{"id":"https://openalex.org/W2548410081","doi":"https://doi.org/10.1109/igarss.2016.7729449","title":"Effect of size and number of calibration plots on the estimation of stem diameter distributions using airborne laser scanning","display_name":"Effect of size and number of calibration plots on the estimation of stem diameter distributions using airborne laser scanning","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2548410081","doi":"https://doi.org/10.1109/igarss.2016.7729449","mag":"2548410081"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2016.7729449","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2016.7729449","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","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/A5101491246","display_name":"Chen Shang","orcid":"https://orcid.org/0000-0002-2128-7667"},"institutions":[{"id":"https://openalex.org/I204722609","display_name":"Queen's University","ror":"https://ror.org/02y72wh86","country_code":"CA","type":"education","lineage":["https://openalex.org/I204722609"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Chen Shang","raw_affiliation_strings":["Department of Geography and Planning, Queen's University, Kingston, ON, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geography and Planning, Queen's University, Kingston, ON, Canada","institution_ids":["https://openalex.org/I204722609"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046443626","display_name":"Trevor A. Jones","orcid":"https://orcid.org/0000-0001-6943-6097"},"institutions":[{"id":"https://openalex.org/I1320721754","display_name":"Ministry of Natural Resources and Forestry","ror":"https://ror.org/02ntv3742","country_code":"CA","type":"government","lineage":["https://openalex.org/I1320721754"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Trevor Jones","raw_affiliation_strings":["Ministry of Natural Resources and Forestry, Sault St. Marie, ON, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ministry of Natural Resources and Forestry, Sault St. Marie, ON, Canada","institution_ids":["https://openalex.org/I1320721754"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043761294","display_name":"Paul Treitz","orcid":"https://orcid.org/0000-0003-2109-9671"},"institutions":[{"id":"https://openalex.org/I204722609","display_name":"Queen's University","ror":"https://ror.org/02y72wh86","country_code":"CA","type":"education","lineage":["https://openalex.org/I204722609"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Paul Treitz","raw_affiliation_strings":["Department of Geography and Planning, Queen's University, Kingston, ON, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geography and Planning, Queen's University, Kingston, ON, Canada","institution_ids":["https://openalex.org/I204722609"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6286,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.69686324,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"41","issue":null,"first_page":"1753","last_page":"1756"},"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":0.9993000030517578,"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":0.998199999332428,"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/statistics","display_name":"Statistics","score":0.5612338185310364},{"id":"https://openalex.org/keywords/forest-inventory","display_name":"Forest inventory","score":0.542707085609436},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.5365175604820251},{"id":"https://openalex.org/keywords/laser-scanning","display_name":"Laser scanning","score":0.5232797265052795},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5225020051002502},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5064641237258911},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.5003225803375244},{"id":"https://openalex.org/keywords/diameter-at-breast-height","display_name":"Diameter at breast height","score":0.49398499727249146},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4870005249977112},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.45090407133102417},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.4500220715999603},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.43068066239356995},{"id":"https://openalex.org/keywords/forest-management","display_name":"Forest management","score":0.3013981878757477},{"id":"https://openalex.org/keywords/forestry","display_name":"Forestry","score":0.23004797101020813},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.20709332823753357},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.17208024859428406},{"id":"https://openalex.org/keywords/laser","display_name":"Laser","score":0.15212565660476685},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1241200864315033},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.11380040645599365},{"id":"https://openalex.org/keywords/agroforestry","display_name":"Agroforestry","score":0.08543121814727783}],"concepts":[{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5612338185310364},{"id":"https://openalex.org/C147103442","wikidata":"https://www.wikidata.org/wiki/Q1423188","display_name":"Forest inventory","level":3,"score":0.542707085609436},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.5365175604820251},{"id":"https://openalex.org/C141349535","wikidata":"https://www.wikidata.org/wiki/Q1361664","display_name":"Laser scanning","level":3,"score":0.5232797265052795},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5225020051002502},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5064641237258911},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.5003225803375244},{"id":"https://openalex.org/C58330081","wikidata":"https://www.wikidata.org/wiki/Q973582","display_name":"Diameter at breast height","level":2,"score":0.49398499727249146},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4870005249977112},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.45090407133102417},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.4500220715999603},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.43068066239356995},{"id":"https://openalex.org/C28631016","wikidata":"https://www.wikidata.org/wiki/Q372561","display_name":"Forest management","level":2,"score":0.3013981878757477},{"id":"https://openalex.org/C97137747","wikidata":"https://www.wikidata.org/wiki/Q38112","display_name":"Forestry","level":1,"score":0.23004797101020813},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.20709332823753357},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.17208024859428406},{"id":"https://openalex.org/C520434653","wikidata":"https://www.wikidata.org/wiki/Q38867","display_name":"Laser","level":2,"score":0.15212565660476685},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1241200864315033},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.11380040645599365},{"id":"https://openalex.org/C54286561","wikidata":"https://www.wikidata.org/wiki/Q397350","display_name":"Agroforestry","level":1,"score":0.08543121814727783},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2016.7729449","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2016.7729449","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.7400000095367432}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W289032787","https://openalex.org/W934247679","https://openalex.org/W1973754976","https://openalex.org/W1992040756","https://openalex.org/W2019126302","https://openalex.org/W2040647925","https://openalex.org/W2049192390","https://openalex.org/W2061969208","https://openalex.org/W2072334158","https://openalex.org/W2072474981","https://openalex.org/W2085520997","https://openalex.org/W2131472136","https://openalex.org/W2155261478","https://openalex.org/W2159470716","https://openalex.org/W2161136770","https://openalex.org/W2473713426","https://openalex.org/W2519724882","https://openalex.org/W2911964244","https://openalex.org/W6720869550","https://openalex.org/W6726781194"],"related_works":["https://openalex.org/W2244384984","https://openalex.org/W2110308804","https://openalex.org/W2149963083","https://openalex.org/W3097107142","https://openalex.org/W2883563055","https://openalex.org/W2765876372","https://openalex.org/W1965597456","https://openalex.org/W3024236969","https://openalex.org/W2995370404","https://openalex.org/W2208843201"],"abstract_inverted_index":{"Stem":[0],"diameter":[1,20,59],"distribution":[2],"is":[3,44],"a":[4,30,119],"crucial":[5],"forest":[6,11,17,36,66,107],"inventory":[7,37],"variable":[8],"in":[9,61],"operational":[10],"management.":[12],"Compared":[13],"to":[14,45,82,135],"ground":[15],"based":[16],"mensuration":[18],"(e.g.,":[19],"at":[21],"breast":[22],"height":[23],"(DBH)),":[24],"airborne":[25],"laser":[26],"scanning":[27],"(ALS)":[28],"offers":[29],"cost":[31],"effective":[32],"alternative":[33],"for":[34],"modelling":[35,58],"variables.":[38],"The":[39],"objective":[40],"of":[41,49,54,75,97,115,128,142,147],"this":[42],"study":[43],"determine":[46],"the":[47,50,73,76,105,113,126,137,143],"impact":[48,121],"size":[51,74,114,144],"and":[52,104,145],"number":[53,127,146],"sample":[55,77,116,148],"plots":[56,78,117],"on":[57,122],"distributions":[60,86],"an":[62],"unevenaged":[63],"tolerant":[64],"hardwood":[65],"using":[67],"discrete":[68],"return":[69],"ALS":[70],"data.":[71],"With":[72],"ranging":[79],"from":[80],"0.04":[81],"0.25":[83],"ha,":[84],"DBH":[85],"were":[87],"divided":[88],"into":[89],"six":[90],"structural":[91],"classes,":[92],"estimated":[93],"by":[94],"two":[95],"categories":[96],"non-parametric":[98],"methods:":[99],"k-nearest":[100],"neighbor":[101],"(k-NN)":[102],"imputation":[103],"random":[106],"(RF).":[108],"Sensitivity":[109],"analysis":[110],"demonstrated":[111],"that":[112],"has":[118],"stronger":[120],"model":[123],"performance":[124],"than":[125],"plots.":[129,149],"In":[130],"addition,":[131],"RF":[132],"was":[133],"found":[134],"be":[136],"most":[138],"accurate":[139],"model,":[140],"regardless":[141]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
