{"id":"https://openalex.org/W3212718697","doi":"https://doi.org/10.3390/rs13224631","title":"A Combined Strategy of Improved Variable Selection and Ensemble Algorithm to Map the Growing Stem Volume of Planted Coniferous Forest","display_name":"A Combined Strategy of Improved Variable Selection and Ensemble Algorithm to Map the Growing Stem Volume of Planted Coniferous Forest","publication_year":2021,"publication_date":"2021-11-17","ids":{"openalex":"https://openalex.org/W3212718697","doi":"https://doi.org/10.3390/rs13224631","mag":"3212718697"},"language":"en","primary_location":{"id":"doi:10.3390/rs13224631","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13224631","pdf_url":"https://www.mdpi.com/2072-4292/13/22/4631/pdf?version=1637198962","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/2072-4292/13/22/4631/pdf?version=1637198962","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082753712","display_name":"Xiaodong Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I119273862","display_name":"Central South University of Forestry and Technology","ror":"https://ror.org/02czw2k81","country_code":"CN","type":"education","lineage":["https://openalex.org/I119273862"]},{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]},{"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":"Xiaodong Xu","raw_affiliation_strings":["Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province, Changsha 410004, China","Key Laboratory of State Forestry Administration on Forest Resources Management and Monitoring in Southern Area, Changsha 410004, China","Research Center of Forestry Remote Sensing & Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province, Changsha 410004, China","institution_ids":[]},{"raw_affiliation_string":"Key Laboratory of State Forestry Administration on Forest Resources Management and Monitoring in Southern Area, Changsha 410004, China","institution_ids":["https://openalex.org/I4210134523"]},{"raw_affiliation_string":"Research Center of Forestry Remote Sensing & Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China","institution_ids":["https://openalex.org/I119273862","https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100384030","display_name":"Hui Lin","orcid":"https://orcid.org/0000-0002-1151-7705"},"institutions":[{"id":"https://openalex.org/I119273862","display_name":"Central South University of Forestry and Technology","ror":"https://ror.org/02czw2k81","country_code":"CN","type":"education","lineage":["https://openalex.org/I119273862"]},{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]},{"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":"Hui Lin","raw_affiliation_strings":["Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province, Changsha 410004, China","Key Laboratory of State Forestry Administration on Forest Resources Management and Monitoring in Southern Area, Changsha 410004, China","Research Center of Forestry Remote Sensing & Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province, Changsha 410004, China","institution_ids":[]},{"raw_affiliation_string":"Key Laboratory of State Forestry Administration on Forest Resources Management and Monitoring in Southern Area, Changsha 410004, China","institution_ids":["https://openalex.org/I4210134523"]},{"raw_affiliation_string":"Research Center of Forestry Remote Sensing & Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China","institution_ids":["https://openalex.org/I119273862","https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007721343","display_name":"Zhaohua Liu","orcid":"https://orcid.org/0000-0002-6597-4741"},"institutions":[{"id":"https://openalex.org/I119273862","display_name":"Central South University of Forestry and Technology","ror":"https://ror.org/02czw2k81","country_code":"CN","type":"education","lineage":["https://openalex.org/I119273862"]},{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]},{"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":"Zhaohua Liu","raw_affiliation_strings":["Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province, Changsha 410004, China","Key Laboratory of State Forestry Administration on Forest Resources Management and Monitoring in Southern Area, Changsha 410004, China","Research Center of Forestry Remote Sensing & Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province, Changsha 410004, China","institution_ids":[]},{"raw_affiliation_string":"Key Laboratory of State Forestry Administration on Forest Resources Management and Monitoring in Southern Area, Changsha 410004, China","institution_ids":["https://openalex.org/I4210134523"]},{"raw_affiliation_string":"Research Center of Forestry Remote Sensing & Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China","institution_ids":["https://openalex.org/I119273862","https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059359043","display_name":"Zilin Ye","orcid":"https://orcid.org/0009-0004-4465-9445"},"institutions":[{"id":"https://openalex.org/I119273862","display_name":"Central South University of Forestry and Technology","ror":"https://ror.org/02czw2k81","country_code":"CN","type":"education","lineage":["https://openalex.org/I119273862"]},{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]},{"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":"Zilin Ye","raw_affiliation_strings":["Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province, Changsha 410004, China","Key Laboratory of State Forestry Administration on Forest Resources Management and Monitoring in Southern Area, Changsha 410004, China","Research Center of Forestry Remote Sensing & Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province, Changsha 410004, China","institution_ids":[]},{"raw_affiliation_string":"Key Laboratory of State Forestry Administration on Forest Resources Management and Monitoring in Southern Area, Changsha 410004, China","institution_ids":["https://openalex.org/I4210134523"]},{"raw_affiliation_string":"Research Center of Forestry Remote Sensing & Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China","institution_ids":["https://openalex.org/I119273862","https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100406080","display_name":"Xinyu Li","orcid":"https://orcid.org/0000-0001-6678-8660"},"institutions":[{"id":"https://openalex.org/I119273862","display_name":"Central South University of Forestry and Technology","ror":"https://ror.org/02czw2k81","country_code":"CN","type":"education","lineage":["https://openalex.org/I119273862"]},{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]},{"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":"Xinyu Li","raw_affiliation_strings":["Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province, Changsha 410004, China","Key Laboratory of State Forestry Administration on Forest Resources Management and Monitoring in Southern Area, Changsha 410004, China","Research Center of Forestry Remote Sensing & Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province, Changsha 410004, China","institution_ids":[]},{"raw_affiliation_string":"Key Laboratory of State Forestry Administration on Forest Resources Management and Monitoring in Southern Area, Changsha 410004, China","institution_ids":["https://openalex.org/I4210134523"]},{"raw_affiliation_string":"Research Center of Forestry Remote Sensing & Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China","institution_ids":["https://openalex.org/I119273862","https://openalex.org/I139660479"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081564636","display_name":"Jiangping Long","orcid":"https://orcid.org/0000-0001-9971-5505"},"institutions":[{"id":"https://openalex.org/I119273862","display_name":"Central South University of Forestry and Technology","ror":"https://ror.org/02czw2k81","country_code":"CN","type":"education","lineage":["https://openalex.org/I119273862"]},{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]},{"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":"Jiangping Long","raw_affiliation_strings":["Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province, Changsha 410004, China","Key Laboratory of State Forestry Administration on Forest Resources Management and Monitoring in Southern Area, Changsha 410004, China","Research Center of Forestry Remote Sensing & Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China"],"raw_orcid":"https://orcid.org/0000-0001-9971-5505","affiliations":[{"raw_affiliation_string":"Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province, Changsha 410004, China","institution_ids":[]},{"raw_affiliation_string":"Key Laboratory of State Forestry Administration on Forest Resources Management and Monitoring in Southern Area, Changsha 410004, China","institution_ids":["https://openalex.org/I4210134523"]},{"raw_affiliation_string":"Research Center of Forestry Remote Sensing & Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China","institution_ids":["https://openalex.org/I119273862","https://openalex.org/I139660479"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5081564636"],"corresponding_institution_ids":["https://openalex.org/I119273862","https://openalex.org/I139660479","https://openalex.org/I4210134523"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2592},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2592},"fwci":3.074,"has_fulltext":true,"cited_by_count":24,"citation_normalized_percentile":{"value":0.91541131,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"13","issue":"22","first_page":"4631","last_page":"4631"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9998000264167786,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9997000098228455,"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":0.9988999962806702,"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/collinearity","display_name":"Collinearity","score":0.8105464577674866},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.709977388381958},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5909675359725952},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.5727624297142029},{"id":"https://openalex.org/keywords/pearson-product-moment-correlation-coefficient","display_name":"Pearson product-moment correlation coefficient","score":0.5295639634132385},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5061907172203064},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.49540388584136963},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.4939797520637512},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4453483819961548},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4327964782714844},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3985682725906372},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39631640911102295},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3848561644554138}],"concepts":[{"id":"https://openalex.org/C106192678","wikidata":"https://www.wikidata.org/wiki/Q1419761","display_name":"Collinearity","level":2,"score":0.8105464577674866},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.709977388381958},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5909675359725952},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.5727624297142029},{"id":"https://openalex.org/C55078378","wikidata":"https://www.wikidata.org/wiki/Q1136628","display_name":"Pearson product-moment correlation coefficient","level":2,"score":0.5295639634132385},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5061907172203064},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.49540388584136963},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.4939797520637512},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4453483819961548},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4327964782714844},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3985682725906372},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39631640911102295},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3848561644554138}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs13224631","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13224631","pdf_url":"https://www.mdpi.com/2072-4292/13/22/4631/pdf?version=1637198962","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:362c77df3cf240a9b98af9821f064afd","is_oa":true,"landing_page_url":"https://doaj.org/article/362c77df3cf240a9b98af9821f064afd","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 13, Iss 22, p 4631 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs13224631","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13224631","pdf_url":"https://www.mdpi.com/2072-4292/13/22/4631/pdf?version=1637198962","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","id":"https://metadata.un.org/sdg/15","score":0.5799999833106995}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3212718697.pdf","grobid_xml":"https://content.openalex.org/works/W3212718697.grobid-xml"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W207758080","https://openalex.org/W428880907","https://openalex.org/W1177863458","https://openalex.org/W1828991496","https://openalex.org/W1907754837","https://openalex.org/W1987352360","https://openalex.org/W1989344766","https://openalex.org/W1989789696","https://openalex.org/W1992679269","https://openalex.org/W1996938046","https://openalex.org/W2019126302","https://openalex.org/W2022224360","https://openalex.org/W2028070629","https://openalex.org/W2035222601","https://openalex.org/W2046788667","https://openalex.org/W2063623478","https://openalex.org/W2094677081","https://openalex.org/W2095357153","https://openalex.org/W2098469025","https://openalex.org/W2104653669","https://openalex.org/W2124837560","https://openalex.org/W2126099406","https://openalex.org/W2129132239","https://openalex.org/W2129428798","https://openalex.org/W2141272333","https://openalex.org/W2152634225","https://openalex.org/W2153534477","https://openalex.org/W2154108701","https://openalex.org/W2188767531","https://openalex.org/W2263939288","https://openalex.org/W2270330859","https://openalex.org/W2533566148","https://openalex.org/W2589611909","https://openalex.org/W2744761727","https://openalex.org/W2765260274","https://openalex.org/W2780157115","https://openalex.org/W2789665835","https://openalex.org/W2905659887","https://openalex.org/W2911964244","https://openalex.org/W2916382809","https://openalex.org/W2920828326","https://openalex.org/W2928790886","https://openalex.org/W2967353317","https://openalex.org/W2969890686","https://openalex.org/W2998216295","https://openalex.org/W2998937092","https://openalex.org/W3010730615","https://openalex.org/W3033402617","https://openalex.org/W3035147592","https://openalex.org/W3089412685","https://openalex.org/W3111373125","https://openalex.org/W3177949452","https://openalex.org/W4212883601","https://openalex.org/W4285719527","https://openalex.org/W6679218201","https://openalex.org/W7066667914"],"related_works":["https://openalex.org/W4382315444","https://openalex.org/W357196361","https://openalex.org/W4233259193","https://openalex.org/W2027314909","https://openalex.org/W3109425891","https://openalex.org/W3096637473","https://openalex.org/W1036938216","https://openalex.org/W2113714434","https://openalex.org/W2600353413","https://openalex.org/W2377792686"],"abstract_inverted_index":{"Remote":[0],"sensing":[1,28],"technology":[2],"is":[3,30],"becoming":[4],"mainstream":[5],"for":[6,250,256],"mapping":[7,230,307],"the":[8,15,22,34,43,61,65,71,93,117,147,174,177,194,199,213,220,227,234,237,260,264,266,275,278,282,296,305],"growing":[9],"stem":[10],"volume":[11],"(GSV)":[12],"and":[13,38,48,64,75,95,107,122,130,141,151,165,173,206,252,315],"overcoming":[14],"shortage":[16],"of":[17,89,277],"traditional":[18],"labor-consumed":[19],"approaches.":[20],"Naturally,":[21],"GSV":[23,79,152,197,229,279,306],"estimation":[24],"accuracy":[25],"utilizing":[26],"remote":[27],"imagery":[29],"highly":[31],"related":[32],"to":[33,41,69,192,248,254,272,303],"variable":[35,58,113,215,223,312],"selection":[36,59,114,216,313],"methods":[37,288],"algorithms.":[39,316],"Thus,":[40],"reduce":[42,304],"uncertainty":[44,308],"caused":[45],"by":[46,204,281,310],"variables":[47,74,91,150],"models,":[49],"this":[50],"paper":[51],"proposes":[52],"a":[53,77,182],"combined":[54,73,222,298],"strategy":[55,299],"involving":[56,263],"improved":[57,112,187],"with":[60,116,185,285],"collinearity":[62,118,175],"test":[63,119],"secondary":[66,183,261,283],"ensemble":[67,184,201,262,284],"algorithm":[68],"obtain":[70],"optimally":[72],"extract":[76],"reliable":[78,195],"from":[80,92,246,270],"several":[81],"base":[82],"models.":[83],"Our":[84],"study":[85],"extracted":[86],"four":[87],"types":[88],"alternative":[90],"Sentinel-1A":[94],"Sentinel-2A":[96],"image":[97],"datasets,":[98],"including":[99],"vegetation":[100],"indices,":[101],"spectral":[102],"reflectance":[103],"variables,":[104],"backscattering":[105],"coefficients,":[106],"texture":[108],"features.":[109],"Then,":[110],"an":[111,186],"criterion":[115,217],"was":[120,289],"developed":[121],"evaluated":[123],"based":[124],"on":[125],"machine":[126],"learning":[127],"algorithms":[128],"(classification":[129],"regression":[131,139],"trees":[132],"(CART),":[133],"k-nearest":[134],"neighbors":[135],"(KNN),":[136],"support":[137],"vector":[138],"(SVR),":[140],"artificial":[142],"neural":[143],"network":[144],"(ANN))":[145],"considering":[146,233],"correlation":[148,158,167],"between":[149],"(with":[153],"random":[154],"forest":[155,196,228],"(RF),":[156],"distance":[157],"coefficient":[159,163,168],"(DC),":[160],"maximal":[161],"information":[162],"(MIC),":[164],"Pearson":[166],"(PCC)":[169],"as":[170],"evaluation":[171],"metrics),":[172],"among":[176],"variables.":[178],"Additionally,":[179],"we":[180],"proposed":[181,214,297],"weighted":[188],"average":[189],"approach":[190],"(IWA)":[191],"estimate":[193],"using":[198],"first":[200,235],"models":[202],"constructed":[203],"Bagging":[205,251],"AdaBoost.":[207],"The":[208,292],"experimental":[209],"results":[210,293],"demonstrated":[211],"that":[212,295],"efficiently":[218],"obtained":[219],"optimal":[221],"set":[224],"without":[225],"affecting":[226],"accuracy.":[231],"Specifically,":[232],"ensemble,":[236],"relative":[238],"root":[239],"mean":[240],"square":[241],"error":[242],"(rRMSE)":[243],"values":[244,268],"ranged":[245,269],"21.91%":[247],"30.28%":[249],"23.33%":[253],"31.49%":[255],"AdaBoost,":[257],"respectively.":[258],"After":[259],"IWA,":[265],"rRMSE":[267],"18.89%":[271],"21.34%.":[273],"Furthermore,":[274],"variance":[276],"mapped":[280],"various":[286],"ranking":[287],"significantly":[290],"reduced.":[291],"prove":[294],"has":[300],"great":[301],"potential":[302],"imposed":[309],"current":[311],"approaches":[314]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":3}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2021-11-22T00:00:00"}