{"id":"https://openalex.org/W4296569550","doi":"https://doi.org/10.3390/rs14174386","title":"Evaluating Statewide NAIP Photogrammetric Point Clouds for Operational Improvement of National Forest Inventory Estimates in Mixed Hardwood Forests of the Southeastern U.S.","display_name":"Evaluating Statewide NAIP Photogrammetric Point Clouds for Operational Improvement of National Forest Inventory Estimates in Mixed Hardwood Forests of the Southeastern U.S.","publication_year":2022,"publication_date":"2022-09-03","ids":{"openalex":"https://openalex.org/W4296569550","doi":"https://doi.org/10.3390/rs14174386"},"language":"en","primary_location":{"id":"doi:10.3390/rs14174386","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14174386","pdf_url":"https://www.mdpi.com/2072-4292/14/17/4386/pdf?version=1662652271","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/2072-4292/14/17/4386/pdf?version=1662652271","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044967770","display_name":"Todd A. Schroeder","orcid":"https://orcid.org/0000-0003-4544-7095"},"institutions":[{"id":"https://openalex.org/I1336096307","display_name":"United States Department of Agriculture","ror":"https://ror.org/01na82s61","country_code":"US","type":"government","lineage":["https://openalex.org/I1336096307"]},{"id":"https://openalex.org/I4210115267","display_name":"Southern Research Station","ror":"https://ror.org/022ethc91","country_code":"US","type":"government","lineage":["https://openalex.org/I1313416372","https://openalex.org/I1336096307","https://openalex.org/I4210115267"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Todd A. Schroeder","raw_affiliation_strings":["United States Department of Agriculture, Forest Service, Southern Research Station, 4700 Old Kingston Pike, Knoxville, TN 37919, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"United States Department of Agriculture, Forest Service, Southern Research Station, 4700 Old Kingston Pike, Knoxville, TN 37919, USA","institution_ids":["https://openalex.org/I1336096307","https://openalex.org/I4210115267"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078575077","display_name":"Shingo Obata","orcid":"https://orcid.org/0000-0002-2974-421X"},"institutions":[{"id":"https://openalex.org/I122345529","display_name":"National Institute for Mathematical and Biological Synthesis","ror":"https://ror.org/04vj69e88","country_code":"US","type":"facility","lineage":["https://openalex.org/I122345529","https://openalex.org/I1311060795"]},{"id":"https://openalex.org/I4210134673","display_name":"The Institute of Statistical Mathematics","ror":"https://ror.org/03jcejr58","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I4210134673","https://openalex.org/I4210158934"]},{"id":"https://openalex.org/I75027704","display_name":"University of Tennessee at Knoxville","ror":"https://ror.org/020f3ap87","country_code":"US","type":"education","lineage":["https://openalex.org/I75027704"]}],"countries":["JP","US"],"is_corresponding":false,"raw_author_name":"Shingo Obata","raw_affiliation_strings":["Institute of Statistical Mathematics, 10-3 Midori-cho, Tachikawa, Tokyo 1908562, Japan","National Institute for Mathematical and Biological Synthesis, University of Tennessee, 1122 Volunteer Blvd., Knoxville, TN 37996, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Statistical Mathematics, 10-3 Midori-cho, Tachikawa, Tokyo 1908562, Japan","institution_ids":["https://openalex.org/I4210134673"]},{"raw_affiliation_string":"National Institute for Mathematical and Biological Synthesis, University of Tennessee, 1122 Volunteer Blvd., Knoxville, TN 37996, USA","institution_ids":["https://openalex.org/I122345529","https://openalex.org/I75027704"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032164522","display_name":"Monica Pape\u015f","orcid":"https://orcid.org/0009-0007-9662-5580"},"institutions":[{"id":"https://openalex.org/I122345529","display_name":"National Institute for Mathematical and Biological Synthesis","ror":"https://ror.org/04vj69e88","country_code":"US","type":"facility","lineage":["https://openalex.org/I122345529","https://openalex.org/I1311060795"]},{"id":"https://openalex.org/I75027704","display_name":"University of Tennessee at Knoxville","ror":"https://ror.org/020f3ap87","country_code":"US","type":"education","lineage":["https://openalex.org/I75027704"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Monica Pape\u015f","raw_affiliation_strings":["Department of Ecology & Evolutionary Biology, University of Tennessee, 569 Dabney Hall, Knoxville, TN 37996, USA","National Institute for Mathematical and Biological Synthesis, University of Tennessee, 1122 Volunteer Blvd., Knoxville, TN 37996, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Ecology & Evolutionary Biology, University of Tennessee, 569 Dabney Hall, Knoxville, TN 37996, USA","institution_ids":["https://openalex.org/I75027704"]},{"raw_affiliation_string":"National Institute for Mathematical and Biological Synthesis, University of Tennessee, 1122 Volunteer Blvd., Knoxville, TN 37996, USA","institution_ids":["https://openalex.org/I122345529","https://openalex.org/I75027704"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002449009","display_name":"Benjamin Branoff","orcid":"https://orcid.org/0000-0002-8796-2039"},"institutions":[{"id":"https://openalex.org/I159176309","display_name":"Universit\u00e4t Hamburg","ror":"https://ror.org/00g30e956","country_code":"DE","type":"education","lineage":["https://openalex.org/I159176309"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Benjamin Branoff","raw_affiliation_strings":["Department of Biology, Universit\u00e4t Hamburg, Ohnhorststra\u00dfe 18, 22609 Hamburg, Germany"],"raw_orcid":"https://orcid.org/0000-0002-8796-2039","affiliations":[{"raw_affiliation_string":"Department of Biology, Universit\u00e4t Hamburg, Ohnhorststra\u00dfe 18, 22609 Hamburg, Germany","institution_ids":["https://openalex.org/I159176309"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5044967770"],"corresponding_institution_ids":["https://openalex.org/I1336096307","https://openalex.org/I4210115267"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2784},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2784},"fwci":0.5962,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.58186603,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"14","issue":"17","first_page":"4386","last_page":"4386"},"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11880","display_name":"Forest ecology and management","score":0.9972000122070312,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/forest-inventory","display_name":"Forest inventory","score":0.8061259984970093},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.7226510643959045},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6680058240890503},{"id":"https://openalex.org/keywords/forestry","display_name":"Forestry","score":0.5845111608505249},{"id":"https://openalex.org/keywords/photogrammetry","display_name":"Photogrammetry","score":0.5618910193443298},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.5549983382225037},{"id":"https://openalex.org/keywords/hardwood","display_name":"Hardwood","score":0.4727286398410797},{"id":"https://openalex.org/keywords/canopy","display_name":"Canopy","score":0.4540749788284302},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4496335983276367},{"id":"https://openalex.org/keywords/tree-canopy","display_name":"Tree canopy","score":0.4486161768436432},{"id":"https://openalex.org/keywords/aerial-photography","display_name":"Aerial photography","score":0.4211667776107788},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.3267233669757843},{"id":"https://openalex.org/keywords/physical-geography","display_name":"Physical geography","score":0.3231145441532135},{"id":"https://openalex.org/keywords/forest-management","display_name":"Forest management","score":0.24666109681129456},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.21516737341880798},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.17348265647888184},{"id":"https://openalex.org/keywords/archaeology","display_name":"Archaeology","score":0.08159759640693665}],"concepts":[{"id":"https://openalex.org/C147103442","wikidata":"https://www.wikidata.org/wiki/Q1423188","display_name":"Forest inventory","level":3,"score":0.8061259984970093},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.7226510643959045},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6680058240890503},{"id":"https://openalex.org/C97137747","wikidata":"https://www.wikidata.org/wiki/Q38112","display_name":"Forestry","level":1,"score":0.5845111608505249},{"id":"https://openalex.org/C117455697","wikidata":"https://www.wikidata.org/wiki/Q190149","display_name":"Photogrammetry","level":2,"score":0.5618910193443298},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.5549983382225037},{"id":"https://openalex.org/C2780674770","wikidata":"https://www.wikidata.org/wiki/Q2266509","display_name":"Hardwood","level":2,"score":0.4727286398410797},{"id":"https://openalex.org/C101000010","wikidata":"https://www.wikidata.org/wiki/Q5033434","display_name":"Canopy","level":2,"score":0.4540749788284302},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4496335983276367},{"id":"https://openalex.org/C39807119","wikidata":"https://www.wikidata.org/wiki/Q1134228","display_name":"Tree canopy","level":3,"score":0.4486161768436432},{"id":"https://openalex.org/C133214962","wikidata":"https://www.wikidata.org/wiki/Q191839","display_name":"Aerial photography","level":2,"score":0.4211667776107788},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.3267233669757843},{"id":"https://openalex.org/C100970517","wikidata":"https://www.wikidata.org/wiki/Q52107","display_name":"Physical geography","level":1,"score":0.3231145441532135},{"id":"https://openalex.org/C28631016","wikidata":"https://www.wikidata.org/wiki/Q372561","display_name":"Forest management","level":2,"score":0.24666109681129456},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.21516737341880798},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.17348265647888184},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.08159759640693665},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs14174386","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14174386","pdf_url":"https://www.mdpi.com/2072-4292/14/17/4386/pdf?version=1662652271","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:e2850d20a2bb4b7b944e7429e34f59a0","is_oa":true,"landing_page_url":"https://doaj.org/article/e2850d20a2bb4b7b944e7429e34f59a0","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 14, Iss 17, p 4386 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/17/4386/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14174386","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","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs14174386","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14174386","pdf_url":"https://www.mdpi.com/2072-4292/14/17/4386/pdf?version=1662652271","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":0.7099999785423279}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306114","display_name":"U.S. Department of Agriculture","ror":"https://ror.org/01na82s61"},{"id":"https://openalex.org/F4320332478","display_name":"U.S. Forest Service","ror":"https://ror.org/03zmjc935"},{"id":"https://openalex.org/F4320337818","display_name":"Rocky Mountain Research Station","ror":"https://ror.org/04347cr60"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4296569550.pdf","grobid_xml":"https://content.openalex.org/works/W4296569550.grobid-xml"},"referenced_works_count":72,"referenced_works":["https://openalex.org/W1272693108","https://openalex.org/W1432478301","https://openalex.org/W1545687845","https://openalex.org/W1615474684","https://openalex.org/W1834239181","https://openalex.org/W1939619463","https://openalex.org/W1967094826","https://openalex.org/W1968165852","https://openalex.org/W1974328142","https://openalex.org/W1981855554","https://openalex.org/W1983374831","https://openalex.org/W1996263757","https://openalex.org/W1998202068","https://openalex.org/W1999601230","https://openalex.org/W2000345291","https://openalex.org/W2010248673","https://openalex.org/W2017131791","https://openalex.org/W2019549520","https://openalex.org/W2028758295","https://openalex.org/W2031419936","https://openalex.org/W2043871384","https://openalex.org/W2057327074","https://openalex.org/W2057913757","https://openalex.org/W2070244059","https://openalex.org/W2076917619","https://openalex.org/W2080401607","https://openalex.org/W2085425336","https://openalex.org/W2090846275","https://openalex.org/W2091939427","https://openalex.org/W2110588562","https://openalex.org/W2116674621","https://openalex.org/W2122450383","https://openalex.org/W2130464813","https://openalex.org/W2134332210","https://openalex.org/W2147499659","https://openalex.org/W2152634225","https://openalex.org/W2161136770","https://openalex.org/W2171204808","https://openalex.org/W2288393565","https://openalex.org/W2416310637","https://openalex.org/W2417240221","https://openalex.org/W2537499819","https://openalex.org/W2561205583","https://openalex.org/W2582847268","https://openalex.org/W2627093455","https://openalex.org/W2758210752","https://openalex.org/W2779722840","https://openalex.org/W2782548987","https://openalex.org/W2785799492","https://openalex.org/W2890377607","https://openalex.org/W2891091873","https://openalex.org/W2901059292","https://openalex.org/W2924496886","https://openalex.org/W2934121071","https://openalex.org/W2940710877","https://openalex.org/W2944750195","https://openalex.org/W2951297504","https://openalex.org/W2957974561","https://openalex.org/W3003421670","https://openalex.org/W3033994816","https://openalex.org/W3088507381","https://openalex.org/W3112246866","https://openalex.org/W3162355627","https://openalex.org/W3166352197","https://openalex.org/W4212863515","https://openalex.org/W4280603148","https://openalex.org/W4293236572","https://openalex.org/W6632615919","https://openalex.org/W6645714515","https://openalex.org/W6653140083","https://openalex.org/W6739597462","https://openalex.org/W6838112396"],"related_works":["https://openalex.org/W2365572566","https://openalex.org/W2394068580","https://openalex.org/W2386046054","https://openalex.org/W608839663","https://openalex.org/W2372478594","https://openalex.org/W2058688210","https://openalex.org/W2989908756","https://openalex.org/W2904216738","https://openalex.org/W2182133515","https://openalex.org/W2040058778"],"abstract_inverted_index":{"The":[0,217,344],"U.S.":[1],"Forest":[2,4],"Service,":[3],"Inventory":[5],"and":[6,14,125,147,152,210,261,282,383],"Analysis":[7],"(FIA)":[8],"program":[9],"is":[10],"tasked":[11],"with":[12,191,203,236,321,329],"making":[13],"reporting":[15],"estimates":[16,32,78,116,168,310,319,359],"of":[17,25,64,92,123,139,157,214,246,267,272,284,347,367,386],"various":[18],"forest":[19,76,166,308,330,395],"attributes":[20,84],"using":[21,144,348,387],"a":[22,37,60,204,265],"design-based":[23],"network":[24],"permanent":[26],"sampling":[27],"plots.":[28],"To":[29],"make":[30],"its":[31],"more":[33,46,224,314,369],"precise,":[34],"FIA":[35,58,148,192,247,262,285,354],"uses":[36,59],"technique":[38],"known":[39],"as":[40],"post-stratification":[41,177,306],"to":[42,72,113,133,163,188,252,291,352,372,391],"group":[43],"plots":[44,371],"into":[45],"homogenous":[47],"classes,":[48],"which":[49,70],"helps":[50],"lower":[51],"variance":[52],"when":[53],"deriving":[54],"population":[55],"means.":[56],"Currently":[57],"nationally":[61],"available":[62],"map":[63,335],"tree":[65,149,196,322],"canopy":[66,323],"cover":[67,324],"for":[68,75,82,226,305,342],"post-stratification,":[69],"tends":[71],"work":[73],"well":[74],"area":[77],"but":[79],"less":[80],"so":[81],"structural":[83],"like":[85],"volume.":[86],"Here":[87],"we":[88],"explore":[89],"the":[90,107,118,136,155,170,182,254,257,294,365,381],"use":[91],"new":[93],"statewide":[94],"digital":[95,159],"aerial":[96],"photogrammetric":[97],"(DAP)":[98],"point":[99,142,184,219,259,389],"clouds":[100,143,185,260,390],"developed":[101],"from":[102,174,333],"stereo":[103],"imagery":[104],"collected":[105],"by":[106,297],"National":[108],"Agricultural":[109],"Imagery":[110],"Program":[111],"(NAIP)":[112],"improve":[114,164,338,392],"these":[115],"in":[117,270,279],"southeastern":[119],"mixed":[120],"hardwood":[121,274],"forests":[122],"Tennessee":[124],"Virginia,":[126],"United":[127],"States":[128],"(U.S.).":[129],"Our":[130,179],"objectives":[131],"are":[132],"1.":[134],"evaluate":[135],"relative":[137],"quality":[138],"NAIP":[140,158,183,218,258,302,327,349,388],"DAP":[141],"airborne":[145],"LiDAR":[146],"height":[150,160,277,350],"measurements,":[151],"2.":[153],"assess":[154],"ability":[156],"models":[161],"(DHMs)":[162],"operational":[165,394],"inventory":[167,396],"above":[169],"gains":[171],"already":[172],"achieved":[173],"FIA\u2019s":[175,393],"current":[176],"approach.":[178],"results":[180,379],"show":[181,380],"were":[186,222,289,312],"moderately":[187],"strongly":[189],"correlated":[190],"field":[193,370],"measured":[194],"maximum":[195],"heights":[197,221],"(average":[198],"Pearson\u2019s":[199],"r":[200],"=":[201,229,234],"0.74)":[202],"slight":[205],"negative":[206],"bias":[207],"(\u22121.56":[208],"m)":[209],"an":[211,237],"RMSE":[212],"error":[213,238],"~4.0":[215],"m.":[216],"cloud":[220],"also":[223],"accurate":[225],"softwoods":[227],"(R2s":[228,233],"0.60\u20130.79)":[230],"than":[231,318],"hardwoods":[232],"0.33\u20130.50)":[235],"structure":[239],"that":[240,311],"was":[241,360],"consistent":[242],"across":[243],"multiple":[244],"years":[245],"measurements.":[248],"Several":[249],"factors":[250],"served":[251],"degrade":[253],"relationship":[255],"between":[256],"data,":[263],"including":[264],"lack":[266],"3D":[268],"points":[269],"areas":[271],"advanced":[273],"senescence,":[275],"spurious":[276],"values":[278],"deep":[280],"shadows":[281],"imprecision":[283],"plot":[286],"locations":[287,296],"(which":[288],"estimated":[290],"be":[292],"off":[293],"true":[295],"+/\u2212":[298],"8":[299],"m).":[300],"Using":[301],"strata":[303],"maps":[304,351],"yielded":[307],"volume":[309,358],"31%":[313],"precise":[315],"on":[316],"average":[317],"stratified":[320],"data.":[325],"Combining":[326],"DHMs":[328],"type":[331],"information":[332],"national":[334],"products":[336],"helped":[337],"stratification":[339],"performance,":[340],"especially":[341],"softwoods.":[343],"monetary":[345],"value":[346],"post-stratify":[353],"survey":[355],"unit":[356],"total":[357],"USD":[361],"1.8":[362],"million":[363],"vs.":[364],"costs":[366],"installing":[368],"achieve":[373],"similar":[374],"precision":[375],"gains.":[376],"Overall,":[377],"our":[378],"benefit":[382],"growing":[384],"feasibility":[385],"estimates.":[397]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}
