{"id":"https://openalex.org/W4409225837","doi":"https://doi.org/10.1109/tgrs.2025.3558312","title":"<i>TreeStructor</i>: Forest Reconstruction With Neural Ranking","display_name":"<i>TreeStructor</i>: Forest Reconstruction With Neural Ranking","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4409225837","doi":"https://doi.org/10.1109/tgrs.2025.3558312"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2025.3558312","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3558312","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"article","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/A5102940048","display_name":"Xiaocheng Zhou","orcid":"https://orcid.org/0000-0003-2280-7799"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaochen Zhou","raw_affiliation_strings":["Department of Computer Science, Purdue University, West Lafayette, IN, USA"],"raw_orcid":"https://orcid.org/0000-0003-2280-7799","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101954740","display_name":"Bosheng Li","orcid":"https://orcid.org/0009-0006-6490-1184"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bosheng Li","raw_affiliation_strings":["Department of Computer Science, Purdue University, West Lafayette, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061742294","display_name":"Bed\u0159ich Bene\u0161","orcid":"https://orcid.org/0000-0002-5293-2112"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bedrich Benes","raw_affiliation_strings":["Department of Computer Science, Purdue University, West Lafayette, IN, USA"],"raw_orcid":"https://orcid.org/0000-0002-5293-2112","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051952251","display_name":"Ayman Habib","orcid":"https://orcid.org/0000-0001-6498-5951"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ayman Habib","raw_affiliation_strings":["Department of Civil Engineering, Purdue University, West Lafayette, IN, USA"],"raw_orcid":"https://orcid.org/0000-0001-6498-5951","affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032832468","display_name":"Songlin Fei","orcid":"https://orcid.org/0000-0003-2772-0166"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Songlin Fei","raw_affiliation_strings":["Department of Forestry and Natural Resources, Purdue University, West Lafayette, IN, USA"],"raw_orcid":"https://orcid.org/0000-0003-2772-0166","affiliations":[{"raw_affiliation_string":"Department of Forestry and Natural Resources, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073692369","display_name":"J. Shao","orcid":"https://orcid.org/0000-0003-0441-9565"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jinyuan Shao","raw_affiliation_strings":["Department of Forestry and Natural Resources, Purdue University, West Lafayette, IN, USA"],"raw_orcid":"https://orcid.org/0000-0003-0441-9565","affiliations":[{"raw_affiliation_string":"Department of Forestry and Natural Resources, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022418359","display_name":"S\u00f6ren Pirk","orcid":"https://orcid.org/0000-0003-1937-9797"},"institutions":[{"id":"https://openalex.org/I32021983","display_name":"Christian-Albrechts-Universit\u00e4t zu Kiel","ror":"https://ror.org/04v76ef78","country_code":"DE","type":"education","lineage":["https://openalex.org/I32021983"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"S\u00f6ren Pirk","raw_affiliation_strings":["Department of Computer Science, Kiel University, Kiel, Germany","Department of Computer Science, Kiel University, Kiel, USA"],"raw_orcid":"https://orcid.org/0000-0003-1937-9797","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Kiel University, Kiel, Germany","institution_ids":["https://openalex.org/I32021983"]},{"raw_affiliation_string":"Department of Computer Science, Kiel University, Kiel, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9278,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.83635025,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"19"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.972000002861023,"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":0.972000002861023,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9315000176429749,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.577531635761261},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5633519291877747},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5101187825202942},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.491565078496933},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4295167624950409},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3497017025947571},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.20319470763206482}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.577531635761261},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5633519291877747},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5101187825202942},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.491565078496933},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4295167624950409},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3497017025947571},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.20319470763206482}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2025.3558312","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3558312","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4465882606","display_name":null,"funder_award_id":"2023-68012-38992","funder_id":"https://openalex.org/F4320332299","funder_display_name":"National Institute of Food and Agriculture"},{"id":"https://openalex.org/G4653267954","display_name":"Collaborative Research: IIBRP: VR-Bio-Talk: VR Voice-Controlled Visual Analytics Platform for Plant Digital Twins","funder_award_id":"2417510","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4787178636","display_name":null,"funder_award_id":"NR233A750004G044","funder_id":"https://openalex.org/F4320332782","funder_display_name":"Natural Resources Conservation Service"},{"id":"https://openalex.org/G4797139084","display_name":null,"funder_award_id":"2024-67013-42449","funder_id":"https://openalex.org/F4320332299","funder_display_name":"National Institute of Food and Agriculture"},{"id":"https://openalex.org/G4963588501","display_name":null,"funder_award_id":"2024-67021-42879","funder_id":"https://openalex.org/F4320332299","funder_display_name":"National Institute of Food and Agriculture"},{"id":"https://openalex.org/G5315432959","display_name":"Collaborative Research: TRTech-PGR: Digital Ideotype for Optimal Canopy Architecture","funder_award_id":"2412928","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332299","display_name":"National Institute of Food and Agriculture","ror":"https://ror.org/05qx3fv49"},{"id":"https://openalex.org/F4320332782","display_name":"Natural Resources Conservation Service","ror":"https://ror.org/03j7rgg33"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":91,"referenced_works":["https://openalex.org/W1577608396","https://openalex.org/W1580065766","https://openalex.org/W1882610713","https://openalex.org/W1955601057","https://openalex.org/W1967688818","https://openalex.org/W1984994646","https://openalex.org/W2010403194","https://openalex.org/W2010769244","https://openalex.org/W2034205349","https://openalex.org/W2036697911","https://openalex.org/W2051490657","https://openalex.org/W2080574968","https://openalex.org/W2091701868","https://openalex.org/W2113748593","https://openalex.org/W2118752698","https://openalex.org/W2131440240","https://openalex.org/W2135844327","https://openalex.org/W2162412455","https://openalex.org/W2165835468","https://openalex.org/W2333006887","https://openalex.org/W2395696537","https://openalex.org/W2596873134","https://openalex.org/W2616039339","https://openalex.org/W2618239361","https://openalex.org/W2621261023","https://openalex.org/W2623697286","https://openalex.org/W2738415988","https://openalex.org/W2769265803","https://openalex.org/W2789936919","https://openalex.org/W2807380843","https://openalex.org/W2901497416","https://openalex.org/W2953602496","https://openalex.org/W2957790523","https://openalex.org/W2963047159","https://openalex.org/W2997388461","https://openalex.org/W2998553944","https://openalex.org/W3028314732","https://openalex.org/W3028855635","https://openalex.org/W3031883024","https://openalex.org/W3107669227","https://openalex.org/W3113798012","https://openalex.org/W3121308055","https://openalex.org/W3137754491","https://openalex.org/W3142649732","https://openalex.org/W3159766270","https://openalex.org/W3165740030","https://openalex.org/W3169964496","https://openalex.org/W3177812761","https://openalex.org/W3181818321","https://openalex.org/W3183706069","https://openalex.org/W3184487972","https://openalex.org/W3197705420","https://openalex.org/W3206849198","https://openalex.org/W3207024742","https://openalex.org/W3208393716","https://openalex.org/W3211830023","https://openalex.org/W4200133699","https://openalex.org/W4214813861","https://openalex.org/W4226359022","https://openalex.org/W4241660447","https://openalex.org/W4286541822","https://openalex.org/W4286611174","https://openalex.org/W4287623247","https://openalex.org/W4290601528","https://openalex.org/W4312274934","https://openalex.org/W4313034350","https://openalex.org/W4313154498","https://openalex.org/W4313524854","https://openalex.org/W4316814214","https://openalex.org/W4320168508","https://openalex.org/W4367400165","https://openalex.org/W4375929013","https://openalex.org/W4378588795","https://openalex.org/W4385288908","https://openalex.org/W4385309036","https://openalex.org/W4386108493","https://openalex.org/W4387385606","https://openalex.org/W4387502952","https://openalex.org/W4387801794","https://openalex.org/W4389539278","https://openalex.org/W4394903686","https://openalex.org/W4400820634","https://openalex.org/W4402716026","https://openalex.org/W4402727277","https://openalex.org/W4402754287","https://openalex.org/W4403267413","https://openalex.org/W4404439859","https://openalex.org/W4404630448","https://openalex.org/W6632393774","https://openalex.org/W6638049664","https://openalex.org/W6856147399"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"We":[0,76,120],"introduceTreeStructor,":[1],"a":[2,15,30,35,49,78,94],"novel":[3],"approach":[4],"for":[5,92,142],"isolating":[6],"and":[7,66,107,122,135,148,161],"reconstructing":[8],"forest":[9,50,130],"trees.":[10],"The":[11,43,159],"key":[12],"novelty":[13],"is":[14,48],"deep":[16],"neural":[17,21],"model":[18],"that":[19,54,61,71,86,125],"uses":[20],"ranking":[22],"to":[23,29,45,82,109],"assign":[24],"pre-generated":[25],"connectable":[26],"3D":[27],"geometries":[28],"point":[31,41,51,59,69,79],"cloud.TreeStructoris":[32],"trained":[33],"on":[34,145,155],"large":[36,95],"set":[37,96],"of":[38,97,114],"synthetically":[39],"generated":[40],"clouds.":[42],"input":[44],"our":[46,126],"method":[47,127,141],"cloud":[52,80],"(FPC)":[53],"we":[55],"first":[56],"decompose":[57],"into":[58,68],"clouds":[60,70],"approximately":[62],"represent":[63,72],"trees":[64,116,131],"(TPC)":[65],"then":[67],"their":[73],"parts":[74],"(PPC).":[75],"use":[77],"encoder-decoder":[81],"compute":[83],"embedding":[84],"vectors":[85],"retrieve":[87],"the":[88,102,138],"best-fitting":[89],"surface":[90,112],"mesh":[91],"eachPPCfrom":[93],"predefined":[98],"branch":[99],"parts.":[100],"Finally,":[101],"retrieved":[103],"meshes":[104,113],"are":[105,163],"connected":[106],"oriented":[108],"obtain":[110],"individual":[111],"all":[115],"represented":[117],"by":[118],"theFPC.":[119],"qualitatively":[121],"quantitatively":[123],"validate":[124],"can":[128],"reconstruct":[129],"with":[132,153],"unprecedented":[133],"accuracy":[134],"visual":[136],"fidelity.TreeStructoroutperforms":[137],"state-of-the-art":[139],"reconstruction":[140],"around":[143],"6%":[144],"quantitative":[146],"metrics":[147],"12%":[149],"less":[150],"error":[151],"compared":[152],"QSM":[154],"low-quality":[156],"scanned":[157],"data.":[158],"code":[160],"data":[162],"available":[164],"at":[165],"https://lewkesy.github.io/TreeStructor/.":[166]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}