{"id":"https://openalex.org/W2015593378","doi":"https://doi.org/10.1109/igarss.2014.6947105","title":"Endmember classes determination using spectral similarity analysis for MODIS reflectance channels","display_name":"Endmember classes determination using spectral similarity analysis for MODIS reflectance channels","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W2015593378","doi":"https://doi.org/10.1109/igarss.2014.6947105","mag":"2015593378"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2014.6947105","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2014.6947105","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Geoscience and Remote Sensing Symposium","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/A5100847144","display_name":"Yuanliu Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuanliu Xu","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing, China","State Key Laboratory of Remote Sensing Science  Jointly Sponsored by the Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences and Beijing Normal University  Beijing 100101  China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]},{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science  Jointly Sponsored by the Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences and Beijing Normal University  Beijing 100101  China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018795881","display_name":"Jinyang Du","orcid":"https://orcid.org/0000-0002-8698-6696"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]},{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinyang Du","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing, China","State Key Laboratory of Remote Sensing Science  Jointly Sponsored by the Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences and Beijing Normal University  Beijing 100101  China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]},{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science  Jointly Sponsored by the Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences and Beijing Normal University  Beijing 100101  China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074231572","display_name":"Jiancheng Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiancheng Shi","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing, China","State Key Laboratory of Remote Sensing Science  Jointly Sponsored by the Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences and Beijing Normal University  Beijing 100101  China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]},{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science  Jointly Sponsored by the Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences and Beijing Normal University  Beijing 100101  China","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100847144"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I25254941","https://openalex.org/I4210166112"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.13350427,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"46","issue":null,"first_page":"2989","last_page":"2992"},"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/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9930999875068665,"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"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9804999828338623,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/endmember","display_name":"Endmember","score":0.9965572357177734},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.7223244905471802},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5968969464302063},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5216479897499084},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5198562741279602},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.49660807847976685},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4782106578350067},{"id":"https://openalex.org/keywords/spectral-signature","display_name":"Spectral signature","score":0.47395965456962585},{"id":"https://openalex.org/keywords/spectral-bands","display_name":"Spectral bands","score":0.47004762291908264},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4282046854496002},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.40585756301879883},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18496111035346985},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12579160928726196},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.10797402262687683}],"concepts":[{"id":"https://openalex.org/C58237817","wikidata":"https://www.wikidata.org/wiki/Q5376204","display_name":"Endmember","level":3,"score":0.9965572357177734},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.7223244905471802},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5968969464302063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5216479897499084},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5198562741279602},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.49660807847976685},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4782106578350067},{"id":"https://openalex.org/C176641082","wikidata":"https://www.wikidata.org/wiki/Q2446767","display_name":"Spectral signature","level":2,"score":0.47395965456962585},{"id":"https://openalex.org/C114700698","wikidata":"https://www.wikidata.org/wiki/Q2882278","display_name":"Spectral bands","level":2,"score":0.47004762291908264},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4282046854496002},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.40585756301879883},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18496111035346985},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12579160928726196},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.10797402262687683}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2014.6947105","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2014.6947105","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.47999998927116394,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1966798775","https://openalex.org/W1970243482","https://openalex.org/W1972293418","https://openalex.org/W2009539575","https://openalex.org/W2010319424","https://openalex.org/W2059377398","https://openalex.org/W2087964169","https://openalex.org/W2093628091","https://openalex.org/W2136635809","https://openalex.org/W2169549452","https://openalex.org/W2172063876"],"related_works":["https://openalex.org/W2037328426","https://openalex.org/W2791078257","https://openalex.org/W2099703033","https://openalex.org/W2798328034","https://openalex.org/W2728548987","https://openalex.org/W4399039556","https://openalex.org/W2890371384","https://openalex.org/W2127934268","https://openalex.org/W2120480074","https://openalex.org/W2039721451"],"abstract_inverted_index":{"Endmember":[0],"variability":[1],"is":[2],"one":[3],"of":[4,8,38,41,88,96],"reasons":[5],"causing":[6],"errors":[7],"model":[9],"fits":[10],"in":[11,19],"spectral":[12,34,39,61,69,73,86,93,99,102],"mixture":[13],"analysis":[14],"(SMA).":[15],"The":[16,36,92],"endmembers":[17],"used":[18,65,82],"endmember":[20,50,55,117],"matrix":[21],"should":[22],"be":[23],"higher":[24],"intra-class":[25],"similarity":[26,40,87],"and":[27,43,52,71,90,104,110],"lower":[28],"inter-class":[29,44],"similarity,":[30,70],"which":[31],"depends":[32],"on":[33,77],"wavelengths.":[35],"quantification":[37],"intra-":[42,89],"helps":[45],"to":[46,66,83,112],"determine":[47,113],"the":[48,54,68,78,85,114,116],"appropriate":[49,115],"classes":[51,118],"optimize":[53],"selection.":[56],"In":[57],"this":[58],"study,":[59],"five":[60],"matching":[62,79],"algorithms":[63,80],"were":[64,81,108],"quantify":[67],"three":[72],"class-matching":[74,94],"metrics":[75,95],"based":[76],"analyze":[84],"inter-class.":[91],"a":[97],"measured":[98],"library":[100],"(ENVI":[101],"libraries)":[103],"MODIS":[105,120],"image":[106],"spectra":[107],"quantified":[109],"assessed":[111],"for":[119],"reflectance":[121],"channels.":[122]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}