iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://api.openalex.org/works/doi:10.3390/RS14061477
{"id":"https://openalex.org/W4221042712","doi":"https://doi.org/10.3390/rs14061477","title":"Combining Sample Plot Stratification and Machine Learning Algorithms to Improve Forest Aboveground Carbon Density Estimation in Northeast China Using Airborne LiDAR Data","display_name":"Combining Sample Plot Stratification and Machine Learning Algorithms to Improve Forest Aboveground Carbon Density Estimation in Northeast China Using Airborne LiDAR Data","publication_year":2022,"publication_date":"2022-03-18","ids":{"openalex":"https://openalex.org/W4221042712","doi":"https://doi.org/10.3390/rs14061477"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14061477","pdf_url":"https://www.mdpi.com/2072-4292/14/6/1477/pdf?version=1647917823","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},"type":"article","type_crossref":"journal-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/14/6/1477/pdf?version=1647917823","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002848127","display_name":"Mingjie Chen","orcid":"https://orcid.org/0000-0002-9955-637X"},"institutions":[{"id":"https://openalex.org/I31683504","display_name":"Beijing Forestry University","ror":"https://ror.org/04xv2pc41","country_code":"CN","type":"education","lineage":["https://openalex.org/I1327237609","https://openalex.org/I31683504","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I4210134523","display_name":"State Forestry and Grassland Administration","ror":"https://ror.org/03f2n3n81","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210134523"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingjie Chen","raw_affiliation_strings":["State Forestry and Grassland Administration Key Laboratory of Forest Resources & Environmental Management, College of Forestry, Beijing Forestry University, Beijing 100083, China"],"affiliations":[{"raw_affiliation_string":"State Forestry and Grassland Administration Key Laboratory of Forest Resources & Environmental Management, College of Forestry, Beijing Forestry University, Beijing 100083, China","institution_ids":["https://openalex.org/I31683504","https://openalex.org/I4210134523"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083264274","display_name":"Xincai Qiu","orcid":null},"institutions":[{"id":"https://openalex.org/I20942203","display_name":"Hainan University","ror":"https://ror.org/03q648j11","country_code":"CN","type":"education","lineage":["https://openalex.org/I20942203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xincai Qiu","raw_affiliation_strings":["Intelligent Forestry Key Laboratory of Haikou City, College of Forestry, Hainan University, Haikou 570228, China"],"affiliations":[{"raw_affiliation_string":"Intelligent Forestry Key Laboratory of Haikou City, College of Forestry, Hainan University, Haikou 570228, China","institution_ids":["https://openalex.org/I20942203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075454983","display_name":"Weisheng Zeng","orcid":"https://orcid.org/0000-0002-5462-0737"},"institutions":[{"id":"https://openalex.org/I4210134523","display_name":"State Forestry and Grassland Administration","ror":"https://ror.org/03f2n3n81","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210134523"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weisheng Zeng","raw_affiliation_strings":["Academy of Inventory and Planning, National Forestry and Grassland Administration, Beijing 100714, China"],"affiliations":[{"raw_affiliation_string":"Academy of Inventory and Planning, National Forestry and Grassland Administration, Beijing 100714, China","institution_ids":["https://openalex.org/I4210134523"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113466052","display_name":"Peng Dao-li","orcid":null},"institutions":[{"id":"https://openalex.org/I31683504","display_name":"Beijing Forestry University","ror":"https://ror.org/04xv2pc41","country_code":"CN","type":"education","lineage":["https://openalex.org/I1327237609","https://openalex.org/I31683504","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I4210134523","display_name":"State Forestry and Grassland Administration","ror":"https://ror.org/03f2n3n81","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210134523"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Daoli Peng","raw_affiliation_strings":["State Forestry and Grassland Administration Key Laboratory of Forest Resources & Environmental Management, College of Forestry, Beijing Forestry University, Beijing 100083, China"],"affiliations":[{"raw_affiliation_string":"State Forestry and Grassland Administration Key Laboratory of Forest Resources & Environmental Management, College of Forestry, Beijing Forestry University, Beijing 100083, China","institution_ids":["https://openalex.org/I31683504","https://openalex.org/I4210134523"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5113466052"],"corresponding_institution_ids":["https://openalex.org/I31683504","https://openalex.org/I4210134523"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707,"provenance":"doaj"},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707,"provenance":"doaj"},"fwci":1.74,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.999886,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":95},"biblio":{"volume":"14","issue":"6","first_page":"1477","last_page":"1477"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9999,"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":0.9999,"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":0.9994,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9952,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/stratification","display_name":"Stratification (seeds)","score":0.75545204},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.56602484},{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.4233621}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.794312},{"id":"https://openalex.org/C192943249","wikidata":"https://www.wikidata.org/wiki/Q1893382","display_name":"Stratification (seeds)","level":5,"score":0.75545204},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.6242387},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5737988},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.56602484},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.4956423},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48940244},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.4233621},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3591993},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.33197576},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32496926},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23989952},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1173982},{"id":"https://openalex.org/C88548481","wikidata":"https://www.wikidata.org/wiki/Q2397491","display_name":"Seed dormancy","level":4,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C100701293","wikidata":"https://www.wikidata.org/wiki/Q193838","display_name":"Germination","level":2,"score":0.0},{"id":"https://openalex.org/C3527866","wikidata":"https://www.wikidata.org/wiki/Q162267","display_name":"Dormancy","level":3,"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":1,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14061477","pdf_url":"https://www.mdpi.com/2072-4292/14/6/1477/pdf?version=1647917823","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}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14061477","pdf_url":"https://www.mdpi.com/2072-4292/14/6/1477/pdf?version=1647917823","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},"sustainable_development_goals":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.56}],"grants":[{"funder":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China","award_id":"2016YFD-0600205"}],"datasets":[],"versions":[],"referenced_works_count":96,"referenced_works":["https://openalex.org/W1975521562","https://openalex.org/W1978642993","https://openalex.org/W1986964304","https://openalex.org/W2001108422","https://openalex.org/W2002730835","https://openalex.org/W2004520553","https://openalex.org/W2008812878","https://openalex.org/W2012519352","https://openalex.org/W2017253904","https://openalex.org/W2028901390","https://openalex.org/W2035118832","https://openalex.org/W2047744778","https://openalex.org/W2056968878","https://openalex.org/W2063335319","https://openalex.org/W2069959013","https://openalex.org/W2073163280","https://openalex.org/W2085520997","https://openalex.org/W2086461898","https://openalex.org/W2087674734","https://openalex.org/W2094365596","https://openalex.org/W2101748122","https://openalex.org/W2109631166","https://openalex.org/W2111078849","https://openalex.org/W2113249705","https://openalex.org/W2113551198","https://openalex.org/W2114228414","https://openalex.org/W2120634709","https://openalex.org/W2121816206","https://openalex.org/W2131347664","https://openalex.org/W2133613984","https://openalex.org/W2137933418","https://openalex.org/W2150026442","https://openalex.org/W2153601600","https://openalex.org/W2155236826","https://openalex.org/W2156665896","https://openalex.org/W2167083595","https://openalex.org/W2170591795","https://openalex.org/W2211054202","https://openalex.org/W2288583194","https://openalex.org/W2295598076","https://openalex.org/W2322716129","https://openalex.org/W2416310637","https://openalex.org/W2474435807","https://openalex.org/W2508131240","https://openalex.org/W2566759027","https://openalex.org/W2587679259","https://openalex.org/W2589073448","https://openalex.org/W2596636264","https://openalex.org/W2605270904","https://openalex.org/W2763240495","https://openalex.org/W2769933020","https://openalex.org/W2789860026","https://openalex.org/W2793370749","https://openalex.org/W2794636625","https://openalex.org/W2800536838","https://openalex.org/W2801958376","https://openalex.org/W2802682635","https://openalex.org/W2809592418","https://openalex.org/W2883153512","https://openalex.org/W2883666593","https://openalex.org/W2884983756","https://openalex.org/W2895702307","https://openalex.org/W2900062227","https://openalex.org/W2911964244","https://openalex.org/W2914965988","https://openalex.org/W2928790886","https://openalex.org/W2932183390","https://openalex.org/W2942851257","https://openalex.org/W2943125170","https://openalex.org/W2945335841","https://openalex.org/W2946533443","https://openalex.org/W2951297504","https://openalex.org/W2956039922","https://openalex.org/W2965977570","https://openalex.org/W2966381923","https://openalex.org/W2969455580","https://openalex.org/W2980571983","https://openalex.org/W2984835294","https://openalex.org/W3002443255","https://openalex.org/W3009288410","https://openalex.org/W3015115077","https://openalex.org/W3020552235","https://openalex.org/W3035803741","https://openalex.org/W3047943663","https://openalex.org/W3094948551","https://openalex.org/W3112661396","https://openalex.org/W3125025235","https://openalex.org/W3125877605","https://openalex.org/W3130219998","https://openalex.org/W3152432465","https://openalex.org/W3153946926","https://openalex.org/W3158692511","https://openalex.org/W3164832080","https://openalex.org/W3186852258","https://openalex.org/W3192946819","https://openalex.org/W84227776"],"related_works":["https://openalex.org/W4379536929","https://openalex.org/W4313906961","https://openalex.org/W4298144988","https://openalex.org/W4212956667","https://openalex.org/W3216682471","https://openalex.org/W3211193619","https://openalex.org/W3208169454","https://openalex.org/W3201348321","https://openalex.org/W3177321454","https://openalex.org/W2950005168"],"abstract_inverted_index":{"Timely,":[0],"accurate":[1],"estimates":[2],"of":[3,69,97,148,173,238,266,272,284,299],"forest":[4,39,63,86,102,118,139,257,285,292,300],"aboveground":[5],"carbon":[6,15,301],"density":[7],"(AGC)":[8],"are":[9],"essential":[10],"for":[11,22,38,138],"understanding":[12],"the":[13,33,54,58,62,67,131,157,165,171,178,187,209,216,239,244,253,263,270,275,281,297],"global":[14],"cycle":[16],"and":[17,60,71,77,106,111,125,135,155,208,232,268,274],"providing":[18],"crucial":[19],"reference":[20],"information":[21],"climate-change-related":[23],"policies.":[24],"To":[25],"date,":[26],"airborne":[27,143],"LiDAR":[28,144],"has":[29,53],"been":[30,82],"considered":[31],"as":[32],"most":[34],"precise":[35],"remote-sensing-based":[36],"technology":[37],"AGC":[40,64,87,140,258],"estimation,":[41,141],"but":[42],"it":[43],"suffers":[44],"great":[45],"challenges":[46],"from":[47],"various":[48],"uncertainty":[49,59],"sources.":[50],"Stratified":[51],"estimation":[52,166,175,183,218,282],"potential":[55],"to":[56,73,129,153],"reduce":[57],"improve":[61,280,296],"estimation.":[65,88,259],"However,":[66],"impact":[68],"stratification":[70,76,99,104,109,133,245,267],"how":[72,269],"effectively":[74,279],"combine":[75],"modeling":[78,113,136],"algorithms":[79,114,204],"have":[80],"not":[81],"fully":[83],"investigated":[84],"in":[85,196,256],"In":[89],"this":[90,191,288],"study,":[91],"we":[92],"performed":[93],"a":[94,161,248],"comparative":[95],"analysis":[96,147],"different":[98,112],"approaches":[100],"(non-stratification,":[101],"type":[103],"(FTS)":[105],"dominant":[107],"species":[108,198],"(DSS))":[110],"(stepwise":[115],"regression,":[116],"random":[117],"(RF),":[119],"Cubist,":[120],"extreme":[121],"gradient":[122],"boosting":[123,127],"(XGBoost)":[124],"categorical":[126],"(CatBoost))":[128],"identify":[130],"optimal":[132],"approach":[134],"algorithm":[137,255,277],"using":[142],"data.":[145],"The":[146,168,202,236],"variance":[149],"(ANOVA)":[150],"was":[151,193,247],"used":[152],"quantify":[154],"determine":[156],"factors":[158],"that":[159,243],"had":[160],"significant":[162,195],"effect":[163,265],"on":[164,213],"accuracy.":[167],"results":[169],"revealed":[170],"superiority":[172],"stratified":[174],"models":[176,211],"over":[177,303],"unstratified":[179],"ones,":[180],"with":[181,290],"higher":[182],"accuracy":[184,219,283],"achieved":[185],"by":[186],"DSS":[188,214,273],"models.":[189],"Moreover,":[190],"improvement":[192],"more":[194,249],"coniferous":[197],"than":[199,252],"broadleaf":[200],"species.":[201],"ML":[203],"outperformed":[205],"stepwise":[206],"regression":[207,254],"CatBoost":[210,276],"based":[212],"provided":[215],"highest":[217],"(R2":[220],"=":[221,224,227,230,234],"0.8232,":[222],"RMSE":[223],"5.2421,":[225],"RRMSE":[226],"20.5680,":[228],"MAE":[229],"4.0169":[231],"Bias":[233],"0.4493).":[235],"ANOVA":[237],"prediction":[240],"error":[241],"indicated":[242],"method":[246],"important":[250],"factor":[251],"This":[260],"study":[261],"demonstrated":[262],"positive":[264],"combination":[271],"can":[278],"AGC.":[286],"Integrating":[287],"strategy":[289],"national":[291],"inventory":[293],"could":[294],"help":[295],"monitoring":[298],"stock":[302],"large":[304],"areas.":[305]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4221042712","counts_by_year":[{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":4}],"updated_date":"2024-12-08T16:10:57.174674","created_date":"2022-04-03"}