{"id":"https://openalex.org/W2905383270","doi":"https://doi.org/10.1109/tgrs.2018.2882623","title":"A Spectral Assignment-Oriented Approach to Improve Interpretability and Accuracy of Proxy Spectral-Based Models","display_name":"A Spectral Assignment-Oriented Approach to Improve Interpretability and Accuracy of Proxy Spectral-Based Models","publication_year":2018,"publication_date":"2018-12-11","ids":{"openalex":"https://openalex.org/W2905383270","doi":"https://doi.org/10.1109/tgrs.2018.2882623","mag":"2905383270"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2018.2882623","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2018.2882623","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-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/A5081864359","display_name":"Nimrod Carmon","orcid":"https://orcid.org/0000-0002-9211-2290"},"institutions":[{"id":"https://openalex.org/I16391192","display_name":"Tel Aviv University","ror":"https://ror.org/04mhzgx49","country_code":"IL","type":"education","lineage":["https://openalex.org/I16391192"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Nimrod Carmon","raw_affiliation_strings":["Porter School of Environment and Earth Sciences, Tel Aviv University, Tel Aviv, Israel"],"raw_orcid":"https://orcid.org/0000-0002-9211-2290","affiliations":[{"raw_affiliation_string":"Porter School of Environment and Earth Sciences, Tel Aviv University, Tel Aviv, Israel","institution_ids":["https://openalex.org/I16391192"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111392166","display_name":"Eyal Ben\u2010Dor","orcid":null},"institutions":[{"id":"https://openalex.org/I16391192","display_name":"Tel Aviv University","ror":"https://ror.org/04mhzgx49","country_code":"IL","type":"education","lineage":["https://openalex.org/I16391192"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Eyal Ben-Dor","raw_affiliation_strings":["Porter School of Environment and Earth Sciences, Tel Aviv University, Tel Aviv, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Porter School of Environment and Earth Sciences, Tel Aviv University, Tel Aviv, Israel","institution_ids":["https://openalex.org/I16391192"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1618,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.49265611,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"57","issue":"6","first_page":"3221","last_page":"3228"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/2311","display_name":"Industrial and Manufacturing 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/T10836","display_name":"Metabolomics and Mass Spectrometry Studies","score":0.9872000217437744,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.9730722308158875},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8727320432662964},{"id":"https://openalex.org/keywords/partial-least-squares-regression","display_name":"Partial least squares regression","score":0.7630226016044617},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.5229526162147522},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5219689607620239},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.48105740547180176},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4405362606048584},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.42947983741760254},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.416837215423584},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38108664751052856},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36856839060783386},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3474929928779602},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2685220241546631}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9730722308158875},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8727320432662964},{"id":"https://openalex.org/C22354355","wikidata":"https://www.wikidata.org/wiki/Q422009","display_name":"Partial least squares regression","level":2,"score":0.7630226016044617},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.5229526162147522},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5219689607620239},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.48105740547180176},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4405362606048584},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.42947983741760254},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.416837215423584},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38108664751052856},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36856839060783386},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3474929928779602},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2685220241546631},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2018.2882623","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2018.2882623","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320337325","display_name":"Facultad de Ciencias Exactas, Universidad Nacional de La Plata","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1587631480","https://openalex.org/W1966649791","https://openalex.org/W1966757639","https://openalex.org/W1972273299","https://openalex.org/W1973111333","https://openalex.org/W1977583818","https://openalex.org/W1978207903","https://openalex.org/W1984114559","https://openalex.org/W1990195132","https://openalex.org/W1996195892","https://openalex.org/W1998863103","https://openalex.org/W2007365900","https://openalex.org/W2018194343","https://openalex.org/W2022110298","https://openalex.org/W2040629518","https://openalex.org/W2045858843","https://openalex.org/W2054625992","https://openalex.org/W2055036777","https://openalex.org/W2059994293","https://openalex.org/W2098136451","https://openalex.org/W2102123872","https://openalex.org/W2153243697","https://openalex.org/W2155278882","https://openalex.org/W2165993842","https://openalex.org/W2321998745","https://openalex.org/W2586813976","https://openalex.org/W2617834892","https://openalex.org/W2766058305","https://openalex.org/W2766916456","https://openalex.org/W2790080658","https://openalex.org/W2793322197","https://openalex.org/W2801397115","https://openalex.org/W2983390845"],"related_works":["https://openalex.org/W2025672346","https://openalex.org/W57792804","https://openalex.org/W3166376400","https://openalex.org/W2012210188","https://openalex.org/W2913581471","https://openalex.org/W2354728162","https://openalex.org/W1970488785","https://openalex.org/W1985322979","https://openalex.org/W2908655904","https://openalex.org/W2809343789","https://openalex.org/W3188195749","https://openalex.org/W2020447651","https://openalex.org/W3150877556","https://openalex.org/W3207444164","https://openalex.org/W2001862591","https://openalex.org/W3167904548","https://openalex.org/W2347982959","https://openalex.org/W2350332581","https://openalex.org/W3101061034","https://openalex.org/W3112670712"],"abstract_inverted_index":{"In":[0,33],"modeling":[1,20,41,58],"chemical":[2],"attributes":[3],"using":[4,145],"hyperspectral":[5,131],"data,":[6],"nonlinear":[7,19,57],"relationships":[8],"between":[9,110],"the":[10,13,31,85,88,93,100,105,173,192],"predictor":[11],"and":[12,149,185],"response":[14,101],"are":[15],"frequent.":[16],"The":[17,64],"common":[18],"techniques":[21],"improve":[22],"prediction":[23],"accuracy":[24,184],"but":[25],"suffer":[26],"from":[27],"low":[28],"interpretability":[29,62],"of":[30,77,84,133,175,191],"models.":[32],"this":[34,67],"paper,":[35],"we":[36],"demonstrate":[37,172],"a":[38,56,72,146,151,188],"new":[39],"multivariate":[40],"method,":[42],"denoted":[43],"as":[44],"spectral":[45,79,108,153,160],"assignment-oriented":[46],"partial":[47,178],"least":[48],"squares":[49],"(SAO-PLS),":[50],"which":[51,164],"is":[52,69,114],"designed":[53],"to":[54,117,163],"provide":[55],"solution":[59],"with":[60,121,137,157],"strong":[61],"products.":[63],"need":[65],"for":[66,81,181],"approach":[68],"apparent":[70],"when":[71],"given":[73],"sample":[74],"population":[75],"consists":[76],"different":[78,82,122],"features":[80],"levels":[83],"response.":[86],"Accordingly,":[87],"suggested":[89],"SAO-PLS":[90,113,176],"algorithm":[91],"segments":[92],"data":[94,127,132],"in":[95,107,138],"an":[96,125,158],"optimal":[97],"location":[98],"on":[99],"distribution":[102],"by":[103],"maximizing":[104],"difference":[106],"assignments":[109],"two":[111,118],"clusters.":[112],"applied":[115],"here":[116],"test":[119],"cases":[120],"characteristics:":[123],"1)":[124],"established":[126],"set":[128],"containing":[129],"airborne":[130],"asphaltic":[134],"roads,":[135],"merged":[136],"situ":[139],"measured":[140,156],"dynamic":[141],"friction":[142],"values":[143],"captured":[144],"standardized":[147],"method":[148],"2)":[150],"soil":[152],"library,":[154],"spectrally":[155],"analytical":[159],"device":[161],"spectrometer,":[162],"organic":[165],"carbon":[166],"measurements":[167],"were":[168],"applied.":[169],"Our":[170],"results":[171],"superiority":[174],"over":[177],"least-squares":[179],"regression":[180],"both":[182],"model":[183],"interpretability,":[186],"providing":[187],"deeper":[189],"understanding":[190],"underlying":[193],"processes.":[194]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
