{"id":"https://openalex.org/W2073593684","doi":"https://doi.org/10.5589/m09-004","title":"Error and quality assessment for remotely sensed estimates of leaf area index","display_name":"Error and quality assessment for remotely sensed estimates of leaf area index","publication_year":2009,"publication_date":"2009-01-01","ids":{"openalex":"https://openalex.org/W2073593684","doi":"https://doi.org/10.5589/m09-004","mag":"2073593684"},"language":"en","primary_location":{"id":"doi:10.5589/m09-004","doi":"https://doi.org/10.5589/m09-004","is_oa":false,"landing_page_url":"https://doi.org/10.5589/m09-004","pdf_url":null,"source":{"id":"https://openalex.org/S85837164","display_name":"Canadian Journal of Remote Sensing","issn_l":"0703-8992","issn":["0703-8992","1712-7971","1712-798X"],"is_oa":false,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-c","jufo-1","norway-1","oarl","poland-100","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Canadian Journal of Remote Sensing","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"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/A5030189898","display_name":"D. M. McAllister","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"D M McAllister","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5056965453","display_name":"Caterina Valeo","orcid":"https://orcid.org/0000-0002-4056-8632","observed_orcids":["https://orcid.org/0000-0002-4056-8632"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"C. Valeo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2677,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.55942398,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":"35","issue":"2","first_page":"141","last_page":"151"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9897000193595886,"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":0.9897000193595886,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.0034000000450760126,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer 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":0.002300000051036477,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/leaf-area-index","display_name":"leaf area index","score":0.984000027179718},{"id":"https://openalex.org/keywords/lai-estimation","display_name":"LAI estimation","score":0.8450000286102295},{"id":"https://openalex.org/keywords/linear-spectral-mixture-analysis","display_name":"linear spectral mixture analysis","score":0.8199999928474426},{"id":"https://openalex.org/keywords/moisture-stress-index","display_name":"moisture stress index","score":0.9580000042915344},{"id":"https://openalex.org/keywords/vegetation-index","display_name":"vegetation indices","score":0.7310000061988831},{"id":"https://openalex.org/keywords/estimation-error","display_name":"estimation error","score":0.6209999918937683},{"id":"https://openalex.org/keywords/landscape-variability","display_name":"landscape variability","score":0.6840000152587891},{"id":"https://openalex.org/keywords/scale-dependence","display_name":"scale dependence","score":0.9169999957084656},{"id":"https://openalex.org/keywords/multiscale-analysis","display_name":"multiscale analysis","score":0.8209999799728394},{"id":"https://openalex.org/keywords/modis","display_name":"MODIS","score":0.9200000166893005},{"id":"https://openalex.org/keywords/spot-imagery","display_name":"SPOT satellite imagery","score":0.9879999756813049},{"id":"https://openalex.org/keywords/monte-carlo-simulation","display_name":"Monte Carlo simulation","score":0.6790000200271606}],"concepts":[{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6953725814819336},{"id":"https://openalex.org/C130066347","wikidata":"https://www.wikidata.org/wiki/Q680509","display_name":"Spectroradiometer","level":3,"score":0.668826162815094},{"id":"https://openalex.org/C25989453","wikidata":"https://www.wikidata.org/wiki/Q446746","display_name":"Leaf area index","level":2,"score":0.5993479490280151},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.53626549243927},{"id":"https://openalex.org/C2777007095","wikidata":"https://www.wikidata.org/wiki/Q676840","display_name":"Moderate-resolution imaging spectroradiometer","level":3,"score":0.5024781227111816},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.4794667959213257},{"id":"https://openalex.org/C150547873","wikidata":"https://www.wikidata.org/wiki/Q947851","display_name":"Watershed","level":2,"score":0.45944133400917053},{"id":"https://openalex.org/C1549246","wikidata":"https://www.wikidata.org/wiki/Q718775","display_name":"Normalized Difference Vegetation Index","level":3,"score":0.45853906869888306},{"id":"https://openalex.org/C78869512","wikidata":"https://www.wikidata.org/wiki/Q5378810","display_name":"Enhanced vegetation index","level":5,"score":0.4406862258911133},{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.4254700243473053},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4171966016292572},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.38868919014930725},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.382296621799469},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3661719560623169},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.30333930253982544},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.1734258234500885},{"id":"https://openalex.org/C2780376076","wikidata":"https://www.wikidata.org/wiki/Q1499458","display_name":"Vegetation Index","level":4,"score":0.1703084409236908},{"id":"https://openalex.org/C108597893","wikidata":"https://www.wikidata.org/wiki/Q663650","display_name":"Reflectivity","level":2,"score":0.14761731028556824},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.07778856158256531},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","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/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5589/m09-004","doi":"https://doi.org/10.5589/m09-004","is_oa":false,"landing_page_url":"https://doi.org/10.5589/m09-004","pdf_url":null,"source":{"id":"https://openalex.org/S85837164","display_name":"Canadian Journal of Remote Sensing","issn_l":"0703-8992","issn":["0703-8992","1712-7971","1712-798X"],"is_oa":false,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-c","jufo-1","norway-1","oarl","poland-100","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Canadian Journal of Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1964712650","https://openalex.org/W1997731494","https://openalex.org/W1999091234","https://openalex.org/W2010784770","https://openalex.org/W2032493415","https://openalex.org/W2036417688","https://openalex.org/W2037100013","https://openalex.org/W2051524227","https://openalex.org/W2052700773","https://openalex.org/W2078376456","https://openalex.org/W2082919734","https://openalex.org/W2083053342","https://openalex.org/W2089052758","https://openalex.org/W2090609279","https://openalex.org/W2094420085","https://openalex.org/W2106245975","https://openalex.org/W2109052600","https://openalex.org/W2110216534","https://openalex.org/W2152809678","https://openalex.org/W2155722785"],"related_works":["https://openalex.org/W7100108600","https://openalex.org/W2802398618","https://openalex.org/W2110216534","https://openalex.org/W4234076978","https://openalex.org/W7097949719","https://openalex.org/W3086568486","https://openalex.org/W2112292523","https://openalex.org/W3025354015","https://openalex.org/W3137493877","https://openalex.org/W2014983414"],"abstract_inverted_index":{"Four":[0],"techniques":[1,178],"for":[2],"estimating":[3],"leaf":[4],"area":[5],"index":[6],"(LAI)":[7],"from":[8],"remote":[9,176,191],"sensing":[10],"data":[11,116],"(linear":[12],"spectral":[13,21],"mixture":[14],"analysis,":[15],"moisture":[16],"stress":[17],"index,":[18],"modification":[19],"of":[20,45,49,53,63,73,90,101,149,152,165,189],"vegetation":[22],"indices,":[23],"and":[24,83,117],"normalized":[25],"distance":[26],"method)":[27],"were":[28,57],"investigated":[29],"to":[30,34,59,131,135,155,183],"determine":[31,132],"the":[32,36,43,61,71,79,84,102,133,137,147,150,163,166,190],"degree":[33],"which":[35,136],"parameters":[37,154],"associated":[38],"with":[39,158],"each":[40,64],"method":[41,193],"influence":[42],"quality":[44,62,72,82],"computed":[46],"landscape-level":[47,74],"estimates":[48,76],"LAI.":[50,91],"A":[51,92],"series":[52],"Monte":[54],"Carlo":[55],"simulations":[56,68],"used":[58],"test":[60],"estimation":[65,168,177,192],"method.":[66],"These":[67,160],"showed":[69],"that":[70,175],"LAI":[75],"depends":[77],"on":[78],"initial":[80],"modeling":[81],"inherent":[85],"landscape":[86],"variability":[87],"in":[88,107,185],"terms":[89],"multiscale":[93,171],"analysis":[94,128,145,172],"was":[95,129],"also":[96,173],"performed":[97,130],"across":[98],"a":[99,180],"portion":[100],"Upper":[103],"Elbow":[104],"River":[105],"watershed":[106],"Alberta,":[108],"Canada,":[109],"using":[110],"Moderate":[111],"Resolution":[112],"Imaging":[113],"Spectroradiometer":[114],"(MODIS)":[115],"resampled":[118],"Satellite":[119],"pour":[120],"l\u2019Observation":[121],"de":[122],"la":[123],"Terre":[124],"(SPOT)":[125],"imagery.":[126],"This":[127],"extent":[134],"derived":[138,167],"relationships":[139],"are":[140],"scale":[141],"dependent.":[142],"Spatial":[143],"statistical":[144],"revealed":[146],"tendency":[148],"correlation":[151],"input":[153],"vary":[156],"inversely":[157],"distance.":[159],"results":[161],"confirm":[162],"validity":[164],"relationships.":[169],"The":[170],"demonstrated":[174],"have":[179],"significant":[181],"sensitivity":[182],"variations":[184],"scale,":[186],"almost":[187],"irrespective":[188],"used.":[194]},"counts_by_year":[{"year":2012,"cited_by_count":1}],"updated_date":"2026-08-15T07:11:24.734988","created_date":"2016-06-24T00:00:00"}
