{"id":"https://openalex.org/W2900948053","doi":"https://doi.org/10.1109/igarss.2018.8517823","title":"Estimation of Leaf Area Index with Various Vegetation Indices from Gaofen-5 Band Reflectances","display_name":"Estimation of Leaf Area Index with Various Vegetation Indices from Gaofen-5 Band Reflectances","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2900948053","doi":"https://doi.org/10.1109/igarss.2018.8517823","mag":"2900948053"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2018.8517823","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8517823","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100357835","display_name":"Ziyang Zhang","orcid":"https://orcid.org/0000-0002-7739-1287"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ziyang Zhang","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088342796","display_name":"Bo\u2010Hui Tang","orcid":"https://orcid.org/0000-0002-1918-5346"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo-Hui Tang","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100357835"],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.0993449,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"38","issue":null,"first_page":"2619","last_page":"2622"},"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":0.9987999796867371,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/vegetation","display_name":"Vegetation (pathology)","score":0.7275640964508057},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.6665080189704895},{"id":"https://openalex.org/keywords/leaf-area-index","display_name":"Leaf area index","score":0.6571779251098633},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6362979412078857},{"id":"https://openalex.org/keywords/vegetation-index","display_name":"Vegetation Index","score":0.54776531457901},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.5197467803955078},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.47773808240890503},{"id":"https://openalex.org/keywords/canopy","display_name":"Canopy","score":0.457692950963974},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4391917586326599},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4363839626312256},{"id":"https://openalex.org/keywords/coefficient-of-determination","display_name":"Coefficient of determination","score":0.41424497961997986},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.33677205443382263},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.32767295837402344},{"id":"https://openalex.org/keywords/normalized-difference-vegetation-index","display_name":"Normalized Difference Vegetation Index","score":0.2226453423500061},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.17247095704078674},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.14279642701148987},{"id":"https://openalex.org/keywords/botany","display_name":"Botany","score":0.1280096471309662}],"concepts":[{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.7275640964508057},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6665080189704895},{"id":"https://openalex.org/C25989453","wikidata":"https://www.wikidata.org/wiki/Q446746","display_name":"Leaf area index","level":2,"score":0.6571779251098633},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6362979412078857},{"id":"https://openalex.org/C2780376076","wikidata":"https://www.wikidata.org/wiki/Q1499458","display_name":"Vegetation Index","level":4,"score":0.54776531457901},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.5197467803955078},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.47773808240890503},{"id":"https://openalex.org/C101000010","wikidata":"https://www.wikidata.org/wiki/Q5033434","display_name":"Canopy","level":2,"score":0.457692950963974},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4391917586326599},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4363839626312256},{"id":"https://openalex.org/C128990827","wikidata":"https://www.wikidata.org/wiki/Q192830","display_name":"Coefficient of determination","level":2,"score":0.41424497961997986},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.33677205443382263},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.32767295837402344},{"id":"https://openalex.org/C1549246","wikidata":"https://www.wikidata.org/wiki/Q718775","display_name":"Normalized Difference Vegetation Index","level":3,"score":0.2226453423500061},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.17247095704078674},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.14279642701148987},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.1280096471309662},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"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},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2018.8517823","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8517823","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1518917059","https://openalex.org/W1964217023","https://openalex.org/W1967395374","https://openalex.org/W1973410094","https://openalex.org/W2000102737","https://openalex.org/W2013328968","https://openalex.org/W2066612219","https://openalex.org/W2077707413","https://openalex.org/W2089441588","https://openalex.org/W2101010747","https://openalex.org/W2171979590","https://openalex.org/W6630885199"],"related_works":["https://openalex.org/W2377212262","https://openalex.org/W4327748155","https://openalex.org/W2955967599","https://openalex.org/W2549050738","https://openalex.org/W4387208895","https://openalex.org/W1594879216","https://openalex.org/W2388815296","https://openalex.org/W2386212941","https://openalex.org/W4383721055","https://openalex.org/W2768064775"],"abstract_inverted_index":{"This":[0],"paper":[1],"attempted":[2],"to":[3,53,68,95,110],"retrieve":[4,111],"leaf":[5,33],"area":[6],"index":[7],"(LAI)":[8],"from":[9,24,28,113],"Gaofen":[10],"(GF)-5":[11],"satellite":[12,46],"simulation":[13],"data":[14,115],"using":[15],"6":[16],"common":[17],"used":[18,52,67,94],"vegetation":[19,32,74],"indices.":[20],"The":[21,99,123],"canopy":[22],"reflectances":[23,57],"0.4-2.5\u03bcm":[25],"were":[26,51,93],"simulated":[27],"the":[29,55,70,73,97,108,128],"combination":[30],"of":[31,80,121],"model":[34],"PROSPECT":[35],"and":[36,60,76,78,87],"four-stream":[37],"scattering":[38],"by":[39],"arbitrarily":[40],"inclined":[41],"leaves":[42],"(4SAIL)":[43],"model.":[44],"GF-5":[45,114],"spectral":[47],"response":[48],"functions":[49],"(SRF)":[50],"calculate":[54],"band":[56],"in":[58],"visible":[59],"near":[61],"infrared":[62],"regions.":[63],"Polynomial":[64],"regression":[65],"was":[66],"establish":[69],"relationships":[71],"between":[72],"indices":[75,106],"LAI,":[77],"coefficient":[79],"determination":[81],"(R":[82],"<sup":[83,118],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[84,119],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[85,120],")":[86],"root":[88],"mean":[89],"square":[90],"error":[91],"(RMSE)":[92],"evaluate":[96],"relationships.":[98],"results":[100,124],"showed":[101,126],"that":[102,127],"DVI":[103],"among":[104],"those":[105],"is":[107],"best":[109],"LAI":[112],"with":[116],"R":[117],"0.964.":[122],"also":[125],"retrieval":[129],"accuracy":[130],"can":[131],"be":[132],"as":[133,135],"high":[134],"0.338.":[136]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}