{"id":"https://openalex.org/W2953483448","doi":"https://doi.org/10.1109/whispers.2018.8747097","title":"Inverting Procosine-D For Very High Spatial and Temporal Resolution Retrieval of Foliar Biochemistry","display_name":"Inverting Procosine-D For Very High Spatial and Temporal Resolution Retrieval of Foliar Biochemistry","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2953483448","doi":"https://doi.org/10.1109/whispers.2018.8747097","mag":"2953483448"},"language":"en","primary_location":{"id":"doi:10.1109/whispers.2018.8747097","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2018.8747097","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","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/A5091317945","display_name":"Henning Buddenbaum","orcid":"https://orcid.org/0000-0002-0956-5628"},"institutions":[{"id":"https://openalex.org/I89864525","display_name":"Universit\u00e4t Trier","ror":"https://ror.org/02778hg05","country_code":"DE","type":"education","lineage":["https://openalex.org/I89864525"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Henning Buddenbaum","raw_affiliation_strings":["Environmental Remote Sensing and Geoinformatics, Trier University, Trier, Germany"],"affiliations":[{"raw_affiliation_string":"Environmental Remote Sensing and Geoinformatics, Trier University, Trier, Germany","institution_ids":["https://openalex.org/I89864525"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5091317945"],"corresponding_institution_ids":["https://openalex.org/I89864525"],"apc_list":null,"apc_paid":null,"fwci":0.1906,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.62817438,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9940999746322632,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/vnir","display_name":"VNIR","score":0.7567824125289917},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.5966050624847412},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5832812190055847},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.48293444514274597},{"id":"https://openalex.org/keywords/beech","display_name":"Beech","score":0.47511348128318787},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.4693630337715149},{"id":"https://openalex.org/keywords/greenhouse","display_name":"Greenhouse","score":0.4268411099910736},{"id":"https://openalex.org/keywords/botany","display_name":"Botany","score":0.336078017950058},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2810044586658478},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2584994435310364},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.17759975790977478},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.15028789639472961}],"concepts":[{"id":"https://openalex.org/C5457282","wikidata":"https://www.wikidata.org/wiki/Q7907352","display_name":"VNIR","level":3,"score":0.7567824125289917},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.5966050624847412},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5832812190055847},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.48293444514274597},{"id":"https://openalex.org/C2776500793","wikidata":"https://www.wikidata.org/wiki/Q25403","display_name":"Beech","level":2,"score":0.47511348128318787},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.4693630337715149},{"id":"https://openalex.org/C32198211","wikidata":"https://www.wikidata.org/wiki/Q165044","display_name":"Greenhouse","level":2,"score":0.4268411099910736},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.336078017950058},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2810044586658478},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2584994435310364},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.17759975790977478},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.15028789639472961}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/whispers.2018.8747097","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2018.8747097","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321602","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt","ror":"https://ror.org/04bwf3e34"},{"id":"https://openalex.org/F4320323803","display_name":"Bundesministerium f\u00fcr Wirtschaft und Energie","ror":"https://ror.org/02vgg2808"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1821652139","https://openalex.org/W1978283906","https://openalex.org/W2051128904","https://openalex.org/W2066612219","https://openalex.org/W2091166556","https://openalex.org/W2121025745","https://openalex.org/W2288553003","https://openalex.org/W2596051487","https://openalex.org/W2620535180","https://openalex.org/W2775006744","https://openalex.org/W3177219931"],"related_works":["https://openalex.org/W4387802641","https://openalex.org/W2027460042","https://openalex.org/W2045337428","https://openalex.org/W2044082451","https://openalex.org/W2801095402","https://openalex.org/W2317401237","https://openalex.org/W1990800631","https://openalex.org/W2167120702","https://openalex.org/W2025039112","https://openalex.org/W2579567122"],"abstract_inverted_index":{"A":[0,29],"combination":[1],"of":[2,18,32,37,66],"the":[3,9,67,90,94,104,118,129],"leaf":[4,19,68],"reflectance":[5,125],"model":[6,11,126],"PROSPECT-D":[7],"and":[8,39,74,84,97,109,124,147],"directional":[10],"COSINE":[12],"was":[13,44],"inverted":[14],"to":[15,131,140],"create":[16],"maps":[17],"constituents":[20,69],"in":[21,79,89,103,134],"millimeter":[22],"resolution":[23],"from":[24,46,117],"field":[25],"imaging":[26,122],"spectroscopy":[27,123],"data.":[28,120],"diurnal":[30],"series":[31,73],"26":[33],"HySpex":[34],"VNIR":[35,119],"images":[36],"well-watered":[38,91],"drought-stressed":[40,105],"young":[41],"beech":[42],"trees":[43,92],"created":[45],"a":[47,53,57],"3.8":[48],"m":[49],"high":[50],"platform":[51],"with":[52,70],"hyperspectral":[54],"camera":[55],"on":[56,144],"rotation":[58],"stage.":[59],"Inversion":[60],"results":[61],"show":[62],"detailed":[63],"spatial":[64],"distribution":[65],"meaningful":[71],"time":[72],"distinction":[75],"between":[76],"both":[77],"groups":[78],"some":[80],"parameters.":[81],"While":[82],"chlorophyll":[83],"carotenoid":[85],"contents":[86,100],"are":[87,101],"higher":[88,102],"throughout":[93],"day,":[95],"anthocyanins":[96],"brown":[98],"matter":[99,111],"trees.":[106],"Leaf":[107],"water":[108],"dry":[110],"content":[112],"cannot":[113],"be":[114],"reliably":[115],"derived":[116],"Field":[121],"inversion":[127],"offer":[128],"capability":[130],"monitor":[132],"plants":[133],"environments":[135],"like":[136],"orchards":[137],"or":[138],"greenhouses":[139],"get":[141],"timely":[142],"information":[143],"plant":[145],"growth":[146],"health.":[148]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
