{"id":"https://openalex.org/W2063385051","doi":"https://doi.org/10.1109/msp.2013.2279894","title":"Manifold-Learning-Based Feature Extraction for Classification of Hyperspectral Data: A Review of Advances in Manifold Learning","display_name":"Manifold-Learning-Based Feature Extraction for Classification of Hyperspectral Data: A Review of Advances in Manifold Learning","publication_year":2013,"publication_date":"2013-12-09","ids":{"openalex":"https://openalex.org/W2063385051","doi":"https://doi.org/10.1109/msp.2013.2279894","mag":"2063385051"},"language":"en","primary_location":{"id":"doi:10.1109/msp.2013.2279894","is_oa":false,"landing_page_url":"https://doi.org/10.1109/msp.2013.2279894","pdf_url":null,"source":{"id":"https://openalex.org/S120977877","display_name":"IEEE Signal Processing Magazine","issn_l":"1053-5888","issn":["1053-5888","1558-0792"],"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 Signal Processing Magazine","raw_type":"journal-article"},"type":"review","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/A5083948807","display_name":"Dalton Lunga","orcid":"https://orcid.org/0000-0003-0054-1141"},"institutions":[{"id":"https://openalex.org/I2799946484","display_name":"Fulbright Commission","ror":"https://ror.org/037nbwt68","country_code":"GB","type":"nonprofit","lineage":["https://openalex.org/I2799946484"]},{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["GB","US"],"is_corresponding":true,"raw_author_name":"Dalton Lunga","raw_affiliation_strings":["Fulbright Scholar, Purdue University","[Fulbright Scholar, Purdue University]"],"affiliations":[{"raw_affiliation_string":"Fulbright Scholar, Purdue University","institution_ids":["https://openalex.org/I2799946484"]},{"raw_affiliation_string":"[Fulbright Scholar, Purdue University]","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037823063","display_name":"Saurabh Prasad","orcid":"https://orcid.org/0000-0003-3729-9360"},"institutions":[{"id":"https://openalex.org/I44461941","display_name":"University of Houston","ror":"https://ror.org/048sx0r50","country_code":"US","type":"education","lineage":["https://openalex.org/I44461941"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Saurabh Prasad","raw_affiliation_strings":["University of Houston","[Univ. of Houston]"],"affiliations":[{"raw_affiliation_string":"University of Houston","institution_ids":["https://openalex.org/I44461941"]},{"raw_affiliation_string":"[Univ. of Houston]","institution_ids":["https://openalex.org/I44461941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002083374","display_name":"Melba M. Crawford","orcid":null},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Melba M. Crawford","raw_affiliation_strings":["Ohio State University"],"affiliations":[{"raw_affiliation_string":"Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083478920","display_name":"Okan K. Ersoy","orcid":"https://orcid.org/0000-0002-7626-0584"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Okan Ersoy","raw_affiliation_strings":["University of California, Los Angeles","University of California\u2013Los Angeles"],"affiliations":[{"raw_affiliation_string":"University of California, Los Angeles","institution_ids":["https://openalex.org/I161318765"]},{"raw_affiliation_string":"University of California\u2013Los Angeles","institution_ids":["https://openalex.org/I161318765"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5083948807"],"corresponding_institution_ids":["https://openalex.org/I219193219","https://openalex.org/I2799946484"],"apc_list":null,"apc_paid":null,"fwci":34.3843,"has_fulltext":false,"cited_by_count":291,"citation_normalized_percentile":{"value":0.99776149,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"31","issue":"1","first_page":"55","last_page":"66"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":1.0,"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":1.0,"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":0.9891999959945679,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9799000024795532,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8456195592880249},{"id":"https://openalex.org/keywords/nonlinear-dimensionality-reduction","display_name":"Nonlinear dimensionality reduction","score":0.686032235622406},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6420465707778931},{"id":"https://openalex.org/keywords/manifold","display_name":"Manifold (fluid mechanics)","score":0.6125262975692749},{"id":"https://openalex.org/keywords/manifold-alignment","display_name":"Manifold alignment","score":0.5350766181945801},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4953097403049469},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.4794120490550995},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.449209064245224},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.44170358777046204},{"id":"https://openalex.org/keywords/external-data-representation","display_name":"External Data Representation","score":0.437145471572876},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40430599451065063},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.382456511259079},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.1241455078125},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10154050588607788}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8456195592880249},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.686032235622406},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6420465707778931},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.6125262975692749},{"id":"https://openalex.org/C153120616","wikidata":"https://www.wikidata.org/wiki/Q17068315","display_name":"Manifold alignment","level":4,"score":0.5350766181945801},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4953097403049469},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.4794120490550995},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.449209064245224},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.44170358777046204},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.437145471572876},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40430599451065063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.382456511259079},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.1241455078125},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10154050588607788},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"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/msp.2013.2279894","is_oa":false,"landing_page_url":"https://doi.org/10.1109/msp.2013.2279894","pdf_url":null,"source":{"id":"https://openalex.org/S120977877","display_name":"IEEE Signal Processing Magazine","issn_l":"1053-5888","issn":["1053-5888","1558-0792"],"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 Signal Processing Magazine","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W46086471","https://openalex.org/W84941271","https://openalex.org/W1964463693","https://openalex.org/W1988802668","https://openalex.org/W1996213136","https://openalex.org/W2001141328","https://openalex.org/W2001298023","https://openalex.org/W2003896345","https://openalex.org/W2005106632","https://openalex.org/W2011266013","https://openalex.org/W2019287283","https://openalex.org/W2029677437","https://openalex.org/W2038911891","https://openalex.org/W2040812261","https://openalex.org/W2042626896","https://openalex.org/W2053186076","https://openalex.org/W2054057905","https://openalex.org/W2057746226","https://openalex.org/W2059089906","https://openalex.org/W2067091528","https://openalex.org/W2077776048","https://openalex.org/W2081176632","https://openalex.org/W2097308346","https://openalex.org/W2097454346","https://openalex.org/W2100247253","https://openalex.org/W2103125780","https://openalex.org/W2107135467","https://openalex.org/W2107844881","https://openalex.org/W2108759471","https://openalex.org/W2109531142","https://openalex.org/W2111282613","https://openalex.org/W2118042967","https://openalex.org/W2118527389","https://openalex.org/W2121862141","https://openalex.org/W2130648700","https://openalex.org/W2131450755","https://openalex.org/W2133893370","https://openalex.org/W2134738108","https://openalex.org/W2140095548","https://openalex.org/W2144151128","https://openalex.org/W2151288205","https://openalex.org/W2151599207","https://openalex.org/W2154872931","https://openalex.org/W2155985040","https://openalex.org/W2156287497","https://openalex.org/W2157444450","https://openalex.org/W2157790742","https://openalex.org/W2161586104","https://openalex.org/W2162698522","https://openalex.org/W2164330327","https://openalex.org/W2171171329","https://openalex.org/W2187089797","https://openalex.org/W3104458014","https://openalex.org/W3148981562","https://openalex.org/W4246202668","https://openalex.org/W4285719527","https://openalex.org/W6601848957","https://openalex.org/W6641286290","https://openalex.org/W6660586002","https://openalex.org/W6670669403","https://openalex.org/W6682644385","https://openalex.org/W6683161245","https://openalex.org/W7034449035"],"related_works":["https://openalex.org/W2387045723","https://openalex.org/W117517268","https://openalex.org/W2573981081","https://openalex.org/W2397338926","https://openalex.org/W2085003924","https://openalex.org/W2384392227","https://openalex.org/W2380477800","https://openalex.org/W1976359930","https://openalex.org/W2142781195","https://openalex.org/W2888431323"],"abstract_inverted_index":{"Advances":[0],"in":[1,11,108,124,232,281,301,310],"hyperspectral":[2,200],"sensing":[3,187],"provide":[4,151],"new":[5,22],"capability":[6],"for":[7,24,62,74,184,191,197,258,268],"characterizing":[8],"spectral":[9],"signatures":[10],"a":[12,101,168,243,259],"wide":[13],"range":[14,169],"of":[15,64,88,142,170,199,255,304],"physical":[16,89],"and":[17,40,70,76,98,132,145,172,201,221,306,314,318],"biological":[18],"systems,":[19],"while":[20],"inspiring":[21],"methods":[23,80,157,309],"extracting":[25],"information":[26],"from":[27,100,289],"these":[28,79,256],"data.":[29,67,126,205],"HSI":[30],"data":[31,130,188,217,222,261],"often":[32,223],"lie":[33],"on":[34,54,139,286],"sparse,":[35],"nonlinear":[36],"manifolds":[37,234],"whose":[38,226],"geometric":[39],"topological":[41],"structures":[42,272],"can":[43],"be":[44,210,239],"exploited":[45],"via":[46],"manifold-learning":[47,156],"techniques.":[48],"In":[49],"this":[50],"article,":[51],"we":[52],"focused":[53,285],"demonstrating":[55],"the":[56,86,96,109,121,125,140,143,152,252,295],"opportunities":[57,71],"provided":[58],"by":[59],"manifold":[60,193,245,271,282],"learning":[61,128,194,283],"classification":[63],"remotely":[65,203],"sensed":[66,204],"However,":[68],"limitations":[69],"remain":[72],"both":[73],"research":[75,266],"applications.":[77],"Although":[78],"have":[81,173,275],"been":[82],"demonstrated":[83],"to":[84,209,274],"mitigate":[85],"impact":[87],"effects":[90],"that":[91,215,237,250],"affect":[92],"electromagnetic":[93],"energy":[94],"traversing":[95],"atmosphere":[97],"reflecting":[99],"target,":[102],"nonlinearities":[103],"are":[104,136,164,207,228],"not":[105,149],"always":[106,119],"exhibited":[107],"data,":[110,144],"particularly":[111,182],"at":[112],"lower":[113],"spatial":[114],"resolutions,":[115],"so":[116],"users":[117],"should":[118],"evaluate":[120],"inherent":[122],"nonlinearity":[123],"Manifold":[127],"is":[129,181,263,298],"driven,":[131],"as":[133],"such,":[134],"results":[135,163],"strongly":[137],"dependent":[138],"characteristics":[141,254],"one":[146],"method":[147],"will":[148],"consistently":[150],"best":[153],"results.":[154],"Nonlinear":[155],"require":[158],"parameter":[159],"tuning,":[160],"although":[161],"experimental":[162],"typically":[165],"stable":[166],"over":[167],"values,":[171],"higher":[174],"computational":[175],"overhead":[176],"than":[177],"linear":[178],"methods,":[179],"which":[180,269],"relevant":[183],"large-scale":[185],"remote":[186],"sets.":[189],"Opportunities":[190],"advancing":[192],"also":[195,299],"exist":[196],"analysis":[198],"multisource":[202],"Manifolds":[206],"assumed":[208],"inherently":[211],"smooth,":[212],"an":[213,264],"assumption":[214],"some":[216],"sets":[218],"may":[219],"violate,":[220],"contain":[224],"classes":[225],"spectra":[227],"distinctly":[229],"different,":[230],"resulting":[231],"multiple":[233],"or":[235],"submanifolds":[236,257],"cannot":[238],"readily":[240],"integrated":[241],"with":[242,316],"single":[244,290],"representation.":[246],"Developing":[247],"appropriate":[248],"characterizations":[249],"exploit":[251],"unique":[253],"particular":[260],"set":[262],"open":[265],"problem":[267],"hierarchical":[270],"appear":[273],"merit.":[276],"To":[277],"date,":[278],"most":[279],"work":[280],"has":[284],"feature":[287],"extraction":[288],"images,":[291],"assuming":[292],"stationarity":[293],"across":[294],"scene.":[296],"Research":[297],"needed":[300],"joint":[302],"exploitation":[303],"global":[305],"local":[307],"embedding":[308],"dynamic,":[311],"multitemporal":[312],"environments":[313],"integration":[315],"semisupervised":[317],"active":[319],"learning.":[320]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":27},{"year":2020,"cited_by_count":22},{"year":2019,"cited_by_count":36},{"year":2018,"cited_by_count":30},{"year":2017,"cited_by_count":32},{"year":2016,"cited_by_count":32},{"year":2015,"cited_by_count":23},{"year":2014,"cited_by_count":15}],"updated_date":"2026-03-26T15:22:09.906841","created_date":"2025-10-10T00:00:00"}