{"id":"https://openalex.org/W2799703355","doi":"https://doi.org/10.3390/rs10040649","title":"The Use of Three-Dimensional Convolutional Neural Networks to Interpret LiDAR for Forest Inventory","display_name":"The Use of Three-Dimensional Convolutional Neural Networks to Interpret LiDAR for Forest Inventory","publication_year":2018,"publication_date":"2018-04-23","ids":{"openalex":"https://openalex.org/W2799703355","doi":"https://doi.org/10.3390/rs10040649","mag":"2799703355"},"language":"en","primary_location":{"id":"doi:10.3390/rs10040649","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs10040649","pdf_url":"https://www.mdpi.com/2072-4292/10/4/649/pdf?version=1525349499","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/2072-4292/10/4/649/pdf?version=1525349499","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027051583","display_name":"Elias Ayrey","orcid":"https://orcid.org/0000-0001-9095-6687"},"institutions":[{"id":"https://openalex.org/I7947594","display_name":"University of Maine","ror":"https://ror.org/01adr0w49","country_code":"US","type":"education","lineage":["https://openalex.org/I2802397601","https://openalex.org/I7947594"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Elias Ayrey","raw_affiliation_strings":["School of Forest Resources, University of Maine, 5755 Nutting Hall, Orono, ME 04469-5755, USA"],"affiliations":[{"raw_affiliation_string":"School of Forest Resources, University of Maine, 5755 Nutting Hall, Orono, ME 04469-5755, USA","institution_ids":["https://openalex.org/I7947594"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034383882","display_name":"Daniel J. Hayes","orcid":"https://orcid.org/0000-0002-3011-7934"},"institutions":[{"id":"https://openalex.org/I7947594","display_name":"University of Maine","ror":"https://ror.org/01adr0w49","country_code":"US","type":"education","lineage":["https://openalex.org/I2802397601","https://openalex.org/I7947594"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel J. Hayes","raw_affiliation_strings":["School of Forest Resources, University of Maine, 5755 Nutting Hall, Orono, ME 04469-5755, USA"],"affiliations":[{"raw_affiliation_string":"School of Forest Resources, University of Maine, 5755 Nutting Hall, Orono, ME 04469-5755, USA","institution_ids":["https://openalex.org/I7947594"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5027051583"],"corresponding_institution_ids":["https://openalex.org/I7947594"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":5.0798,"has_fulltext":false,"cited_by_count":98,"citation_normalized_percentile":{"value":0.95715381,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"10","issue":"4","first_page":"649","last_page":"649"},"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":0.9987999796867371,"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/T12713","display_name":"Forest Ecology and Biodiversity Studies","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1109","display_name":"Insect Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.8972897529602051},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6999324560165405},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6958539485931396},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.5779111385345459},{"id":"https://openalex.org/keywords/forest-inventory","display_name":"Forest inventory","score":0.5605674982070923},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5045152902603149},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.49190235137939453},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4880622625350952},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43417122960090637},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.42376261949539185},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3334991931915283},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2971191108226776},{"id":"https://openalex.org/keywords/forest-management","display_name":"Forest management","score":0.16935613751411438},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1415756344795227},{"id":"https://openalex.org/keywords/forestry","display_name":"Forestry","score":0.123689204454422},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09983614087104797}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.8972897529602051},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6999324560165405},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6958539485931396},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.5779111385345459},{"id":"https://openalex.org/C147103442","wikidata":"https://www.wikidata.org/wiki/Q1423188","display_name":"Forest inventory","level":3,"score":0.5605674982070923},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5045152902603149},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.49190235137939453},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4880622625350952},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43417122960090637},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.42376261949539185},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3334991931915283},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2971191108226776},{"id":"https://openalex.org/C28631016","wikidata":"https://www.wikidata.org/wiki/Q372561","display_name":"Forest management","level":2,"score":0.16935613751411438},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1415756344795227},{"id":"https://openalex.org/C97137747","wikidata":"https://www.wikidata.org/wiki/Q38112","display_name":"Forestry","level":1,"score":0.123689204454422},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09983614087104797},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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":3,"locations":[{"id":"doi:10.3390/rs10040649","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs10040649","pdf_url":"https://www.mdpi.com/2072-4292/10/4/649/pdf?version=1525349499","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:07e4ac88ed0a43ab8c506c692ac1a911","is_oa":true,"landing_page_url":"https://doaj.org/article/07e4ac88ed0a43ab8c506c692ac1a911","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 10, Iss 4, p 649 (2018)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/10/4/649/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs10040649","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 10; Issue 4; Pages: 649","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs10040649","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs10040649","pdf_url":"https://www.mdpi.com/2072-4292/10/4/649/pdf?version=1525349499","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","score":0.7200000286102295,"display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2799703355.pdf","grobid_xml":"https://content.openalex.org/works/W2799703355.grobid-xml"},"referenced_works_count":78,"referenced_works":["https://openalex.org/W29510506","https://openalex.org/W331395217","https://openalex.org/W1483870316","https://openalex.org/W1493004075","https://openalex.org/W1527011892","https://openalex.org/W1538131130","https://openalex.org/W1652321627","https://openalex.org/W1836465849","https://openalex.org/W1849277567","https://openalex.org/W1903029394","https://openalex.org/W1915761309","https://openalex.org/W1965228281","https://openalex.org/W1966946865","https://openalex.org/W1974789528","https://openalex.org/W1994336791","https://openalex.org/W1996263757","https://openalex.org/W2012002695","https://openalex.org/W2024081693","https://openalex.org/W2026942141","https://openalex.org/W2028901390","https://openalex.org/W2041334360","https://openalex.org/W2045626198","https://openalex.org/W2052426632","https://openalex.org/W2060983504","https://openalex.org/W2067841380","https://openalex.org/W2095705004","https://openalex.org/W2097117768","https://openalex.org/W2097998348","https://openalex.org/W2117539524","https://openalex.org/W2118625899","https://openalex.org/W2131121992","https://openalex.org/W2133160971","https://openalex.org/W2143481518","https://openalex.org/W2145287260","https://openalex.org/W2151843635","https://openalex.org/W2153534477","https://openalex.org/W2155714399","https://openalex.org/W2156303437","https://openalex.org/W2159352923","https://openalex.org/W2163605009","https://openalex.org/W2168125451","https://openalex.org/W2168178486","https://openalex.org/W2169874044","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2211722331","https://openalex.org/W2224722989","https://openalex.org/W2225955099","https://openalex.org/W2253429366","https://openalex.org/W2294229279","https://openalex.org/W2301358467","https://openalex.org/W2339077268","https://openalex.org/W2431874326","https://openalex.org/W2482464033","https://openalex.org/W2503161859","https://openalex.org/W2507439898","https://openalex.org/W2523609223","https://openalex.org/W2537499819","https://openalex.org/W2541777388","https://openalex.org/W2546066744","https://openalex.org/W2555003865","https://openalex.org/W2558294288","https://openalex.org/W2565258258","https://openalex.org/W2620645313","https://openalex.org/W2919115771","https://openalex.org/W2962759496","https://openalex.org/W2963459241","https://openalex.org/W2963567641","https://openalex.org/W2964184568","https://openalex.org/W2964350391","https://openalex.org/W6602417957","https://openalex.org/W6632100814","https://openalex.org/W6637412569","https://openalex.org/W6674330103","https://openalex.org/W6674385629","https://openalex.org/W6679349572","https://openalex.org/W6679732833","https://openalex.org/W6684451421"],"related_works":["https://openalex.org/W4384112194","https://openalex.org/W2783354812","https://openalex.org/W2103009189","https://openalex.org/W4312958259","https://openalex.org/W2349383066","https://openalex.org/W1969901537","https://openalex.org/W4328132048","https://openalex.org/W2594043982","https://openalex.org/W3036493597","https://openalex.org/W2087573166"],"abstract_inverted_index":{"As":[0],"light":[1],"detection":[2],"and":[3,37,44,72,144],"ranging":[4],"(LiDAR)":[5],"technology":[6],"becomes":[7],"more":[8,162],"available,":[9],"it":[10],"has":[11],"become":[12],"common":[13],"to":[14,18,40,48,115,173],"use":[15,34],"these":[16,30,46],"datasets":[17],"generate":[19],"remotely":[20],"sensed":[21],"forest":[22,79,87,170],"inventories":[23,31,171],"across":[24],"landscapes.":[25],"Traditional":[26],"methods":[27],"for":[28,77,169],"generating":[29],"employ":[32,56],"the":[33,69,83,90,100,106,149],"of":[35,93,102,124,151,165],"height":[36,120],"proportion":[38],"metrics":[39],"measure":[41],"LiDAR":[42,70,167],"returns":[43],"relate":[45],"back":[47],"field":[49,101],"data":[50,71,168],"using":[51,89,118,157],"predictive":[52],"models.":[53],"Here,":[54],"we":[55,111],"a":[57,63,161],"three-dimensional":[58,91],"convolutional":[59],"neural":[60],"network":[61],"(CNN),":[62],"deep":[64],"learning":[65],"technique":[66],"that":[67,128,156],"scans":[68],"automatically":[73],"generates":[74],"useful":[75],"features":[76],"predicting":[78],"attributes.":[80],"We":[81,154],"test":[82],"accuracy":[84],"in":[85,99,140],"estimating":[86,136,141,148],"attributes":[88],"implementations":[92],"different":[94],"CNN":[95,113],"models":[96,116],"commonly":[97],"used":[98],"image":[103],"recognition.":[104],"Using":[105],"best":[107],"performing":[108],"model":[109],"architecture,":[110],"compared":[112,172],"performance":[114],"developed":[117],"traditional":[119],"metrics.":[121],"The":[122],"results":[123],"this":[125],"comparison":[126],"show":[127],"CNNs":[129,158],"produced":[130],"12%":[131],"less":[132,139,146],"prediction":[133],"error":[134],"when":[135,147],"biomass,":[137],"6%":[138],"tree":[142],"count,":[143],"2%":[145],"percentage":[150],"needleleaf":[152],"trees.":[153],"conclude":[155],"can":[159],"be":[160],"accurate":[163],"means":[164],"interpreting":[166],"standard":[174],"approaches.":[175]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":1}],"updated_date":"2026-03-14T08:43:22.919905","created_date":"2018-05-17T00:00:00"}
