{"id":"https://openalex.org/W2900859473","doi":"https://doi.org/10.1109/igarss.2018.8518151","title":"Derivation of High Spatio-Temporal Resolution Leaf Area Index and Uncertainty Maps by Combining LAINet, CACAO and GPR","display_name":"Derivation of High Spatio-Temporal Resolution Leaf Area Index and Uncertainty Maps by Combining LAINet, CACAO and GPR","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2900859473","doi":"https://doi.org/10.1109/igarss.2018.8518151","mag":"2900859473"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2018.8518151","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518151","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":"conference-paper","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/A5005934331","display_name":"Gaofei Yin","orcid":"https://orcid.org/0000-0002-9828-7139"},"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/I4210124748","display_name":"Institute of Mountain Hazards and Environment","ror":"https://ror.org/02z0nsb22","country_code":"CN","type":"nonprofit","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210124748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gaofei Yin","raw_affiliation_strings":["Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210124748"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019197462","display_name":"Ainong Li","orcid":"https://orcid.org/0000-0002-4543-5118"},"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/I4210124748","display_name":"Institute of Mountain Hazards and Environment","ror":"https://ror.org/02z0nsb22","country_code":"CN","type":"nonprofit","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210124748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ainong Li","raw_affiliation_strings":["Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210124748"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":null,"first_page":"5960","last_page":"5963"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9991999864578247,"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":0.9991999864578247,"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/T10616","display_name":"Smart Agriculture and AI","score":0.9925000071525574,"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/T10266","display_name":"Plant Water Relations and Carbon Dynamics","score":0.9904000163078308,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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":0.7808018922805786},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.7298576235771179},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.6465432643890381},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.6231160163879395},{"id":"https://openalex.org/keywords/ground-penetrating-radar","display_name":"Ground-penetrating radar","score":0.5706360340118408},{"id":"https://openalex.org/keywords/temporal-resolution","display_name":"Temporal resolution","score":0.5441824197769165},{"id":"https://openalex.org/keywords/precision-agriculture","display_name":"Precision agriculture","score":0.536370038986206},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5066412091255188},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4748430550098419},{"id":"https://openalex.org/keywords/propagation-of-uncertainty","display_name":"Propagation of uncertainty","score":0.4743306040763855},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4594041407108307},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4021882712841034},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.3657758831977844},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.22835001349449158},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21236631274223328},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.19880414009094238},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.17922478914260864},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.15103378891944885},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.12180858850479126},{"id":"https://openalex.org/keywords/agriculture","display_name":"Agriculture","score":0.10344263911247253}],"concepts":[{"id":"https://openalex.org/C25989453","wikidata":"https://www.wikidata.org/wiki/Q446746","display_name":"Leaf area index","level":2,"score":0.7808018922805786},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.7298576235771179},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.6465432643890381},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.6231160163879395},{"id":"https://openalex.org/C71813955","wikidata":"https://www.wikidata.org/wiki/Q503560","display_name":"Ground-penetrating radar","level":3,"score":0.5706360340118408},{"id":"https://openalex.org/C119666444","wikidata":"https://www.wikidata.org/wiki/Q5977280","display_name":"Temporal resolution","level":2,"score":0.5441824197769165},{"id":"https://openalex.org/C120217122","wikidata":"https://www.wikidata.org/wiki/Q740083","display_name":"Precision agriculture","level":3,"score":0.536370038986206},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5066412091255188},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4748430550098419},{"id":"https://openalex.org/C123614077","wikidata":"https://www.wikidata.org/wiki/Q1364905","display_name":"Propagation of uncertainty","level":2,"score":0.4743306040763855},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4594041407108307},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4021882712841034},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3657758831977844},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.22835001349449158},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21236631274223328},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19880414009094238},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.17922478914260864},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.15103378891944885},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12180858850479126},{"id":"https://openalex.org/C118518473","wikidata":"https://www.wikidata.org/wiki/Q11451","display_name":"Agriculture","level":2,"score":0.10344263911247253},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2018.8518151","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518151","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":[{"display_name":"Zero hunger","score":0.6600000262260437,"id":"https://metadata.un.org/sdg/2"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1746819321","https://openalex.org/W1977083889","https://openalex.org/W1977290837","https://openalex.org/W1986812364","https://openalex.org/W1997904108","https://openalex.org/W1999051604","https://openalex.org/W2021494835","https://openalex.org/W2053476149","https://openalex.org/W2073226970","https://openalex.org/W2088348477","https://openalex.org/W2138448722","https://openalex.org/W2158834676","https://openalex.org/W2200350976","https://openalex.org/W2290567182","https://openalex.org/W2557818291","https://openalex.org/W2567650967","https://openalex.org/W2574954317","https://openalex.org/W4211049957","https://openalex.org/W6731580910"],"related_works":["https://openalex.org/W4315471419","https://openalex.org/W2946057701","https://openalex.org/W4386931161","https://openalex.org/W2374146176","https://openalex.org/W2065249286","https://openalex.org/W2366839571","https://openalex.org/W4223960160","https://openalex.org/W2027762722","https://openalex.org/W2356754952","https://openalex.org/W2217449633"],"abstract_inverted_index":{"We":[0],"proposed":[1,120],"a":[2,42,60,91,125],"framework":[3,151],"to":[4,29,53,66,77,98,105,175],"generate":[5],"high":[6,69,79],"spatio-temporal":[7,80],"resolution":[8,73,81,183],"leaf":[9],"area":[10],"index":[11],"(LAI)":[12],"and":[13,34,70,110,132,141,178],"uncertainty":[14,114,135,161],"maps":[15,131,136,162],"based":[16,46],"on":[17],"the":[18,27,68,87,100,112,119,150,159,166,169],"integration":[19],"of":[20,26,118,168],"LAINet":[21],"observation":[22,49],"system,":[23],"Consistent":[24],"Adjustment":[25],"Climatology":[28],"Actual":[30],"Observations":[31],"(CACAO)":[32],"method":[33,121],"Gaussian":[35],"process":[36],"regression":[37,94],"(GPR).":[38],"LAINet,":[39],"which":[40],"is":[41],"wireless":[43],"sensor":[44],"network":[45],"automatic":[47],"LAI":[48,108,130,155,170,184],"instrument,":[50],"was":[51,64,96,122],"used":[52,65,97],"provide":[54,153,163],"temporally":[55],"continuous":[56],"field":[57,88,103],"measurements;":[58],"CACAO,":[59],"data":[61],"blending":[62],"method,":[63],"blend":[67],"low":[71],"spatial":[72],"remote":[74,82],"sensing":[75,83],"observations":[76,84],"obtain":[78],"synchronous":[85],"with":[86,138],"measurements.":[89],"GPR,":[90],"machine":[92],"learning":[93],"algorithm,":[95],"upscale":[99],"spatially":[101,106],"discrete":[102],"measurements":[104],"explicit":[107],"maps,":[109],"get":[111],"concomitant":[113,160],"maps.":[115],"The":[116],"performance":[117],"evaluated":[123],"over":[124],"crop":[126],"site,":[127],"where":[128],"seven":[129],"their":[133],"accompanying":[134],"all":[137],"30":[139],"m":[140],"8":[142],"days":[143],"resolutions":[144],"were":[145],"generated.":[146],"Results":[147],"show":[148],"that":[149],"can":[152],"accurate":[154],"retrievals.":[156,171],"In":[157],"addition,":[158],"insight":[164],"into":[165],"reliability":[167],"This":[172],"paper":[173],"contributes":[174],"precision":[176],"agriculture":[177],"validation":[179],"activities":[180],"for":[181],"coarse":[182],"products.":[185]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}