{"id":"https://openalex.org/W2612483188","doi":"https://doi.org/10.3390/rs9050473","title":"Validation of Abundance Map Reference Data for Spectral Unmixing","display_name":"Validation of Abundance Map Reference Data for Spectral Unmixing","publication_year":2017,"publication_date":"2017-05-12","ids":{"openalex":"https://openalex.org/W2612483188","doi":"https://doi.org/10.3390/rs9050473","mag":"2612483188"},"language":"en","primary_location":{"id":"doi:10.3390/rs9050473","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs9050473","pdf_url":"https://www.mdpi.com/2072-4292/9/5/473/pdf?version=1494585544","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/9/5/473/pdf?version=1494585544","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026025255","display_name":"McKay Williams","orcid":null},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"McKay Williams","raw_affiliation_strings":["Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY 14623, USA"],"affiliations":[{"raw_affiliation_string":"Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY 14623, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074150108","display_name":"Robert Parody","orcid":null},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Robert Parody","raw_affiliation_strings":["School of Mathematical Sciences, Rochester Institute of Technology, Rochester, NY 14623, USA"],"affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, Rochester Institute of Technology, Rochester, NY 14623, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010566239","display_name":"Alexander Fafard","orcid":"https://orcid.org/0000-0002-7879-2234"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexander Fafard","raw_affiliation_strings":["Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY 14623, USA"],"affiliations":[{"raw_affiliation_string":"Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY 14623, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040385195","display_name":"John P. Kerekes","orcid":"https://orcid.org/0000-0002-0754-8170"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John Kerekes","raw_affiliation_strings":["Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY 14623, USA"],"affiliations":[{"raw_affiliation_string":"Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY 14623, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085740223","display_name":"Jan van Aardt","orcid":"https://orcid.org/0000-0002-3036-0088"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jan Van Aardt","raw_affiliation_strings":["Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY 14623, USA"],"affiliations":[{"raw_affiliation_string":"Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY 14623, USA","institution_ids":["https://openalex.org/I155173764"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5026025255"],"corresponding_institution_ids":["https://openalex.org/I155173764"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.6389,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.86656489,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"9","issue":"5","first_page":"473","last_page":"473"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9990000128746033,"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/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.991599977016449,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6417436599731445},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.6336633563041687},{"id":"https://openalex.org/keywords/reference-data","display_name":"Reference data","score":0.6229520440101624},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.6083791255950928},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5848740339279175},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5037185549736023},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.43374091386795044},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4223843514919281},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38991695642471313},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.24927017092704773},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.1933366358280182},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.13832500576972961},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.09536769986152649}],"concepts":[{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6417436599731445},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.6336633563041687},{"id":"https://openalex.org/C60478076","wikidata":"https://www.wikidata.org/wiki/Q3036835","display_name":"Reference data","level":2,"score":0.6229520440101624},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.6083791255950928},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5848740339279175},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5037185549736023},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.43374091386795044},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4223843514919281},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38991695642471313},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.24927017092704773},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.1933366358280182},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13832500576972961},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.09536769986152649},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs9050473","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs9050473","pdf_url":"https://www.mdpi.com/2072-4292/9/5/473/pdf?version=1494585544","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:mdpi.com:/2072-4292/9/5/473/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs9050473","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 9; Issue 5; Pages: 473","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs9050473","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs9050473","pdf_url":"https://www.mdpi.com/2072-4292/9/5/473/pdf?version=1494585544","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G209756880","display_name":null,"funder_award_id":"NNX12AQ24G","funder_id":"https://openalex.org/F4320306101","funder_display_name":"National Aeronautics and Space Administration"},{"id":"https://openalex.org/G6096010750","display_name":null,"funder_award_id":"0752017","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6595181174","display_name":null,"funder_award_id":"DBI-0752017","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306101","display_name":"National Aeronautics and Space Administration","ror":"https://ror.org/027ka1x80"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2612483188.pdf","grobid_xml":"https://content.openalex.org/works/W2612483188.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W571150846","https://openalex.org/W846821018","https://openalex.org/W1591388113","https://openalex.org/W1979839678","https://openalex.org/W2010265430","https://openalex.org/W2010797000","https://openalex.org/W2019899368","https://openalex.org/W2022470997","https://openalex.org/W2032046865","https://openalex.org/W2034932500","https://openalex.org/W2037328426","https://openalex.org/W2058891717","https://openalex.org/W2069921544","https://openalex.org/W2075665712","https://openalex.org/W2087964169","https://openalex.org/W2112118618","https://openalex.org/W2114486983","https://openalex.org/W2120184245","https://openalex.org/W2123907688","https://openalex.org/W2124386111","https://openalex.org/W2128686953","https://openalex.org/W2147555557","https://openalex.org/W2156419436","https://openalex.org/W2157321686","https://openalex.org/W2163886442","https://openalex.org/W2170186417","https://openalex.org/W2400770128","https://openalex.org/W2504793552","https://openalex.org/W2506684654","https://openalex.org/W2508058002","https://openalex.org/W2519257651","https://openalex.org/W2998399533","https://openalex.org/W4233760599","https://openalex.org/W4245539475","https://openalex.org/W4300420063","https://openalex.org/W4301109526","https://openalex.org/W4410620231","https://openalex.org/W6677703657","https://openalex.org/W6922696963"],"related_works":["https://openalex.org/W4295532600","https://openalex.org/W2063823869","https://openalex.org/W2088899772","https://openalex.org/W2020734820","https://openalex.org/W2937739364","https://openalex.org/W1987289672","https://openalex.org/W1773688426","https://openalex.org/W4385362411","https://openalex.org/W2519489155","https://openalex.org/W2268445639"],"abstract_inverted_index":{"The":[0,72,322],"purpose":[1],"of":[2,10,40,65,69,93,113,161,175,187,199,212,219,223,241,260,269,275,278,289,295,299,306,320,325],"this":[3,76,318],"study":[4],"is":[5,231,328],"to":[6,25,35,53,62,104,193,234,245,247,333],"validate":[7],"the":[8,38,91,114,176,197,205,209,217,279,341],"accuracy":[9,324],"abundance":[11,345],"map":[12],"reference":[13,26,84,188,224,347],"data":[14,27,85,103,189,225,348],"(AMRD)":[15],"for":[16,107,173,226,317,349],"three":[17,115,152],"airborne":[18,350],"imaging":[19],"spectrometer":[20],"(IS)":[21],"scenes.":[22],"AMRD":[23,73,106,121,164,242],"refers":[24],"maps":[28],"(\u201cground":[29],"truth\u201d)":[30],"that":[31,184,216],"are":[32],"specifically":[33],"designed":[34],"quantitatively":[36],"assess":[37],"performance":[39,198],"spectral":[41,58],"unmixing":[42,59,97,202],"algorithms.":[43,153,203],"While":[44],"classification":[45,95,200],"algorithms":[46,98,281],"typically":[47],"label":[48],"whole":[49],"pixels":[50,61],"as":[51,284],"belonging":[52],"certain":[54],"ground":[55,178],"cover":[56,179],"classes,":[57],"allows":[60],"be":[63],"composed":[64],"fractions":[66],"or":[67,96],"abundances":[68],"each":[70,227],"class.":[71],"validated":[74,344],"in":[75,122,195],"paper":[77],"were":[78,170,243,255],"generated":[79],"using":[80,129],"our":[81,166],"previously-proposed":[82],"remotely-sensed":[83],"(RSRD)":[86],"technique,":[87],"which":[88,263],"spatially":[89],"aggregates":[90],"results":[92,182,254,339],"standard":[94,273,293],"from":[99,165],"fine":[100],"spatial-scale":[101],"IS":[102,110,351],"produce":[105],"co-located":[108],"coarse-scale":[109],"data.":[111,352],"Validation":[112],"scenes":[116],"was":[117,282],"accomplished":[118],"by":[119,141,146,151,257],"estimating":[120],"51":[123],"randomly-selected":[124],"10":[125],"m\u00d710":[126],"m":[127],"plots,":[128],"seven":[130],"independent":[131,136,210,239],"methods":[132,327],"and":[133,149,229,250],"observers.":[134],"These":[135,181,338],"estimates":[137],"included":[138],"field":[139,168],"surveys":[140,169],"two":[142,147,167,174],"observers,":[143],"imagery":[144,261],"analysis":[145,298],"observers":[148],"RSRD":[150,280,326],"Results":[154],"indicated":[155],"statistically-significant":[156],"differences":[157,207,268,288],"between":[158,208,308],"all":[159,185,220],"versions":[160,211,222,240],"AMRD.":[162,337],"Even":[163],"significantly":[171],"different":[172],"four":[177],"classes.":[180],"suggest":[183],"forms":[186],"require":[190],"validation":[191],"prior":[192],"use":[194],"assessing":[196],"and/or":[201],"Given":[204],"significant":[206],"AMRD,":[213],"we":[214],"propose":[215],"mean":[218,265,287],"(MOA)":[221],"plot":[228],"class":[230],"most":[232],"likely":[233],"represent":[235],"true":[236],"abundances.":[237],"Our":[238],"compared":[244],"MOA":[246],"characterize":[248],"error":[249],"uncertainty.":[251],"Best":[252],"case":[253],"achieved":[256],"a":[258,272,292],"version":[259,319],"analysis,":[262],"had":[264],"coverage":[266],"area":[267],"2.0%,":[270],"with":[271,291],"deviation":[274,294],"5.6%.":[276],"One":[277],"nearly":[283],"accurate,":[285],"achieving":[286],"3.0%,":[290],"6.3%.":[296],"Further":[297],"statistical":[300],"equivalence":[301,307],"yielded":[302],"an":[303],"overall":[304],"zone":[305],"[":[309],"\u2212":[310],"7.0":[311],"%":[312,315],",":[313],"7.2":[314],"]":[316],"RSRD.":[321],"relative":[323],"promising,":[329],"given":[330],"their":[331],"potential":[332],"efficiently":[334],"generate":[335],"scene-wide":[336],"provide":[340],"first":[342],"known":[343],"level":[346]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2017-05-19T00:00:00"}