{"id":"https://openalex.org/W3048690716","doi":"https://doi.org/10.3390/rs12162574","title":"Assessment of Leaf Chlorophyll Content Models for Winter Wheat Using Landsat-8 Multispectral Remote Sensing Data","display_name":"Assessment of Leaf Chlorophyll Content Models for Winter Wheat Using Landsat-8 Multispectral Remote Sensing Data","publication_year":2020,"publication_date":"2020-08-11","ids":{"openalex":"https://openalex.org/W3048690716","doi":"https://doi.org/10.3390/rs12162574","mag":"3048690716"},"language":"en","primary_location":{"id":"doi:10.3390/rs12162574","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12162574","pdf_url":"https://www.mdpi.com/2072-4292/12/16/2574/pdf?version=1597108312","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/2072-4292/12/16/2574/pdf?version=1597108312","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069930488","display_name":"Xianfeng Zhou","orcid":"https://orcid.org/0000-0001-5398-0848"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianfeng Zhou","raw_affiliation_strings":["School of Artificial Intelligence, Hangzhou Dianzi University, Hangzhou 310018, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Hangzhou Dianzi University, Hangzhou 310018, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101532051","display_name":"Jingcheng Zhang","orcid":"https://orcid.org/0000-0002-6339-7661"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingcheng Zhang","raw_affiliation_strings":["School of Artificial Intelligence, Hangzhou Dianzi University, Hangzhou 310018, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Hangzhou Dianzi University, Hangzhou 310018, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100677493","display_name":"Dongmei Chen","orcid":"https://orcid.org/0000-0001-5419-8735"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongmei Chen","raw_affiliation_strings":["School of Artificial Intelligence, Hangzhou Dianzi University, Hangzhou 310018, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Hangzhou Dianzi University, Hangzhou 310018, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006023502","display_name":"Yanbo Huang","orcid":"https://orcid.org/0000-0002-1409-8868"},"institutions":[{"id":"https://openalex.org/I1312222531","display_name":"Agricultural Research Service","ror":"https://ror.org/02d2m2044","country_code":"US","type":"government","lineage":["https://openalex.org/I1312222531","https://openalex.org/I1336096307"]},{"id":"https://openalex.org/I1336096307","display_name":"United States Department of Agriculture","ror":"https://ror.org/01na82s61","country_code":"US","type":"government","lineage":["https://openalex.org/I1336096307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanbo Huang","raw_affiliation_strings":["United States Department of Agriculture, Agricultural Research Service, Crop Production Systems Research Unit, Stoneville, MS 38776, USA"],"affiliations":[{"raw_affiliation_string":"United States Department of Agriculture, Agricultural Research Service, Crop Production Systems Research Unit, Stoneville, MS 38776, USA","institution_ids":["https://openalex.org/I1336096307","https://openalex.org/I1312222531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102818489","display_name":"Weiping Kong","orcid":null},"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/I4210151155","display_name":"Academy of Opto-Electronics","ror":"https://ror.org/04acsr153","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210151155"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiping Kong","raw_affiliation_strings":["Key Laboratory of Quantitative Remote Sensing Information Technology, Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing 100094, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Quantitative Remote Sensing Information Technology, Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing 100094, China","institution_ids":["https://openalex.org/I4210151155","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049701324","display_name":"Lin Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210160030","display_name":"Zhejiang University of Water Resource and Electric Power","ror":"https://ror.org/04dg5b632","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210160030"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Yuan","raw_affiliation_strings":["School of Information Engineering and Art and Design, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering and Art and Design, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China","institution_ids":["https://openalex.org/I4210160030"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100780503","display_name":"Huichun Ye","orcid":"https://orcid.org/0000-0001-7836-497X"},"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":"Huichun Ye","raw_affiliation_strings":["Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109619264","display_name":"Wenjiang Huang","orcid":"https://orcid.org/0009-0009-3343-7034"},"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":true,"raw_author_name":"Wenjiang Huang","raw_affiliation_strings":["Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5109619264"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210137199"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":4.8086,"has_fulltext":false,"cited_by_count":58,"citation_normalized_percentile":{"value":0.95409541,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"12","issue":"16","first_page":"2574","last_page":"2574"},"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":0.9921000003814697,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.7482908964157104},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.7215750217437744},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.7180296182632446},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.5573458671569824},{"id":"https://openalex.org/keywords/leaf-area-index","display_name":"Leaf area index","score":0.5525125861167908},{"id":"https://openalex.org/keywords/lookup-table","display_name":"Lookup table","score":0.520114541053772},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.5080795288085938},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.4100944399833679},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.32419949769973755},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31115883588790894},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.17725956439971924},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15406551957130432},{"id":"https://openalex.org/keywords/agronomy","display_name":"Agronomy","score":0.13289880752563477}],"concepts":[{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.7482908964157104},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.7215750217437744},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.7180296182632446},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.5573458671569824},{"id":"https://openalex.org/C25989453","wikidata":"https://www.wikidata.org/wiki/Q446746","display_name":"Leaf area index","level":2,"score":0.5525125861167908},{"id":"https://openalex.org/C134835016","wikidata":"https://www.wikidata.org/wiki/Q690265","display_name":"Lookup table","level":2,"score":0.520114541053772},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.5080795288085938},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.4100944399833679},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.32419949769973755},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31115883588790894},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.17725956439971924},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15406551957130432},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.13289880752563477},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs12162574","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12162574","pdf_url":"https://www.mdpi.com/2072-4292/12/16/2574/pdf?version=1597108312","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:7b3de7ba3c934173afbd858d18ff0b54","is_oa":true,"landing_page_url":"https://doaj.org/article/7b3de7ba3c934173afbd858d18ff0b54","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 12, Iss 16, p 2574 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/12/16/2574/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs12162574","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 16; Pages: 2574","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs12162574","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12162574","pdf_url":"https://www.mdpi.com/2072-4292/12/16/2574/pdf?version=1597108312","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":"Affordable and clean energy","score":0.41999998688697815,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3048690716.pdf","grobid_xml":"https://content.openalex.org/works/W3048690716.grobid-xml"},"referenced_works_count":59,"referenced_works":["https://openalex.org/W221493477","https://openalex.org/W1596717185","https://openalex.org/W1968235624","https://openalex.org/W1974635621","https://openalex.org/W1981590796","https://openalex.org/W1986136566","https://openalex.org/W1987607942","https://openalex.org/W2000102737","https://openalex.org/W2000613913","https://openalex.org/W2003944446","https://openalex.org/W2005034723","https://openalex.org/W2007342648","https://openalex.org/W2009517474","https://openalex.org/W2012686349","https://openalex.org/W2024925469","https://openalex.org/W2036149627","https://openalex.org/W2042901310","https://openalex.org/W2049556619","https://openalex.org/W2051128904","https://openalex.org/W2051438985","https://openalex.org/W2052700773","https://openalex.org/W2054172243","https://openalex.org/W2070203790","https://openalex.org/W2081887174","https://openalex.org/W2082867835","https://openalex.org/W2089441588","https://openalex.org/W2094677081","https://openalex.org/W2101010747","https://openalex.org/W2102160343","https://openalex.org/W2109006150","https://openalex.org/W2123737232","https://openalex.org/W2128438912","https://openalex.org/W2129719999","https://openalex.org/W2139709933","https://openalex.org/W2152164823","https://openalex.org/W2155482699","https://openalex.org/W2158863190","https://openalex.org/W2161815745","https://openalex.org/W2163410149","https://openalex.org/W2167787089","https://openalex.org/W2313541398","https://openalex.org/W2337882350","https://openalex.org/W2379512924","https://openalex.org/W2404939661","https://openalex.org/W2499194778","https://openalex.org/W2531109463","https://openalex.org/W2583965418","https://openalex.org/W2766047845","https://openalex.org/W2806394060","https://openalex.org/W2887487187","https://openalex.org/W2911964244","https://openalex.org/W2915540904","https://openalex.org/W2990557644","https://openalex.org/W4211049957","https://openalex.org/W6678557583","https://openalex.org/W6710068505","https://openalex.org/W6723684865","https://openalex.org/W6770844292","https://openalex.org/W6847019388"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W4318664220","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2070598848","https://openalex.org/W2022304901","https://openalex.org/W2018850895","https://openalex.org/W2988577871","https://openalex.org/W1987483041"],"abstract_inverted_index":{"The":[0,95,142],"leaf":[1],"chlorophyll":[2],"content":[3],"(LCC)":[4],"is":[5],"a":[6,161,171,343],"critical":[7],"index":[8,150],"to":[9,66,113,247],"characterize":[10],"crop":[11,29,87,337],"growth":[12,30],"conditions,":[13],"photosynthetic":[14],"capacity,":[15],"and":[16,32,38,43,78,81,107,117,138,170,186,221,265,300,310,340],"physiological":[17],"status.":[18],"Its":[19],"dynamic":[20],"change":[21],"characteristics":[22],"are":[23,334],"of":[24,36,83,100,167,175,229,268,284,303],"great":[25],"significance":[26],"for":[27,86,119,157,205,292,316,336,345],"monitoring":[28],"conditions":[31],"understanding":[33],"the":[34,44,74,79,84,108,146,153,202,236,248,254,266,275,282,297,301,313],"process":[35,198],"material":[37],"energy":[39],"exchange":[40],"between":[41],"crops":[42],"environment.":[45],"Extensive":[46],"research":[47],"has":[48,63],"focused":[49],"on":[50],"LCC":[51,67,88,120,158,206,293,317,338,346],"retrieval":[52,125,159,207,339],"with":[53,160,216,235,290,348],"hyperspectral":[54],"data":[55,75,85,112,333],"onboard":[56],"various":[57],"sensor":[58],"platforms.":[59],"Nevertheless,":[60],"limited":[61],"attention":[62],"been":[64,92],"paid":[65],"inversion":[68,233,276],"from":[69,76,184,196],"multispectral":[70,350],"data,":[71],"such":[72],"as":[73],"Landsat-8,":[77],"potentials":[80,118],"capabilities":[82,116],"estimation":[89,256,298,318,347],"have":[90],"not":[91],"fully":[93],"explored.":[94],"present":[96],"study":[97,328],"made":[98],"use":[99,283],"Landsat-8":[101,331],"Operational":[102],"Land":[103],"Imager":[104],"(OLI)":[105],"imagery":[106],"corresponding":[109],"field":[110],"experimental":[111],"evaluate":[114],"their":[115],"modeling":[121],"using":[122],"four":[123],"different":[124],"methods:":[126],"vegetation":[127,149,179],"indices":[128,180],"(VIs),":[129],"machine":[130],"learning":[131,286],"regression":[132,140,199,280],"algorithms":[133],"(MLRAs),":[134],"lookup-table":[135],"(LUT)-based":[136],"inversion,":[137],"hybrid":[139,279],"approaches.":[141],"results":[143,257],"showed":[144,253],"that":[145,181,245,330],"modified":[147],"triangular":[148],"(MTVI2)":[151],"exhibited":[152,191],"best":[154,255,314],"estimate":[155],"accuracy":[156,204,315],"root":[162],"mean":[163],"square":[164],"error":[165],"(RMSE)":[166],"5.99":[168],"\u03bcg/cm2":[169],"relative":[172],"RMSE":[173],"(RRMSE)":[174],"10.49%.":[176],"Several":[177],"other":[178,217,225],"were":[182],"established":[183,195],"red":[185,220],"near-infrared":[187],"(NIR)":[188],"bands":[189,223,226],"also":[190],"good":[192],"accuracy.":[193,277],"Models":[194],"Gaussian":[197],"(GPR)":[200],"achieved":[201],"highest":[203],"(RMSE":[208,258,319],"=":[209,213,238,259,263,320,324],"5.50":[210],"\u03bcg/cm2,":[211,261,322],"RRMSE":[212,262,323],"9.62%)":[214],"compared":[215],"MLRAs.":[218],"Moreover,":[219],"NIR":[222],"outweighed":[224],"in":[227],"terms":[228],"GPR":[230,291,311],"modelling.":[231],"LUT-based":[232],"methods":[234],"\u201cK(x)":[237],"\u2212log":[239],"(x)":[240],"+":[241],"x\u201d":[242],"cost":[243],"function":[244],"belongs":[246],"\u201cminimum":[249],"contrast":[250],"estimates\u201d":[251],"family":[252],"8.08":[260],"14.14%),":[264],"addition":[267],"multiple":[269],"solution":[270],"regularization":[271],"strategies":[272],"effectively":[273],"improved":[274],"For":[278],"methods,":[281],"active":[285],"(AL)":[287],"techniques":[288],"together":[289],"modelling":[294],"significantly":[295],"increased":[296],"accuracy,":[299],"combination":[302],"entropy":[304],"query":[305],"by":[306],"bagging":[307],"(EQB)":[308],"AL":[309],"had":[312],"12.43":[321],"21.77%).":[325],"Overall,":[326],"our":[327],"suggest":[329],"OLI":[332],"suitable":[335],"could":[341],"provide":[342],"basis":[344],"similar":[349],"datasets.":[351]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2020-08-18T00:00:00"}
