{"id":"https://openalex.org/W3119735510","doi":"https://doi.org/10.3390/rs13020218","title":"Random Forest Regression Model for Estimation of the Growing Stock Volumes in Georgia, USA, Using Dense Landsat Time Series and FIA Dataset","display_name":"Random Forest Regression Model for Estimation of the Growing Stock Volumes in Georgia, USA, Using Dense Landsat Time Series and FIA Dataset","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3119735510","doi":"https://doi.org/10.3390/rs13020218","mag":"3119735510"},"language":"en","primary_location":{"id":"doi:10.3390/rs13020218","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13020218","pdf_url":"https://www.mdpi.com/2072-4292/13/2/218/pdf?version=1610931465","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/2072-4292/13/2/218/pdf?version=1610931465","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","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/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":true,"raw_author_name":"Shingo Obata","raw_affiliation_strings":["National Institute for Mathematical and Biological Synthesis, 1122 Volunteer Blvd., University of Tennessee, Knoxville, TN 37996, USA"],"affiliations":[{"raw_affiliation_string":"National Institute for Mathematical and Biological Synthesis, 1122 Volunteer Blvd., University of Tennessee, Knoxville, TN 37996, USA","institution_ids":["https://openalex.org/I122345529","https://openalex.org/I75027704"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008181657","display_name":"Chris J. Cieszewski","orcid":"https://orcid.org/0000-0003-2842-4406"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chris J. Cieszewski","raw_affiliation_strings":["Warnell School of Forestry and Natural Resources, University of Georgia, 180 E Green St., Athens, GA 30602, USA"],"affiliations":[{"raw_affiliation_string":"Warnell School of Forestry and Natural Resources, University of Georgia, 180 E Green St., Athens, GA 30602, USA","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007900007","display_name":"Roger C. Lowe","orcid":"https://orcid.org/0000-0002-4770-9936"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Roger C. Lowe","raw_affiliation_strings":["Warnell School of Forestry and Natural Resources, University of Georgia, 180 E Green St., Athens, GA 30602, USA"],"affiliations":[{"raw_affiliation_string":"Warnell School of Forestry and Natural Resources, University of Georgia, 180 E Green St., Athens, GA 30602, USA","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045879211","display_name":"Pete Bettinger","orcid":"https://orcid.org/0000-0002-5454-3970"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pete Bettinger","raw_affiliation_strings":["Warnell School of Forestry and Natural Resources, University of Georgia, 180 E Green St., Athens, GA 30602, USA"],"affiliations":[{"raw_affiliation_string":"Warnell School of Forestry and Natural Resources, University of Georgia, 180 E Green St., Athens, GA 30602, USA","institution_ids":["https://openalex.org/I165733156"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5078575077"],"corresponding_institution_ids":["https://openalex.org/I122345529","https://openalex.org/I75027704"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":2.3711,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.8740421,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"13","issue":"2","first_page":"218","last_page":"218"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"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":0.9991000294685364,"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/random-forest","display_name":"Random forest","score":0.6515976190567017},{"id":"https://openalex.org/keywords/forest-inventory","display_name":"Forest inventory","score":0.598421037197113},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5836852192878723},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.553752064704895},{"id":"https://openalex.org/keywords/satellite-imagery","display_name":"Satellite imagery","score":0.5189637541770935},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.4965711236000061},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.46772301197052},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4496387839317322},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.43090540170669556},{"id":"https://openalex.org/keywords/ancillary-data","display_name":"Ancillary data","score":0.4176279604434967},{"id":"https://openalex.org/keywords/raster-data","display_name":"Raster data","score":0.41541174054145813},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4153367280960083},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3318437933921814},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.3146028518676758},{"id":"https://openalex.org/keywords/raster-graphics","display_name":"Raster graphics","score":0.2881244719028473},{"id":"https://openalex.org/keywords/forest-management","display_name":"Forest management","score":0.2862672209739685},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.23031365871429443},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16755136847496033},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.10567519068717957}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6515976190567017},{"id":"https://openalex.org/C147103442","wikidata":"https://www.wikidata.org/wiki/Q1423188","display_name":"Forest inventory","level":3,"score":0.598421037197113},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5836852192878723},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.553752064704895},{"id":"https://openalex.org/C2778102629","wikidata":"https://www.wikidata.org/wiki/Q725252","display_name":"Satellite imagery","level":2,"score":0.5189637541770935},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.4965711236000061},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.46772301197052},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4496387839317322},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.43090540170669556},{"id":"https://openalex.org/C2780408538","wikidata":"https://www.wikidata.org/wiki/Q3615217","display_name":"Ancillary data","level":2,"score":0.4176279604434967},{"id":"https://openalex.org/C2692088","wikidata":"https://www.wikidata.org/wiki/Q182270","display_name":"Raster data","level":3,"score":0.41541174054145813},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4153367280960083},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3318437933921814},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.3146028518676758},{"id":"https://openalex.org/C181844469","wikidata":"https://www.wikidata.org/wiki/Q182270","display_name":"Raster graphics","level":2,"score":0.2881244719028473},{"id":"https://openalex.org/C28631016","wikidata":"https://www.wikidata.org/wiki/Q372561","display_name":"Forest management","level":2,"score":0.2862672209739685},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.23031365871429443},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16755136847496033},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.10567519068717957},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C54286561","wikidata":"https://www.wikidata.org/wiki/Q397350","display_name":"Agroforestry","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","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},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs13020218","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13020218","pdf_url":"https://www.mdpi.com/2072-4292/13/2/218/pdf?version=1610931465","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:e57bd55387e347cc9050d03d81f956ee","is_oa":true,"landing_page_url":"https://doaj.org/article/e57bd55387e347cc9050d03d81f956ee","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 13, Iss 2, p 218 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/13/2/218/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs13020218","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 13; Issue 2; Pages: 218","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs13020218","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13020218","pdf_url":"https://www.mdpi.com/2072-4292/13/2/218/pdf?version=1610931465","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":[{"display_name":"Life in Land","score":0.75,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3119735510.pdf","grobid_xml":"https://content.openalex.org/works/W3119735510.grobid-xml"},"referenced_works_count":64,"referenced_works":["https://openalex.org/W1544274373","https://openalex.org/W1615474684","https://openalex.org/W1677562123","https://openalex.org/W1970024833","https://openalex.org/W1974328142","https://openalex.org/W1981139388","https://openalex.org/W1989726747","https://openalex.org/W2002057634","https://openalex.org/W2006429183","https://openalex.org/W2012519352","https://openalex.org/W2025745000","https://openalex.org/W2028240797","https://openalex.org/W2031600437","https://openalex.org/W2035466979","https://openalex.org/W2037202266","https://openalex.org/W2038993404","https://openalex.org/W2055718260","https://openalex.org/W2065253570","https://openalex.org/W2082201041","https://openalex.org/W2085316211","https://openalex.org/W2086620533","https://openalex.org/W2090491989","https://openalex.org/W2093349640","https://openalex.org/W2101234009","https://openalex.org/W2110588562","https://openalex.org/W2126250722","https://openalex.org/W2130037317","https://openalex.org/W2139709933","https://openalex.org/W2151456308","https://openalex.org/W2155863249","https://openalex.org/W2163241395","https://openalex.org/W2167250466","https://openalex.org/W2175899267","https://openalex.org/W2213155418","https://openalex.org/W2260602653","https://openalex.org/W2346766736","https://openalex.org/W2414009932","https://openalex.org/W2555220256","https://openalex.org/W2605847660","https://openalex.org/W2618417257","https://openalex.org/W2624854028","https://openalex.org/W2725897987","https://openalex.org/W2769828489","https://openalex.org/W2772370991","https://openalex.org/W2788340823","https://openalex.org/W2790602384","https://openalex.org/W2886463967","https://openalex.org/W2891091873","https://openalex.org/W2891721681","https://openalex.org/W2899059867","https://openalex.org/W2901960699","https://openalex.org/W2911964244","https://openalex.org/W2934832248","https://openalex.org/W2937955301","https://openalex.org/W2944366268","https://openalex.org/W2972261980","https://openalex.org/W2997047947","https://openalex.org/W3011249784","https://openalex.org/W4212863515","https://openalex.org/W4212883601","https://openalex.org/W6675354045","https://openalex.org/W6746475178","https://openalex.org/W6755774386","https://openalex.org/W6767914843"],"related_works":["https://openalex.org/W2137644361","https://openalex.org/W4384500538","https://openalex.org/W2247125043","https://openalex.org/W2043913960","https://openalex.org/W961966657","https://openalex.org/W4385799572","https://openalex.org/W2175899267","https://openalex.org/W2415454320","https://openalex.org/W2587035872","https://openalex.org/W4385362411"],"abstract_inverted_index":{"The":[0,229,334,354,388,456],"forest":[1,20,44,118,375],"volumes":[2],"are":[3,7,475],"essential":[4],"as":[5,125,186,226,350,378],"they":[6],"directly":[8],"related":[9],"to":[10,52,96,105,113,137,143,251,267,272,326,370,408,477],"the":[11,17,27,30,33,42,54,60,67,72,86,99,106,109,115,130,133,139,145,148,156,179,182,207,216,232,253,256,269,274,277,280,283,287,293,300,317,321,331,339,346,351,358,361,371,393,397,400,403,410,418,427,437,440,452,468,472,479],"economic":[12],"and":[13,29,58,71,121,135,164,181,198,215,221,289,299,305,311,417,451,465],"environmental":[14],"values":[15,184,188,291,307],"of":[16,32,41,66,74,82,108,117,132,147,161,211,231,276,292,308,360,396,402,429,458,467,471],"forests.":[18],"Satellite-based":[19],"volume":[21,45,56,62],"estimation":[22,34,46,110],"was":[23,172,235,264,324],"first":[24],"developed":[25],"in":[26,85,178,189,399],"1990s,":[28],"accuracy":[31,131],"has":[35],"been":[36],"improved":[37],"over":[38],"time.":[39],"One":[40],"satellite-based":[43],"issues":[47],"is":[48],"that":[49,336,357],"it":[50],"tends":[51],"overestimate":[53],"large":[55],"class":[57],"underestimate":[59],"small":[61],"class.":[63],"Free":[64],"availability":[65,457],"major":[68],"satellite":[69,83],"imagery":[70,84],"development":[73],"cloud-based":[75],"computational":[76],"platforms":[77],"facilitate":[78],"an":[79],"immense":[80],"amount":[81],"estimation.":[87,149],"In":[88],"this":[89,449],"paper,":[90],"we":[91,446],"set":[92],"three":[93,152],"objectives:":[94],"(1)":[95],"examine":[97,273],"whether":[98],"long":[100,165,312,340,362],"Landsat":[101,157,295,313,363],"time":[102,167,296,314,341,364,441],"series":[103,297,342,365,442],"contributes":[104],"improvement":[107],"accuracy,":[111],"(2)":[112],"explore":[114],"effectiveness":[116,275],"disturbance":[119,222,376],"record":[120],"land":[122],"cover":[123],"data":[124,128,158,170,224,234,343,377,445,464,474],"ancillary":[126,227],"spatial":[127],"on":[129,386,426],"estimation,":[134],"(3)":[136],"apply":[138],"bias":[140,146,261,389,398,413,421],"correction":[141,262,390],"method":[142,263,391],"reduce":[144],"We":[150],"computed":[151,447],"Tasseled-cap":[153],"components":[154],"from":[155,406],"for":[159,448],"preparation":[160],"short":[162,294,310],"(2014\u20132016)":[163],"(1984\u20132016)":[166],"series.":[168,315],"Each":[169],"entity":[171],"analyzed":[173],"with":[174,244,255],"harmonic":[175],"regressions":[176],"resulting":[177],"coefficients":[180,288,304],"fitted":[183,290,306],"recorded":[185],"pixel":[187],"a":[190,379],"multilayer":[191],"raster":[192],"database.":[193],"Data":[194],"included":[195],"Forest":[196,213,241],"Inventory":[197],"Analysis":[199],"(FIA)":[200],"unit":[201],"field":[202],"inventory":[203],"measurements":[204],"provided":[205],"by":[206,414,422],"United":[208],"States":[209],"Department":[210],"Agriculture":[212],"Service":[214],"National":[217],"Land":[218],"Cover":[219],"Database":[220],"history":[223],"added":[225],"information.":[228],"totality":[230],"available":[233],"organized":[236],"into":[237],"seven":[238,281],"distinct":[239],"Random":[240],"(RF)":[242],"models":[243,271],"different":[245],"variables":[246,433],"compared":[247],"against":[248],"each":[249],"other":[250],"identify":[252],"ones":[254],"most":[257],"satisfactory":[258],"performance.":[259,368],"A":[260],"then":[265],"applied":[266],"all":[268],"RF":[270],"method.":[278],"Among":[279],"models,":[282],"worst":[284,332],"one":[285,302],"used":[286,303,337],"only,":[298],"best":[301,322,352,404],"both":[309],"Using":[316],"Out-of-bag":[318],"(OOB)":[319],"score,":[320],"model":[323,335,367,405,480],"found":[325],"be":[327],"34.4%":[328],"better":[329],"than":[330],"one.":[333],"only":[338],"had":[344,382],"almost":[345,383],"same":[347],"OOB":[348],"score":[349],"model.":[353],"results":[355],"indicate":[356],"use":[359],"improves":[366],"Contrary":[369],"previous":[372],"research":[373,450],"employing":[374],"feature":[380,432],"variable":[381],"no":[384],"effect":[385],"OOB.":[387],"reduced":[392],"relative":[394],"size":[395],"estimates":[401,481],"3.79%":[407],"\u22121.47%,":[409],"bottom":[411],"10%":[412,420],"12.5":[415],"points,":[416],"top":[419],"9.9":[423],"points.":[424],"Depending":[425],"types":[428],"forest,":[430],"important":[431],"were":[434],"differed,":[435],"reflecting":[436],"relationship":[438],"between":[439],"remote":[443],"sensing":[444],"forests\u2019":[453],"phenological":[454],"characteristics.":[455],"Light":[459],"Detection":[460],"And":[461],"Ranging":[462],"(LiDAR)":[463],"accessibility":[466],"precise":[469],"locations":[470],"FIA":[473],"likely":[476],"improve":[478],"further.":[482]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
