{"id":"https://openalex.org/W2026423725","doi":"https://doi.org/10.1109/igarss.2012.6352321","title":"Mapping LAI and chlorophyll content from at-sensor APEX data using a Bayesian optimisation of a coupled canopy-atmosphere model","display_name":"Mapping LAI and chlorophyll content from at-sensor APEX data using a Bayesian optimisation of a coupled canopy-atmosphere model","publication_year":2012,"publication_date":"2012-07-01","ids":{"openalex":"https://openalex.org/W2026423725","doi":"https://doi.org/10.1109/igarss.2012.6352321","mag":"2026423725"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2012.6352321","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2012.6352321","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021388109","display_name":"V.C.E. Laurent","orcid":"https://orcid.org/0000-0003-1039-6945"},"institutions":[{"id":"https://openalex.org/I202697423","display_name":"University of Zurich","ror":"https://ror.org/02crff812","country_code":"CH","type":"education","lineage":["https://openalex.org/I202697423"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"V.C.E Laurent","raw_affiliation_strings":["Remote Sensing Laboratories, University of Zurich, Switzerland","Remote Sensing Laboratories, Univ. of Z\u00fcrich, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Remote Sensing Laboratories, University of Zurich, Switzerland","institution_ids":["https://openalex.org/I202697423"]},{"raw_affiliation_string":"Remote Sensing Laboratories, Univ. of Z\u00fcrich, Switzerland","institution_ids":["https://openalex.org/I202697423"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048370565","display_name":"W. Verhoef","orcid":"https://orcid.org/0000-0003-4696-2144"},"institutions":[{"id":"https://openalex.org/I94624287","display_name":"University of Twente","ror":"https://ror.org/006hf6230","country_code":"NL","type":"education","lineage":["https://openalex.org/I94624287"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"W. Verhoef","raw_affiliation_strings":["Faculty of Geo-Information Science and Earth Observation, University of Twente, Netherlands","Faculty of Geo-Information, Science and Earth Observation, University of Twente, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Geo-Information Science and Earth Observation, University of Twente, Netherlands","institution_ids":["https://openalex.org/I94624287"]},{"raw_affiliation_string":"Faculty of Geo-Information, Science and Earth Observation, University of Twente, The Netherlands","institution_ids":["https://openalex.org/I94624287"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017159201","display_name":"Michael E. Schaepman","orcid":"https://orcid.org/0000-0002-9627-9565"},"institutions":[{"id":"https://openalex.org/I202697423","display_name":"University of Zurich","ror":"https://ror.org/02crff812","country_code":"CH","type":"education","lineage":["https://openalex.org/I202697423"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"M.E. Schaepman","raw_affiliation_strings":["Remote Sensing Laboratories, University of Zurich, Switzerland","Remote Sensing Laboratories, Univ. of Z\u00fcrich, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Remote Sensing Laboratories, University of Zurich, Switzerland","institution_ids":["https://openalex.org/I202697423"]},{"raw_affiliation_string":"Remote Sensing Laboratories, Univ. of Z\u00fcrich, Switzerland","institution_ids":["https://openalex.org/I202697423"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066510854","display_name":"Alexander Damm","orcid":"https://orcid.org/0000-0001-8965-3427"},"institutions":[{"id":"https://openalex.org/I202697423","display_name":"University of Zurich","ror":"https://ror.org/02crff812","country_code":"CH","type":"education","lineage":["https://openalex.org/I202697423"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"A. Damm","raw_affiliation_strings":["Remote Sensing Laboratories, University of Zurich, Switzerland","Remote Sensing Laboratories, Univ. of Z\u00fcrich, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Remote Sensing Laboratories, University of Zurich, Switzerland","institution_ids":["https://openalex.org/I202697423"]},{"raw_affiliation_string":"Remote Sensing Laboratories, Univ. of Z\u00fcrich, Switzerland","institution_ids":["https://openalex.org/I202697423"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001842171","display_name":"J.G.P.W. Clevers","orcid":"https://orcid.org/0000-0002-0046-082X"},"institutions":[{"id":"https://openalex.org/I913481162","display_name":"Wageningen University & Research","ror":"https://ror.org/04qw24q55","country_code":"NL","type":"education","lineage":["https://openalex.org/I913481162"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"J.G.P.W. Clevers","raw_affiliation_strings":["Centre for Geo-Information, Wageningen University, Netherlands","Centre for Geo-information Wageningen University, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centre for Geo-Information, Wageningen University, Netherlands","institution_ids":["https://openalex.org/I913481162"]},{"raw_affiliation_string":"Centre for Geo-information Wageningen University, The Netherlands","institution_ids":["https://openalex.org/I913481162"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5916,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.72592933,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"5685","last_page":"5688"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9993000030517578,"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":0.9993000030517578,"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/T10766","display_name":"Urban Heat Island Mitigation","score":0.9846000075340271,"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/T10895","display_name":"Species Distribution and Climate Change","score":0.9793000221252441,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"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/radiance","display_name":"Radiance","score":0.7443087100982666},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.7044486999511719},{"id":"https://openalex.org/keywords/radiative-transfer","display_name":"Radiative transfer","score":0.6258542537689209},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.5728291869163513},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.5570298433303833},{"id":"https://openalex.org/keywords/leaf-area-index","display_name":"Leaf area index","score":0.5428124070167542},{"id":"https://openalex.org/keywords/atmosphere","display_name":"Atmosphere (unit)","score":0.5239044427871704},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.521103024482727},{"id":"https://openalex.org/keywords/atmospheric-radiative-transfer-codes","display_name":"Atmospheric radiative transfer codes","score":0.5028449892997742},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5027999877929688},{"id":"https://openalex.org/keywords/canopy","display_name":"Canopy","score":0.5022096633911133},{"id":"https://openalex.org/keywords/spectrometer","display_name":"Spectrometer","score":0.48879191279411316},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.4618239998817444},{"id":"https://openalex.org/keywords/imaging-spectrometer","display_name":"Imaging spectrometer","score":0.4184594750404358},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3563849925994873},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2716320753097534},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.23881796002388},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.149386465549469},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.14448386430740356},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.14182236790657043},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.13642364740371704},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1212063729763031},{"id":"https://openalex.org/keywords/botany","display_name":"Botany","score":0.08293896913528442}],"concepts":[{"id":"https://openalex.org/C23690007","wikidata":"https://www.wikidata.org/wiki/Q1411145","display_name":"Radiance","level":2,"score":0.7443087100982666},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.7044486999511719},{"id":"https://openalex.org/C74902906","wikidata":"https://www.wikidata.org/wiki/Q1190858","display_name":"Radiative transfer","level":2,"score":0.6258542537689209},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.5728291869163513},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.5570298433303833},{"id":"https://openalex.org/C25989453","wikidata":"https://www.wikidata.org/wiki/Q446746","display_name":"Leaf area index","level":2,"score":0.5428124070167542},{"id":"https://openalex.org/C65440619","wikidata":"https://www.wikidata.org/wiki/Q177974","display_name":"Atmosphere (unit)","level":2,"score":0.5239044427871704},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.521103024482727},{"id":"https://openalex.org/C199390426","wikidata":"https://www.wikidata.org/wiki/Q2353151","display_name":"Atmospheric radiative transfer codes","level":3,"score":0.5028449892997742},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5027999877929688},{"id":"https://openalex.org/C101000010","wikidata":"https://www.wikidata.org/wiki/Q5033434","display_name":"Canopy","level":2,"score":0.5022096633911133},{"id":"https://openalex.org/C33390570","wikidata":"https://www.wikidata.org/wiki/Q188463","display_name":"Spectrometer","level":2,"score":0.48879191279411316},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.4618239998817444},{"id":"https://openalex.org/C183852935","wikidata":"https://www.wikidata.org/wiki/Q6002848","display_name":"Imaging spectrometer","level":3,"score":0.4184594750404358},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3563849925994873},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2716320753097534},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.23881796002388},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.149386465549469},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.14448386430740356},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.14182236790657043},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.13642364740371704},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1212063729763031},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.08293896913528442},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/igarss.2012.6352321","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2012.6352321","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:www.zora.uzh.ch:68089","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401281","display_name":"Zurich Open Repository and Archive (University of Zurich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I202697423","host_organization_name":"University of Zurich","host_organization_lineage":["https://openalex.org/I202697423"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Laurent, Val\u00e9rie C E; Verhoef, W; Schaepman, Michael E; Damm, Alexander; Clevers, J G P W  (2012). Mapping LAI and chlorophyll content from at-sensor APEX data using a Bayesian optimisation of a coupled canopy-atmosphere model.  In: Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International, Munich, Germany, 22 July 2012 - 27 July 2012. IEEE International, 5685-5688.","raw_type":"Conference or Workshop Item"},{"id":"doi:10.5167/uzh-68089","is_oa":true,"landing_page_url":"https://doi.org/10.5167/uzh-68089","pdf_url":null,"source":{"id":"https://openalex.org/S7407051291","display_name":"Universit\u00e4t Z\u00fcrich, ZORA","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":""}],"best_oa_location":{"id":"pmh:oai:www.zora.uzh.ch:68089","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401281","display_name":"Zurich Open Repository and Archive (University of Zurich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I202697423","host_organization_name":"University of Zurich","host_organization_lineage":["https://openalex.org/I202697423"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Laurent, Val\u00e9rie C E; Verhoef, W; Schaepman, Michael E; Damm, Alexander; Clevers, J G P W  (2012). Mapping LAI and chlorophyll content from at-sensor APEX data using a Bayesian optimisation of a coupled canopy-atmosphere model.  In: Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International, Munich, Germany, 22 July 2012 - 27 July 2012. IEEE International, 5685-5688.","raw_type":"Conference or Workshop Item"},"sustainable_development_goals":[{"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2","score":0.6600000262260437}],"awards":[],"funders":[{"id":"https://openalex.org/F4320331149","display_name":"Board of the Swiss Federal Institutes of Technology","ror":"https://ror.org/01rvn4p91"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1512208174","https://openalex.org/W1968575417","https://openalex.org/W2002934707","https://openalex.org/W2007833591","https://openalex.org/W2030078894","https://openalex.org/W2060356694","https://openalex.org/W2084778007","https://openalex.org/W2115539456","https://openalex.org/W2117884339","https://openalex.org/W2139802794","https://openalex.org/W2166312616","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W4226068337","https://openalex.org/W2067703153","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","https://openalex.org/W4281254516"],"abstract_inverted_index":{"This":[0,30],"contribution":[1],"proposes":[2],"a":[3,8,15,24,87],"methodological":[4],"approach":[5,31],"based":[6],"on":[7],"coupled":[9],"canopy-atmosphere":[10],"radiative":[11],"transfer":[12],"model":[13],"and":[14,37,79,104],"Bayesian":[16,61],"optimization":[17,62],"algorithm,":[18],"which":[19],"allows":[20],"the":[21,28,43,54,71,83,96],"use":[22],"of":[23,53,76,95],"priori":[25],"data":[26,52],"in":[27,42,70,93],"retrieval.":[29],"was":[32],"used":[33],"to":[34,66],"estimate":[35],"LAI":[36,78],"leaf":[38],"chlorophyll":[39],"content":[40],"(Cab)":[41],"agricultural":[44],"test":[45],"site":[46],"Oensingen,":[47],"Switzerland,":[48],"from":[49],"at-sensor":[50],"radiance":[51],"new":[55],"airborne":[56],"APEX":[57],"imaging":[58],"spectrometer.":[59],"The":[60,73],"allowed":[63],"having":[64],"up":[65],"7":[67],"free":[68],"variables":[69],"optimization.":[72],"obtained":[74],"maps":[75],"estimated":[77],"Cab":[80],"values":[81,97],"at":[82],"field":[84],"level":[85],"show":[86],"good":[88],"agreement":[89],"with":[90],"our":[91],"expectations":[92],"terms":[94],"themselves,":[98],"but":[99],"also":[100],"their":[101],"variation":[102],"range":[103],"spread.":[105]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2013,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}