903","https://openalex.org/W2001832926","https://openalex.org/W2004553299","https://openalex.org/W2004759643","https://openalex.org/W2008233110","https://openalex.org/W2009731464","https://openalex.org/W2018627383","https://openalex.org/W2022576632","https://openalex.org/W2032413422","https://openalex.org/W2042891401","https://openalex.org/W2046421861","https://openalex.org/W2055734610","https://openalex.org/W2059854942","https://openalex.org/W2060042860","https://openalex.org/W2065258204","https://openalex.org/W2070857546","https://openalex.org/W2080157231","https://openalex.org/W2083565284","https://openalex.org/W2085741981","https://openalex.org/W2087667361","https://openalex.org/W2089806346","https://openalex.org/W2090858999","https://openalex.org/W2095069619","https://openalex.org/W2096002337","https://openalex.org/W2097337758","https://openalex.org/W2106488983","https://openalex.org/W2107250927","https://openalex.org/W2109850379","https://openalex.org/W2120332097","https://openalex.org/W2125899407","https://openalex.org/W2127354426","https://openalex.org/W2131058553","https://openalex.org/W2131258618","https://openalex.org/W2132097058","https://openalex.org/W2144313462","https://openalex.org/W2148115499","https://openalex.org/W2156747007","https://openalex.org/W2161548576","https://openalex.org/W2161746820","https://openalex.org/W2162298841","https://openalex.org/W2165044919","https://openalex.org/W2165148193","https://openalex.org/W2166307050","https://openalex.org/W2166823771","https://openalex.org/W2172346641","https://openalex.org/W2174905165","https://openalex.org/W2181716224","https://openalex.org/W2188738748","https://openalex.org/W2253886175","https://openalex.org/W2287279569","https://openalex.org/W2327937174","https://openalex.org/W2333659417","https://openalex.org/W2340847604","https://openalex.org/W2417835980","https://openalex.org/W2464006696","https://openalex.org/W2619078875","https://openalex.org/W2911964244","https://openalex.org/W3023447741","https://openalex.org/W6642535928","https://openalex.org/W6655012520","https://openalex.org/W6665363120","https://openalex.org/W6686379823","https://openalex.org/W6691857744","https://openalex.org/W6701955510","https://openalex.org/W6702992862","https://openalex.org/W6703624077","https://openalex.org/W6719598845"],"related_works":["https://openalex.org/W2999163302","https://openalex.org/W2913144852","https://openalex.org/W2355025665","https://openalex.org/W2889565671","https://openalex.org/W2612344629","https://openalex.org/W3113741757","https://openalex.org/W2516322942","https://openalex.org/W3199643238","https://openalex.org/W2980371763","https://openalex.org/W3117825621"],"abstract_inverted_index":{"Individual":[0],"tree":[1,47,73,90,106,265],"delineation":[2],"using":[3,76,139,206,230,282],"remotely":[4],"sensed":[5],"data":[6,44,120,294],"plays":[7],"a":[8,23,57,77,105,140,300],"very":[9],"important":[10],"role":[11],"in":[12,52,63,150,267,279],"precision":[13],"forestry":[14],"because":[15],"it":[16],"can":[17],"provide":[18],"detailed":[19],"forest":[20,30,238],"information":[21],"on":[22],"large":[24],"scale,":[25],"which":[26],"is":[27],"required":[28],"by":[29,70,218],"managers.":[31],"This":[32,285],"study":[33,65,158,252,269,286],"aimed":[34],"to":[35,204,262,303],"evaluate":[36],"the":[37,64,71,84,88,118,127,151,161,164,186,193,196,207,211,213,224,231,248,254,264,268,289,292],"utility":[38],"of":[39,113,130,156,163,190,195,210,227,244,250,291],"airborne":[40],"laser":[41,168],"scanning":[42],"(ALS)":[43],"for":[45,132],"individual":[46,72],"detection":[48,74],"and":[49,102,121,181,221,236,260,295],"species":[50,133,266,305],"classification":[51,108,146,188,246,273],"Japanese":[53],"coniferous":[54],"forests":[55,281],"with":[56,110,167,192,223],"high":[58],"canopy":[59,78],"density.":[60],"Tree":[61],"crowns":[62,91],"area":[66],"were":[67,92,137,148],"first":[68],"delineated":[69],"approach":[75,109,256,302],"height":[79,183],"model":[80],"(CHM)":[81],"derived":[82,116],"from":[83,117],"ALS":[85,119,293],"data.":[86,284],"Then,":[87],"detected":[89],"classified":[93],"into":[94],"four":[95],"classes\u2014Pinus":[96],"densiflora,":[97],"Chamaecyparis":[98],"obtusa,":[99],"Larix":[100],"kaempferi,":[101],"broadleaved":[103],"trees\u2014using":[104],"crown-based":[107],"different":[111,245,283],"combinations":[112],"23":[114],"features":[115,131,184,228],"true-color":[122],"(red-green-blue\u2014RGB)":[123],"orthoimages.":[124],"To":[125],"determine":[126],"best":[128,225],"combination":[129,162,226],"classification,":[134],"several":[135,145],"loops":[136],"performed":[138],"forward":[141],"iteration":[142],"method.":[143],"Additionally,":[144],"algorithms":[147],"compared":[149],"present":[152],"study.":[153],"The":[154],"results":[155],"this":[157],"indicate":[159],"that":[160,288],"RGB":[165,296],"images":[166,297],"intensity,":[169],"convex":[170,173],"hull":[171,174],"area,":[172,180],"point":[175],"volume,":[176],"shape":[177],"index,":[178],"crown":[179,182],"produced":[185],"highest":[187],"accuracy":[189,215],"90.8%":[191],"use":[194],"quadratic":[197],"support":[198],"vector":[199],"machines":[200],"(QSVM)":[201],"classifier.":[202],"Compared":[203],"only":[205],"spectral":[208],"characteristics":[209],"orthophotos,":[212],"overall":[214],"was":[216],"improved":[217],"14.1%,":[219],"9.4%,":[220],"8.8%":[222],"when":[229],"QSVM,":[232],"neural":[233],"network":[234],"(NN),":[235],"random":[237],"(RF)":[239],"approaches,":[240],"respectively.":[241],"In":[242],"terms":[243],"algorithms,":[247],"findings":[249],"our":[251],"recommend":[253],"QSVM":[255],"rather":[257],"than":[258],"NNs":[259],"RFs":[261],"classify":[263],"area.":[270],"However,":[271],"these":[272],"approaches":[274],"should":[275],"be":[276,299],"further":[277],"tested":[278],"other":[280],"demonstrates":[287],"synergy":[290],"could":[298],"promising":[301],"improve":[304],"classifications.":[306]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":11},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":4}],"updated_date":"2026-06-18T10:00:31.954636","created_date":"2017-01-06T00:00:00"}
