{"id":"https://openalex.org/W1903096925","doi":"https://doi.org/10.1109/igarss.2010.5653678","title":"Retrieval of time series LAI by coupling an empirical crop growth model with a radiative transfer model","display_name":"Retrieval of time series LAI by coupling an empirical crop growth model with a radiative transfer model","publication_year":2010,"publication_date":"2010-07-01","ids":{"openalex":"https://openalex.org/W1903096925","doi":"https://doi.org/10.1109/igarss.2010.5653678","mag":"1903096925"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2010.5653678","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2010.5653678","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 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/A5107597668","display_name":"Guangjian Yan","orcid":"https://orcid.org/0000-0001-5030-748X"},"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":"Guangjian Yan","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, 100875, China","State key laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, 100875, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, 100875, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]},{"raw_affiliation_string":"State key laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, 100875, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110377916","display_name":"Xiaoyan Yang","orcid":null},"institutions":[{"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"]},{"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyan Yang","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, 100875, China","State key laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, 100875, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, 100875, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]},{"raw_affiliation_string":"State key laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, 100875, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112559416","display_name":"Jing Li","orcid":"https://orcid.org/0000-0001-9736-5732"},"institutions":[{"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"]},{"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Li","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, 100875, China","State key laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, 100875, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, 100875, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]},{"raw_affiliation_string":"State key laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, 100875, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082646129","display_name":"Xihan Mu","orcid":"https://orcid.org/0000-0003-4812-3045"},"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":"Xihan Mu","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, 100875, China","State key laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, 100875, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, 100875, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]},{"raw_affiliation_string":"State key laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, 100875, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5107597668"],"corresponding_institution_ids":["https://openalex.org/I25254941","https://openalex.org/I4210166112"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.07112829,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"3","issue":null,"first_page":"1645","last_page":"1647"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.998199999332428,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9902999997138977,"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/inversion","display_name":"Inversion (geology)","score":0.7310305833816528},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6236323118209839},{"id":"https://openalex.org/keywords/radiative-transfer","display_name":"Radiative transfer","score":0.5752972364425659},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5541302561759949},{"id":"https://openalex.org/keywords/atmospheric-radiative-transfer-codes","display_name":"Atmospheric radiative transfer codes","score":0.5528009533882141},{"id":"https://openalex.org/keywords/temporal-resolution","display_name":"Temporal resolution","score":0.5467209219932556},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.5061680674552917},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.49630147218704224},{"id":"https://openalex.org/keywords/leaf-area-index","display_name":"Leaf area index","score":0.49368223547935486},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4294635057449341},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3536790609359741},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.3364157974720001},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.12661832571029663},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.11540210247039795},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09001308679580688},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.08312481641769409}],"concepts":[{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.7310305833816528},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6236323118209839},{"id":"https://openalex.org/C74902906","wikidata":"https://www.wikidata.org/wiki/Q1190858","display_name":"Radiative transfer","level":2,"score":0.5752972364425659},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5541302561759949},{"id":"https://openalex.org/C199390426","wikidata":"https://www.wikidata.org/wiki/Q2353151","display_name":"Atmospheric radiative transfer codes","level":3,"score":0.5528009533882141},{"id":"https://openalex.org/C119666444","wikidata":"https://www.wikidata.org/wiki/Q5977280","display_name":"Temporal resolution","level":2,"score":0.5467209219932556},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.5061680674552917},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.49630147218704224},{"id":"https://openalex.org/C25989453","wikidata":"https://www.wikidata.org/wiki/Q446746","display_name":"Leaf area index","level":2,"score":0.49368223547935486},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4294635057449341},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3536790609359741},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.3364157974720001},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.12661832571029663},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.11540210247039795},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09001308679580688},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.08312481641769409},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C109007969","wikidata":"https://www.wikidata.org/wiki/Q749565","display_name":"Structural basin","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2010.5653678","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2010.5653678","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","display_name":"No poverty","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1966483641","https://openalex.org/W1975108950","https://openalex.org/W1984680692","https://openalex.org/W1989403585","https://openalex.org/W1999310382","https://openalex.org/W2008183434","https://openalex.org/W2057021477","https://openalex.org/W3215395091"],"related_works":["https://openalex.org/W4226068337","https://openalex.org/W2067703153","https://openalex.org/W2217449633","https://openalex.org/W3198701072","https://openalex.org/W2067958002","https://openalex.org/W2731864949","https://openalex.org/W4220727947","https://openalex.org/W2118791227","https://openalex.org/W2018494703","https://openalex.org/W1483386591"],"abstract_inverted_index":{"Continuous":[0],"LAI":[1,16,45,78],"values":[2],"are":[3,18],"very":[4,36],"important":[5],"in":[6,94],"crop":[7,32,52,56],"growth":[8,57],"monitoring,":[9],"however,":[10],"all":[11],"of":[12,110],"the":[13,21,76,91,95,111],"remotely":[14],"sensed":[15],"products":[17],"limited":[19],"by":[20,80,103],"temporal":[22,38],"and":[23],"spatial":[24,27],"resolution.":[25],"High":[26],"resolution":[28],"is":[29,47],"good":[30],"for":[31,51],"monitoring":[33],"but":[34],"with":[35,71],"poor":[37],"sampling.":[39],"The":[40,97],"popular":[41],"MODIS":[42],"8":[43],"day":[44,79],"product":[46],"still":[48],"not":[49],"sufficient":[50],"monitoring.":[53],"An":[54],"empirical":[55],"model":[58,73],"was":[59,68,86,101],"developed":[60],"based":[61],"on":[62],"two":[63],"years'":[64],"ground":[65],"truth.":[66],"It":[67],"then":[69],"coupled":[70,99],"SAILH":[72],"to":[74,89],"retrieve":[75],"continuous":[77],"day.":[81],"A":[82],"rolling":[83],"inversion":[84,100,113],"strategy":[85],"proposed":[87],"further":[88],"minimize":[90],"random":[92],"noise":[93],"observations.":[96],"models":[98],"tested":[102],"simulation":[104],"inversion.":[105],"Results":[106],"show":[107],"significant":[108],"improvements":[109],"new":[112],"method.":[114]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}