{"id":"https://openalex.org/W3038890942","doi":"https://doi.org/10.3390/rs12132110","title":"Leaf Area Index Estimation Algorithm for GF-5 Hyperspectral Data Based on Different Feature Selection and Machine Learning Methods","display_name":"Leaf Area Index Estimation Algorithm for GF-5 Hyperspectral Data Based on Different Feature Selection and Machine Learning Methods","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3038890942","doi":"https://doi.org/10.3390/rs12132110","mag":"3038890942"},"language":"en","primary_location":{"id":"doi:10.3390/rs12132110","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12132110","pdf_url":"https://www.mdpi.com/2072-4292/12/13/2110/pdf","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/2072-4292/12/13/2110/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019004092","display_name":"Zhulin Chen","orcid":"https://orcid.org/0000-0001-7280-2916"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhulin Chen","raw_affiliation_strings":["Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China","State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]},{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063493372","display_name":"Kun Jia","orcid":"https://orcid.org/0000-0001-8586-4243"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kun Jia","raw_affiliation_strings":["Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China","State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"],"raw_orcid":"https://orcid.org/0000-0001-8586-4243","affiliations":[{"raw_affiliation_string":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]},{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102663415","display_name":"Chenchao Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210092591","display_name":"China Centre for Resources Satellite Data and Application","ror":"https://ror.org/00ft0fw96","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210092591"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenchao Xiao","raw_affiliation_strings":["Land Satellite Remote Sensing Application Center, Ministry of Natural Resource of the People\u2019s Republic of China, Beijing 100048, China","Land Satellite Remote Sensing Application Center, Ministry of Natural Resource of the People's Republic of China, Beijing 100048, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Land Satellite Remote Sensing Application Center, Ministry of Natural Resource of the People\u2019s Republic of China, Beijing 100048, China","institution_ids":["https://openalex.org/I4210092591"]},{"raw_affiliation_string":"Land Satellite Remote Sensing Application Center, Ministry of Natural Resource of the People's Republic of China, Beijing 100048, China","institution_ids":["https://openalex.org/I4210092591"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082968854","display_name":"Dandan Wei","orcid":"https://orcid.org/0000-0002-5597-6233"},"institutions":[{"id":"https://openalex.org/I4210092591","display_name":"China Centre for Resources Satellite Data and Application","ror":"https://ror.org/00ft0fw96","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210092591"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dandan Wei","raw_affiliation_strings":["Land Satellite Remote Sensing Application Center, Ministry of Natural Resource of the People\u2019s Republic of China, Beijing 100048, China","Land Satellite Remote Sensing Application Center, Ministry of Natural Resource of the People's Republic of China, Beijing 100048, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Land Satellite Remote Sensing Application Center, Ministry of Natural Resource of the People\u2019s Republic of China, Beijing 100048, China","institution_ids":["https://openalex.org/I4210092591"]},{"raw_affiliation_string":"Land Satellite Remote Sensing Application Center, Ministry of Natural Resource of the People's Republic of China, Beijing 100048, China","institution_ids":["https://openalex.org/I4210092591"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020032935","display_name":"Xiang Zhao","orcid":"https://orcid.org/0000-0002-0155-6735"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Zhao","raw_affiliation_strings":["Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China","State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"],"raw_orcid":"https://orcid.org/0000-0002-0155-6735","affiliations":[{"raw_affiliation_string":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]},{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101943364","display_name":"Jinhui Lan","orcid":"https://orcid.org/0000-0002-9071-9953"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhui Lan","raw_affiliation_strings":["Beijing Engineering Research Center of Industrial Spectrum Imaging, Beijing 100083, China","School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Engineering Research Center of Industrial Spectrum Imaging, Beijing 100083, China","institution_ids":[]},{"raw_affiliation_string":"School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079396291","display_name":"Xiangqin Wei","orcid":"https://orcid.org/0000-0001-9531-5336"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangqin Wei","raw_affiliation_strings":["Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011417699","display_name":"Yunjun Yao","orcid":"https://orcid.org/0000-0003-3803-8170"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunjun Yao","raw_affiliation_strings":["Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China","State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]},{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100382502","display_name":"Bing Wang","orcid":"https://orcid.org/0000-0002-2937-4757"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing Wang","raw_affiliation_strings":["Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China","State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]},{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076712405","display_name":"Yuan Sun","orcid":"https://orcid.org/0000-0002-4595-9237"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Sun","raw_affiliation_strings":["Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101573202","display_name":"Lei Wang","orcid":"https://orcid.org/0000-0001-6855-6687"},"institutions":[{"id":"https://openalex.org/I21642278","display_name":"Ningxia University","ror":"https://ror.org/04j7b2v61","country_code":"CN","type":"education","lineage":["https://openalex.org/I21642278"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Wang","raw_affiliation_strings":["Northwest National Key Laboratory Breeding Base for Land Degradation and Ecological Restoration, Ningxia University, Yinchuan 750021, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwest National Key Laboratory Breeding Base for Land Degradation and Ecological Restoration, Ningxia University, Yinchuan 750021, China","institution_ids":["https://openalex.org/I21642278"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":11,"corresponding_author_ids":["https://openalex.org/A5063493372"],"corresponding_institution_ids":["https://openalex.org/I25254941","https://openalex.org/I4210166112"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":7.2354,"has_fulltext":true,"cited_by_count":74,"citation_normalized_percentile":{"value":0.97685932,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"12","issue":"13","first_page":"2110","last_page":"2110"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9998999834060669,"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":0.9998999834060669,"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/T14365","display_name":"Leaf Properties and Growth Measurement","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9857000112533569,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/leaf-area-index","display_name":"Leaf area index","score":0.7939236164093018},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7338820695877075},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6723371744155884},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5834645628929138},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5334396958351135},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5272566080093384},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.49349796772003174},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48044678568840027},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4534180760383606},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.4289875626564026},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33709806203842163},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24849307537078857},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09011703729629517}],"concepts":[{"id":"https://openalex.org/C25989453","wikidata":"https://www.wikidata.org/wiki/Q446746","display_name":"Leaf area index","level":2,"score":0.7939236164093018},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7338820695877075},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6723371744155884},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5834645628929138},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5334396958351135},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5272566080093384},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.49349796772003174},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48044678568840027},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4534180760383606},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.4289875626564026},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33709806203842163},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24849307537078857},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09011703729629517},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","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},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs12132110","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12132110","pdf_url":"https://www.mdpi.com/2072-4292/12/13/2110/pdf","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:02431103d5c94576a0c9390de0d9a438","is_oa":true,"landing_page_url":"https://doaj.org/article/02431103d5c94576a0c9390de0d9a438","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 12, Iss 13, p 2110 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/12/13/2110/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs12132110","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 12; Issue 13; Pages: 2110","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs12132110","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12132110","pdf_url":"https://www.mdpi.com/2072-4292/12/13/2110/pdf","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":0.6200000047683716}],"awards":[{"id":"https://openalex.org/G1698978604","display_name":null,"funder_award_id":"2016YFB0501404","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8930261513","display_name":null,"funder_award_id":"2016YFA0600103","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3038890942.pdf","grobid_xml":"https://content.openalex.org/works/W3038890942.grobid-xml"},"referenced_works_count":113,"referenced_works":["https://openalex.org/W61452412","https://openalex.org/W221493477","https://openalex.org/W633320881","https://openalex.org/W1576520375","https://openalex.org/W1761723896","https://openalex.org/W1827322724","https://openalex.org/W1969568499","https://openalex.org/W1986767077","https://openalex.org/W1988872612","https://openalex.org/W1998025025","https://openalex.org/W1998776407","https://openalex.org/W1999469638","https://openalex.org/W2001510610","https://openalex.org/W2007179958","https://openalex.org/W2010423750","https://openalex.org/W2013968785","https://openalex.org/W2027878650","https://openalex.org/W2034574277","https://openalex.org/W2034650341","https://openalex.org/W2038137144","https://openalex.org/W2039768055","https://openalex.org/W2043673805","https://openalex.org/W2044309218","https://openalex.org/W2054284355","https://openalex.org/W2054443752","https://openalex.org/W2059730111","https://openalex.org/W2069883641","https://openalex.org/W2070564279","https://openalex.org/W2076137473","https://openalex.org/W2096599785","https://openalex.org/W2097192876","https://openalex.org/W2097970470","https://openalex.org/W2104635733","https://openalex.org/W2109965565","https://openalex.org/W2112732795","https://openalex.org/W2113242816","https://openalex.org/W2118599489","https://openalex.org/W2121025745","https://openalex.org/W2128274720","https://openalex.org/W2128686953","https://openalex.org/W2132073218","https://openalex.org/W2133167927","https://openalex.org/W2139584183","https://openalex.org/W2139925058","https://openalex.org/W2155261478","https://openalex.org/W2155622525","https://openalex.org/W2159263823","https://openalex.org/W2161160262","https://openalex.org/W2161509783","https://openalex.org/W2164936431","https://openalex.org/W2167248655","https://openalex.org/W2167799103","https://openalex.org/W2180748755","https://openalex.org/W2183383912","https://openalex.org/W2213617029","https://openalex.org/W2280205526","https://openalex.org/W2285717070","https://openalex.org/W2293711698","https://openalex.org/W2413484788","https://openalex.org/W2466023328","https://openalex.org/W2510415821","https://openalex.org/W2517208926","https://openalex.org/W2522904071","https://openalex.org/W2532184334","https://openalex.org/W2587679259","https://openalex.org/W2598259734","https://openalex.org/W2607281691","https://openalex.org/W2730602593","https://openalex.org/W2731864949","https://openalex.org/W2735018031","https://openalex.org/W2741011090","https://openalex.org/W2746479033","https://openalex.org/W2748857187","https://openalex.org/W2755091472","https://openalex.org/W2761090773","https://openalex.org/W2767189848","https://openalex.org/W2767768852","https://openalex.org/W2771068942","https://openalex.org/W2782772130","https://openalex.org/W2788146971","https://openalex.org/W2791150000","https://openalex.org/W2800465684","https://openalex.org/W2802272327","https://openalex.org/W2883168372","https://openalex.org/W2891829124","https://openalex.org/W2892497409","https://openalex.org/W2902773593","https://openalex.org/W2902928861","https://openalex.org/W2903512164","https://openalex.org/W2904957358","https://openalex.org/W2911694020","https://openalex.org/W2911964244","https://openalex.org/W2915777673","https://openalex.org/W2917296284","https://openalex.org/W2921811015","https://openalex.org/W2924352154","https://openalex.org/W2936132604","https://openalex.org/W2943149585","https://openalex.org/W2950294063","https://openalex.org/W2969739369","https://openalex.org/W2979332295","https://openalex.org/W2981785157","https://openalex.org/W3008712295","https://openalex.org/W3019506118","https://openalex.org/W6634442568","https://openalex.org/W6676301020","https://openalex.org/W6719473894","https://openalex.org/W6733368147","https://openalex.org/W6760371494","https://openalex.org/W6761240365","https://openalex.org/W6762493413","https://openalex.org/W6767380218","https://openalex.org/W6769401563"],"related_works":["https://openalex.org/W2132083814","https://openalex.org/W2292979300","https://openalex.org/W1995622179","https://openalex.org/W1484111231","https://openalex.org/W4391160746","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907"],"abstract_inverted_index":{"Leaf":[0],"area":[1],"index":[2],"(LAI)":[3],"is":[4,29,38,78,105,122],"an":[5,364],"essential":[6],"vegetation":[7,16,61,182],"parameter":[8],"that":[9,120,293,379,393],"represents":[10],"the":[11,20,57,101,123,132,142,153,164,246,252,259,269,295,325,335,356,371,390,394,414],"light":[12],"energy":[13],"utilization":[14],"and":[15,111,141,149,163,183,186,198,203,217,285,303,343,352,402,431],"canopy":[17],"structure.":[18],"As":[19],"only":[21],"in-operation":[22],"hyperspectral":[23],"satellite":[24],"launched":[25],"by":[26,166,355,422],"China,":[27],"GF-5":[28,44,135,177,409],"potentially":[30],"useful":[31],"for":[32,46,98,108,138,300,306,340,346,375,405],"accurate":[33],"LAI":[34,47,114,140,226,275,310,376,434],"estimation.":[35,48,115,366],"However,":[36,116],"there":[37],"no":[39,117],"research":[40],"focus":[41],"on":[42,130,274],"evaluating":[43,131],"data":[45,52,66,82,179,424],"Hyperspectral":[49],"remote":[50],"sensing":[51],"contains":[53],"abundant":[54],"information":[55],"about":[56],"reflective":[58],"characteristics":[59],"of":[60,134,144,147,255,313,334],"canopies,":[62],"but":[63],"these":[64],"abound":[65],"also":[67],"easily":[68],"result":[69],"in":[70,113],"a":[71],"dimensionality":[72],"curse.":[73],"Therefore,":[74,126],"feature":[75,301,341,350,400],"selection":[76,262,302,342,351,369,401],"(FS)":[77],"necessary":[79],"to":[80,84,174,223,244,267],"reduce":[81],"redundancy":[83],"achieve":[85,385],"more":[86],"reliable":[87,309],"estimations.":[88],"Currently,":[89],"machine":[90],"learning":[91],"(ML)":[92],"algorithms":[93],"have":[94],"been":[95],"widely":[96],"used":[97,173,222,266,299,305,339,345,398,404],"FS.":[99],"Moreover,":[100,367],"same":[102,357],"ML":[103,150,205,358,381],"algorithm":[104,359],"usually":[106],"conducted":[107,233,243,354],"both":[109],"FS":[110,148,189,230,240],"regression":[112,210,353,382],"evidence":[118],"suggests":[119],"this":[121,127],"optimal":[124,365],"solution.":[125],"study":[128],"focuses":[129],"capacity":[133],"spectral":[136,410],"reflectance":[137,178,412],"estimating":[139],"performances":[143],"different":[145,181,236],"combination":[146],"algorithms.":[151],"Firstly,":[152,238],"PROSAIL":[154],"model,":[155,171],"which":[156,250],"coupled":[157],"leaf":[158],"optical":[159],"properties":[160],"model":[161,297,337,396],"PROSPECT":[162],"scattering":[165],"arbitrarily":[167],"inclined":[168],"leaves":[169],"(SAIL)":[170],"was":[172,232,265],"generate":[175],"simulated":[176,423],"under":[180],"soil":[184],"conditions,":[185],"then":[187],"three":[188,204,239,279],"methods,":[190],"including":[191,207],"random":[192,208],"forest":[193,209],"(RF),":[194],"K-means":[195],"clustering":[196],"(K-means)":[197],"mean":[199,319],"impact":[200,273],"value":[201],"(MIV),":[202],"algorithms,":[206],"(RFR),":[211],"back":[212],"propagation":[213],"neural":[214],"network":[215],"(BPNN)":[216],"K-nearest":[218],"neighbor":[219],"(KNN)":[220],"were":[221,242,283],"develop":[224],"nine":[225],"estimation":[227,253,276,281,377,387,416],"models.":[228],"The":[229,290],"process":[231],"twice":[234],"using":[235,287,349],"strategies:":[237],"methods":[241],"search":[245],"lowest":[247],"dimension":[248],"number,":[249],"maintained":[251],"accuracy":[254],"all":[256],"bands.":[257],"Then,":[258],"sequential":[260],"backward":[261],"(SBS)":[263],"method":[264,383],"eliminate":[268],"bands":[270,374],"having":[271],"minimal":[272],"accuracy.":[277],"Finally,":[278,389],"best":[280],"models":[282],"selected":[284],"evaluated":[286],"reference":[288,433],"LAI.":[289],"results":[291,391,417],"showed":[292],"although":[294],"RF_RFR":[296],"(RF":[298,397],"RFR":[304],"regression)":[307,347,406],"achieved":[308,413],"estimates":[311],"(coefficient":[312],"determination":[314],"(R2)":[315],"=":[316,323,329,332,426,429,436,439],"0.828,":[317],"root":[318],"square":[320],"error":[321],"(RMSE)":[322],"0.839),":[324],"poor":[326],"performance":[327],"(R2":[328,425,435],"0.763,":[330],"RMSE":[331,428,438],"0.987)":[333],"MIV_BPNN":[336],"(MIV":[338],"BPNN":[344],"suggested":[348],"could":[360,384],"not":[361],"always":[362],"ensure":[363],"RF":[368],"preserved":[370],"most":[372],"informative":[373],"so":[378],"each":[380],"satisfactory":[386],"results.":[388],"indicated":[392],"RF_KNN":[395],"as":[399],"KNN":[403],"with":[407],"seven":[408],"band":[411],"better":[415],"than":[418],"others":[419],"when":[420],"validated":[421],"0.834,":[427],"0.824)":[430],"actual":[432],"0.659,":[437],"0.697).":[440]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":16},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
