{"id":"https://openalex.org/W2932477389","doi":"https://doi.org/10.3390/rs11070738","title":"Improving Aboveground Biomass Estimation of Pinus densata Forests in Yunnan Using Landsat 8 Imagery by Incorporating Age Dummy Variable and Method Comparison","display_name":"Improving Aboveground Biomass Estimation of Pinus densata Forests in Yunnan Using Landsat 8 Imagery by Incorporating Age Dummy Variable and Method Comparison","publication_year":2019,"publication_date":"2019-03-27","ids":{"openalex":"https://openalex.org/W2932477389","doi":"https://doi.org/10.3390/rs11070738","mag":"2932477389"},"language":"en","primary_location":{"id":"doi:10.3390/rs11070738","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11070738","pdf_url":"https://www.mdpi.com/2072-4292/11/7/738/pdf?version=1553671239","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/2072-4292/11/7/738/pdf?version=1553671239","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101506717","display_name":"Guanglong Ou","orcid":"https://orcid.org/0000-0003-1925-6690"},"institutions":[{"id":"https://openalex.org/I25399270","display_name":"Southwest Forestry University","ror":"https://ror.org/03dfa9f06","country_code":"CN","type":"education","lineage":["https://openalex.org/I25399270"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanglong Ou","raw_affiliation_strings":["Key Laboratory of State Forestry Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650224, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of State Forestry Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650224, China","institution_ids":["https://openalex.org/I25399270"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100323174","display_name":"Chao Li","orcid":"https://orcid.org/0000-0002-2099-1142"},"institutions":[{"id":"https://openalex.org/I25399270","display_name":"Southwest Forestry University","ror":"https://ror.org/03dfa9f06","country_code":"CN","type":"education","lineage":["https://openalex.org/I25399270"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Li","raw_affiliation_strings":["Key Laboratory of State Forestry Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650224, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of State Forestry Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650224, China","institution_ids":["https://openalex.org/I25399270"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066543614","display_name":"Yanyu Lv","orcid":null},"institutions":[{"id":"https://openalex.org/I25399270","display_name":"Southwest Forestry University","ror":"https://ror.org/03dfa9f06","country_code":"CN","type":"education","lineage":["https://openalex.org/I25399270"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanyu Lv","raw_affiliation_strings":["Key Laboratory of State Forestry Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650224, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of State Forestry Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650224, China","institution_ids":["https://openalex.org/I25399270"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002414763","display_name":"Anchao Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I25399270","display_name":"Southwest Forestry University","ror":"https://ror.org/03dfa9f06","country_code":"CN","type":"education","lineage":["https://openalex.org/I25399270"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Anchao Wei","raw_affiliation_strings":["Key Laboratory of State Forestry Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650224, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of State Forestry Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650224, China","institution_ids":["https://openalex.org/I25399270"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058044904","display_name":"Xiong Hexian","orcid":null},"institutions":[{"id":"https://openalex.org/I25399270","display_name":"Southwest Forestry University","ror":"https://ror.org/03dfa9f06","country_code":"CN","type":"education","lineage":["https://openalex.org/I25399270"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hexian Xiong","raw_affiliation_strings":["Key Laboratory of State Forestry Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650224, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of State Forestry Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650224, China","institution_ids":["https://openalex.org/I25399270"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101775813","display_name":"Hui Xu","orcid":"https://orcid.org/0000-0001-6913-6043"},"institutions":[{"id":"https://openalex.org/I25399270","display_name":"Southwest Forestry University","ror":"https://ror.org/03dfa9f06","country_code":"CN","type":"education","lineage":["https://openalex.org/I25399270"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hui Xu","raw_affiliation_strings":["Key Laboratory of State Forestry Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650224, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of State Forestry Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650224, China","institution_ids":["https://openalex.org/I25399270"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086878627","display_name":"Guangxing Wang","orcid":"https://orcid.org/0000-0002-5419-4547"},"institutions":[{"id":"https://openalex.org/I110378019","display_name":"Southern Illinois University Carbondale","ror":"https://ror.org/049kefs16","country_code":"US","type":"education","lineage":["https://openalex.org/I110378019","https://openalex.org/I2801502357"]},{"id":"https://openalex.org/I25399270","display_name":"Southwest Forestry University","ror":"https://ror.org/03dfa9f06","country_code":"CN","type":"education","lineage":["https://openalex.org/I25399270"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Guangxing Wang","raw_affiliation_strings":["Department of Geography, Southern Illinois University, Carbondale, IL 62901, USA","Key Laboratory of State Forestry Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650224, China"],"affiliations":[{"raw_affiliation_string":"Department of Geography, Southern Illinois University, Carbondale, IL 62901, USA","institution_ids":["https://openalex.org/I110378019"]},{"raw_affiliation_string":"Key Laboratory of State Forestry Administration on Biodiversity Conservation in Southwest China, Southwest Forestry University, Kunming 650224, China","institution_ids":["https://openalex.org/I25399270"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5101775813"],"corresponding_institution_ids":["https://openalex.org/I25399270"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":2.7462,"has_fulltext":true,"cited_by_count":53,"citation_normalized_percentile":{"value":0.88990826,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"11","issue":"7","first_page":"738","last_page":"738"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9977999925613403,"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":0.5613510012626648},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.5233917832374573},{"id":"https://openalex.org/keywords/canopy","display_name":"Canopy","score":0.5225224494934082},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.51636803150177},{"id":"https://openalex.org/keywords/pinus-genus","display_name":"Pinus <genus>","score":0.5116784572601318},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.44652488827705383},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.42359888553619385},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.41427022218704224},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.21450188755989075},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.19809868931770325},{"id":"https://openalex.org/keywords/botany","display_name":"Botany","score":0.09098276495933533},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.08411383628845215}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5613510012626648},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.5233917832374573},{"id":"https://openalex.org/C101000010","wikidata":"https://www.wikidata.org/wiki/Q5033434","display_name":"Canopy","level":2,"score":0.5225224494934082},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.51636803150177},{"id":"https://openalex.org/C2910048773","wikidata":"https://www.wikidata.org/wiki/Q1924659","display_name":"Pinus <genus>","level":2,"score":0.5116784572601318},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.44652488827705383},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.42359888553619385},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41427022218704224},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.21450188755989075},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.19809868931770325},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.09098276495933533},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.08411383628845215},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","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/rs11070738","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11070738","pdf_url":"https://www.mdpi.com/2072-4292/11/7/738/pdf?version=1553671239","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:7ac0915777974278b25dc1ce21ec43ed","is_oa":true,"landing_page_url":"https://doaj.org/article/7ac0915777974278b25dc1ce21ec43ed","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 11, Iss 7, p 738 (2019)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/11/7/738/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs11070738","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 11; Issue 7; Pages: 738","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs11070738","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11070738","pdf_url":"https://www.mdpi.com/2072-4292/11/7/738/pdf?version=1553671239","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":0.7599999904632568}],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4020255992","display_name":null,"funder_award_id":"Project","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5199044421","display_name":null,"funder_award_id":"31660202","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5400045994","display_name":null,"funder_award_id":"31770677","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7382107429","display_name":null,"funder_award_id":"201404","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7608752429","display_name":null,"funder_award_id":"Talent","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326701","display_name":"Recruitment Program of Global Experts","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2932477389.pdf","grobid_xml":"https://content.openalex.org/works/W2932477389.grobid-xml"},"referenced_works_count":92,"referenced_works":["https://openalex.org/W1177863458","https://openalex.org/W1966689649","https://openalex.org/W1969910334","https://openalex.org/W1969986265","https://openalex.org/W1970253947","https://openalex.org/W1974328142","https://openalex.org/W1974476774","https://openalex.org/W1975521562","https://openalex.org/W1977761893","https://openalex.org/W1981855554","https://openalex.org/W1992709528","https://openalex.org/W1995341919","https://openalex.org/W1996855919","https://openalex.org/W1998442441","https://openalex.org/W2006429183","https://openalex.org/W2008674189","https://openalex.org/W2010688372","https://openalex.org/W2012519352","https://openalex.org/W2029632022","https://openalex.org/W2032541606","https://openalex.org/W2038993404","https://openalex.org/W2039579272","https://openalex.org/W2040120109","https://openalex.org/W2041550093","https://openalex.org/W2045626198","https://openalex.org/W2046443332","https://openalex.org/W2047744778","https://openalex.org/W2047933096","https://openalex.org/W2049070397","https://openalex.org/W2055162110","https://openalex.org/W2059663113","https://openalex.org/W2061427081","https://openalex.org/W2063907334","https://openalex.org/W2070536167","https://openalex.org/W2071215415","https://openalex.org/W2072139589","https://openalex.org/W2075049524","https://openalex.org/W2076867991","https://openalex.org/W2077116289","https://openalex.org/W2077799957","https://openalex.org/W2079454091","https://openalex.org/W2084936455","https://openalex.org/W2088409791","https://openalex.org/W2093540905","https://openalex.org/W2098630016","https://openalex.org/W2099252418","https://openalex.org/W2103394375","https://openalex.org/W2104830773","https://openalex.org/W2105593416","https://openalex.org/W2105770001","https://openalex.org/W2109631166","https://openalex.org/W2113249705","https://openalex.org/W2117706739","https://openalex.org/W2123574709","https://openalex.org/W2124837560","https://openalex.org/W2126099406","https://openalex.org/W2129186929","https://openalex.org/W2129892623","https://openalex.org/W2138482055","https://openalex.org/W2139709933","https://openalex.org/W2141135018","https://openalex.org/W2141545157","https://openalex.org/W2142420122","https://openalex.org/W2143010534","https://openalex.org/W2143895821","https://openalex.org/W2145604601","https://openalex.org/W2155863249","https://openalex.org/W2157846047","https://openalex.org/W2158982427","https://openalex.org/W2159162331","https://openalex.org/W2160454972","https://openalex.org/W2164850486","https://openalex.org/W2167083595","https://openalex.org/W2168525280","https://openalex.org/W2207489776","https://openalex.org/W2266591399","https://openalex.org/W2304112809","https://openalex.org/W2317845212","https://openalex.org/W2335220829","https://openalex.org/W2416310637","https://openalex.org/W2499345884","https://openalex.org/W2508131240","https://openalex.org/W2609881461","https://openalex.org/W2622259492","https://openalex.org/W2624854028","https://openalex.org/W2801958376","https://openalex.org/W2809237570","https://openalex.org/W2911964244","https://openalex.org/W6641807947","https://openalex.org/W6645714515","https://openalex.org/W6697694827","https://openalex.org/W6725533128"],"related_works":["https://openalex.org/W2370893802","https://openalex.org/W2347729776","https://openalex.org/W2081457971","https://openalex.org/W2028659695","https://openalex.org/W4388140610","https://openalex.org/W2389115318","https://openalex.org/W2072749356","https://openalex.org/W2014400117","https://openalex.org/W2465294738","https://openalex.org/W2611334322"],"abstract_inverted_index":{"Optical":[0],"remote":[1],"sensing":[2],"data":[3],"have":[4,32],"been":[5],"widely":[6],"used":[7],"for":[8,29,56,66,225,234,266,279,301,310,366],"estimating":[9],"forest":[10,83,113,144,213,374],"aboveground":[11],"biomass":[12],"(AGB).":[13],"However,":[14],"the":[15,24,44,79,106,110,151,160,196,200,216,248,251,255,258,264,267,277,280,293,302,311,319,324,333,337,352,355,368],"use":[16,353],"of":[17,26,46,82,109,117,122,210,218,354,371],"optical":[18],"images":[19,180,328],"is":[20],"often":[21],"restricted":[22],"by":[23,43,93,297,306],"saturation":[25],"spectral":[27,47,339],"reflectance":[28,48],"forests":[30],"that":[31,192,346],"multilayered":[33],"and":[34,38,42,53,64,68,72,133,145,155,167,181,187,215,229,276,305,317,341,359],"complex":[35],"canopy":[36],"structures":[37],"high":[39],"AGB":[40,114,270,283],"values":[41,271,284],"effect":[45],"from":[49,221,230,323],"underlayer":[50],"shrub,":[51],"grass,":[52],"bare":[54],"soil":[55],"young":[57],"stands.":[58],"This":[59,344],"usually":[60],"leads":[61],"to":[62,77,104,171,223,232,299,308,331],"overestimations":[63,265],"underestimations":[65,278],"smaller":[67,272],"larger":[69,285],"values,":[70],"respectively,":[71],"makes":[73],"it":[74],"very":[75],"challenging":[76],"improve":[78,105],"estimation":[80,107,208,295,334,369],"accuracy":[81,108,219,296,335,370],"AGB.":[84,173,375],"In":[85],"this":[86],"study,":[87],"a":[88,98,363],"novel":[89],"methodology":[90],"was":[91],"proposed":[92],"incorporating":[94],"stand":[95],"age":[96,152,161,252,259,356],"as":[97],"dummy":[99,153,162,253,260,357],"variable":[100,163,261,358],"into":[101],"four":[102,156],"models":[103,128,141,158,249,256],"Pinus":[111,211,372],"densata":[112,212,373],"in":[115,205],"Yunnan":[116],"Southwestern":[118],"China.":[119],"A":[120],"total":[121],"eight":[123],"models,":[124,199,349],"including":[125],"two":[126,139,197,201,347],"parametric":[127,198],"(LM:":[129],"linear":[130],"regression":[131],"model":[132],"LMC:":[134],"LM":[135],"with":[136,159,195,247,257,269,282,351],"combined":[137],"variables),":[138],"nonparametric":[140,202,348],"(RF:":[142],"random":[143],"ANN:":[146],"artificial":[147],"neural":[148],"network)":[149],"without":[150,250],"variable,":[154,254],"corresponding":[157],"(DLM,":[164],"DLMC,":[165],"DRF,":[166],"DANN),":[168],"were":[169,185],"compared":[170,194,246],"estimate":[172],"Landsat":[174,325],"8":[175,326],"Operational":[176],"Land":[177],"Imager":[178],"(OLI)":[179],"147":[182],"sample":[183],"plots":[184,228,237,268,281,304,313],"acquired":[186],"utilized.":[188],"The":[189],"results":[190],"showed":[191],"(1)":[193],"algorithms":[203],"resulted":[204],"significantly":[206,291],"greater":[207],"accuracies":[209],"AGB,":[214],"increases":[217],"varied":[220],"8%":[222],"32%":[224,307],"100":[226],"modeling":[227,303],"12%":[231],"35%":[233],"47":[235],"test":[236,312],"based":[238,314],"on":[239,315],"root":[240],"mean":[241],"square":[242],"error":[243],"(RMSE);":[244],"(2)":[245],"greatly":[262],"reduced":[263],"than":[273,286,336],"70":[274],"Mg/ha":[275,288],"180":[287],"and,":[289],"thus,":[290],"improved":[292],"overall":[294],"14%":[298],"42%":[300],"44%":[309],"RMSE;":[316],"(3)":[318],"texture":[320,360],"measures":[321],"derived":[322],"OLI":[327],"contributed":[329],"more":[330],"improving":[332,367],"original":[338],"bands":[340],"other":[342],"transformations.":[343],"implied":[345],"coupled":[350],"measures,":[361],"offered":[362],"great":[364],"potential":[365]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":3}],"updated_date":"2026-04-20T07:46:08.049788","created_date":"2019-04-11T00:00:00"}
