{"id":"https://openalex.org/W4309651454","doi":"https://doi.org/10.1145/3557915.3561471","title":"Deep learning based 3D point cloud regression for estimating forest biomass","display_name":"Deep learning based 3D point cloud regression for estimating forest biomass","publication_year":2022,"publication_date":"2022-11-01","ids":{"openalex":"https://openalex.org/W4309651454","doi":"https://doi.org/10.1145/3557915.3561471"},"language":"en","primary_location":{"id":"doi:10.1145/3557915.3561471","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3557915.3561471","pdf_url":null,"source":{"id":"https://openalex.org/S4363608995","display_name":"Proceedings of the 30th International Conference on Advances in Geographic Information Systems","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://researchprofiles.ku.dk/da/publications/a533c339-99d4-4526-874c-9b5364ee124b","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017031707","display_name":"Stefan Oehmcke","orcid":"https://orcid.org/0000-0002-0240-1559"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Stefan Oehmcke","raw_affiliation_strings":["University of Copenhagen, Copenhagen, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I124055696"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100440300","display_name":"Lei Li","orcid":"https://orcid.org/0000-0002-2929-0828"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Lei Li","raw_affiliation_strings":["University of Copenhagen, Copenhagen, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I124055696"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052183109","display_name":"Jaime Caballer Revenga","orcid":"https://orcid.org/0000-0002-9330-6572"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Jaime C. Revenga","raw_affiliation_strings":["University of Copenhagen, Copenhagen, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I124055696"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075519362","display_name":"Thomas Nord\u2010Larsen","orcid":"https://orcid.org/0000-0002-5341-6435"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Thomas Nord-Larsen","raw_affiliation_strings":["University of Copenhagen, Copenhagen, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I124055696"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074779213","display_name":"Katerina Trepekli","orcid":"https://orcid.org/0000-0002-9040-4409"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Katerina Trepekli","raw_affiliation_strings":["University of Copenhagen, Copenhagen, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I124055696"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023532714","display_name":"Fabian Gieseke","orcid":"https://orcid.org/0000-0001-7093-5803"},"institutions":[{"id":"https://openalex.org/I22465464","display_name":"University of M\u00fcnster","ror":"https://ror.org/00pd74e08","country_code":"DE","type":"education","lineage":["https://openalex.org/I22465464"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Fabian Gieseke","raw_affiliation_strings":["University of M\u00fcnster, M\u00fcnster, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of M\u00fcnster, M\u00fcnster, Germany","institution_ids":["https://openalex.org/I22465464"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042628612","display_name":"Christian Igel","orcid":"https://orcid.org/0000-0003-2868-0856"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Christian Igel","raw_affiliation_strings":["University of Copenhagen, Copenhagen, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I124055696"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":16.5803,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.9968298,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"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/T11880","display_name":"Forest ecology and management","score":0.9990000128746033,"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":0.9944000244140625,"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":0.782712459564209},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6704791188240051},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.608912467956543},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.5638081431388855},{"id":"https://openalex.org/keywords/forest-inventory","display_name":"Forest inventory","score":0.48664411902427673},{"id":"https://openalex.org/keywords/terrain","display_name":"Terrain","score":0.4683398902416229},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.44810548424720764},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.443228542804718},{"id":"https://openalex.org/keywords/biomass","display_name":"Biomass (ecology)","score":0.42651286721229553},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.41783392429351807},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4168393015861511},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.412800133228302},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.33526092767715454},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20470574498176575},{"id":"https://openalex.org/keywords/forest-management","display_name":"Forest management","score":0.19935351610183716},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.18807452917099},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.14959612488746643},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.11409187316894531},{"id":"https://openalex.org/keywords/agroforestry","display_name":"Agroforestry","score":0.08002525568008423}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.782712459564209},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6704791188240051},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.608912467956543},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.5638081431388855},{"id":"https://openalex.org/C147103442","wikidata":"https://www.wikidata.org/wiki/Q1423188","display_name":"Forest inventory","level":3,"score":0.48664411902427673},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.4683398902416229},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.44810548424720764},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.443228542804718},{"id":"https://openalex.org/C115540264","wikidata":"https://www.wikidata.org/wiki/Q2945560","display_name":"Biomass (ecology)","level":2,"score":0.42651286721229553},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41783392429351807},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4168393015861511},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.412800133228302},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.33526092767715454},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20470574498176575},{"id":"https://openalex.org/C28631016","wikidata":"https://www.wikidata.org/wiki/Q372561","display_name":"Forest management","level":2,"score":0.19935351610183716},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.18807452917099},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.14959612488746643},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.11409187316894531},{"id":"https://openalex.org/C54286561","wikidata":"https://www.wikidata.org/wiki/Q397350","display_name":"Agroforestry","level":1,"score":0.08002525568008423},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3557915.3561471","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3557915.3561471","pdf_url":null,"source":{"id":"https://openalex.org/S4363608995","display_name":"Proceedings of the 30th International Conference on Advances in Geographic Information Systems","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/a533c339-99d4-4526-874c-9b5364ee124b","is_oa":true,"landing_page_url":"https://researchprofiles.ku.dk/da/publications/a533c339-99d4-4526-874c-9b5364ee124b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401983","display_name":"Research at the University of Copenhagen (University of Copenhagen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I124055696","host_organization_name":"University of Copenhagen","host_organization_lineage":["https://openalex.org/I124055696"],"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":null,"raw_type":"contributionToPeriodical"}],"best_oa_location":{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/a533c339-99d4-4526-874c-9b5364ee124b","is_oa":true,"landing_page_url":"https://researchprofiles.ku.dk/da/publications/a533c339-99d4-4526-874c-9b5364ee124b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401983","display_name":"Research at the University of Copenhagen (University of Copenhagen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I124055696","host_organization_name":"University of Copenhagen","host_organization_lineage":["https://openalex.org/I124055696"],"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":null,"raw_type":"contributionToPeriodical"},"sustainable_development_goals":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.46000000834465027}],"awards":[{"id":"https://openalex.org/G5394559786","display_name":null,"funder_award_id":"34306","funder_id":"https://openalex.org/F4320310490","funder_display_name":"Villum Fonden"}],"funders":[{"id":"https://openalex.org/F4320310490","display_name":"Villum Fonden","ror":"https://ror.org/007ww2d15"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W1973428156","https://openalex.org/W2093830434","https://openalex.org/W2121942758","https://openalex.org/W2124284178","https://openalex.org/W2143010534","https://openalex.org/W2164850486","https://openalex.org/W2560609797","https://openalex.org/W2752782242","https://openalex.org/W2797957951","https://openalex.org/W3014318699","https://openalex.org/W6606051233","https://openalex.org/W6681039344","https://openalex.org/W6818893528"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W4406302447","https://openalex.org/W2901265155","https://openalex.org/W2956374172","https://openalex.org/W4319837668","https://openalex.org/W4308071650","https://openalex.org/W3188333020","https://openalex.org/W4281783339","https://openalex.org/W4293094720","https://openalex.org/W2739701376"],"abstract_inverted_index":{"Knowledge":[0],"of":[1,73,92,125,152],"forest":[2,88],"biomass":[3,42],"stocks":[4,48],"and":[5,44,66,114],"their":[6],"development":[7],"is":[8,138],"important":[9],"for":[10,37,62,75,97],"implementing":[11],"effective":[12],"climate":[13],"change":[14],"mitigation":[15],"measures.":[16],"Remote":[17],"sensing":[18,71],"using":[19],"airborne":[20,51],"LiDAR":[21,52],"can":[22],"be":[23],"used":[24],"to":[25,118,131,144],"measure":[26],"vegetation":[27],"structure":[28],"at":[29],"large":[30],"scale.":[31],"We":[32,140],"present":[33],"deep":[34,104],"learning":[35],"systems":[36],"predicting":[38],"wood":[39,111],"volume,":[40,112],"above-ground":[41,46],"(AGB),":[43],"subsequently":[45],"carbon":[47,115],"directly":[49],"from":[50,82],"point":[53,63,127],"clouds.":[54,128],"Specifically,":[55],"we":[56],"devise":[57],"different":[58],"neural":[59,95,105],"network":[60],"architectures":[61],"cloud":[64],"regression":[65,98],"evaluate":[67],"them":[68],"on":[69,122,149],"remote":[70],"data":[72],"areas":[74],"which":[76],"AGB":[77],"estimates":[78,116],"have":[79,145],"been":[80],"obtained":[81],"field":[83],"measurements":[84],"in":[85],"a":[86,146],"national":[87],"inventory.":[89],"Our":[90],"adaptation":[91],"Minkowski":[93],"convolutional":[94],"networks":[96,106],"gave":[99],"the":[100,126],"best":[101],"results.":[102],"The":[103],"produced":[107],"significantly":[108],"more":[109],"accurate":[110],"AGB,":[113],"compared":[117],"state-of-the-art":[119],"approaches":[120],"operating":[121],"basic":[123],"statistics":[124],"In":[129],"contrast":[130],"other":[132],"methods,":[133],"no":[134],"digital":[135],"terrain":[136],"model":[137],"required.":[139],"expect":[141],"this":[142],"finding":[143],"strong":[147],"impact":[148],"LiDAR-based":[150],"analyses":[151],"terrestrial":[153],"ecosystem":[154],"dynamics.":[155]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}