{"id":"https://openalex.org/W4212838026","doi":"https://doi.org/10.3390/rs14041042","title":"A Novel Method for Hyperspectral Mineral Mapping Based on Clustering-Matching and Nonnegative Matrix Factorization","display_name":"A Novel Method for Hyperspectral Mineral Mapping Based on Clustering-Matching and Nonnegative Matrix Factorization","publication_year":2022,"publication_date":"2022-02-21","ids":{"openalex":"https://openalex.org/W4212838026","doi":"https://doi.org/10.3390/rs14041042"},"language":"en","primary_location":{"id":"doi:10.3390/rs14041042","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14041042","pdf_url":"https://www.mdpi.com/2072-4292/14/4/1042/pdf?version=1645525055","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/2072-4292/14/4/1042/pdf?version=1645525055","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016302020","display_name":"Zhongliang Ren","orcid":"https://orcid.org/0000-0003-3442-2634"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongliang Ren","raw_affiliation_strings":["College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China"],"affiliations":[{"raw_affiliation_string":"College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075638106","display_name":"Qiuping Zhai","orcid":null},"institutions":[{"id":"https://openalex.org/I15823474","display_name":"Linyi University","ror":"https://ror.org/01knv0402","country_code":"CN","type":"education","lineage":["https://openalex.org/I15823474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiuping Zhai","raw_affiliation_strings":["Shandong Provincial Key Laboratory of Water and Soil Conservation and Environmental Protection, School of Resource and Environmental Sciences, Linyi University, Linyi 276000, China"],"affiliations":[{"raw_affiliation_string":"Shandong Provincial Key Laboratory of Water and Soil Conservation and Environmental Protection, School of Resource and Environmental Sciences, Linyi University, Linyi 276000, China","institution_ids":["https://openalex.org/I15823474"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018668652","display_name":"Lin Sun","orcid":"https://orcid.org/0000-0001-9607-9232"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lin Sun","raw_affiliation_strings":["College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China"],"affiliations":[{"raw_affiliation_string":"College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China","institution_ids":["https://openalex.org/I80143920"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5018668652"],"corresponding_institution_ids":["https://openalex.org/I80143920"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.9809,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":{"value":0.87249545,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"14","issue":"4","first_page":"1042","last_page":"1042"},"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":0.9995999932289124,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9620000123977661,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8645056486129761},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.817999541759491},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.728699266910553},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6356746554374695},{"id":"https://openalex.org/keywords/endmember","display_name":"Endmember","score":0.6331812143325806},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.590591311454773},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5529668927192688},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5356041789054871},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.47618308663368225},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.43082401156425476},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.37777087092399597},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.35622310638427734},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35180217027664185},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.18610763549804688},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.17365577816963196},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10365217924118042},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07652860879898071}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8645056486129761},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.817999541759491},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.728699266910553},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6356746554374695},{"id":"https://openalex.org/C58237817","wikidata":"https://www.wikidata.org/wiki/Q5376204","display_name":"Endmember","level":3,"score":0.6331812143325806},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.590591311454773},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5529668927192688},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5356041789054871},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.47618308663368225},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.43082401156425476},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.37777087092399597},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.35622310638427734},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35180217027664185},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.18610763549804688},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.17365577816963196},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10365217924118042},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07652860879898071},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs14041042","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14041042","pdf_url":"https://www.mdpi.com/2072-4292/14/4/1042/pdf?version=1645525055","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:doaj.org/article:d2d2995f720e4c9295db26a6ae06a09b","is_oa":true,"landing_page_url":"https://doaj.org/article/d2d2995f720e4c9295db26a6ae06a09b","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 14, Iss 4, p 1042 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/4/1042/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14041042","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 14; Issue 4; Pages: 1042","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs14041042","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14041042","pdf_url":"https://www.mdpi.com/2072-4292/14/4/1042/pdf?version=1645525055","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":[{"score":0.49000000953674316,"display_name":"No poverty","id":"https://metadata.un.org/sdg/1"}],"awards":[{"id":"https://openalex.org/G7622341797","display_name":null,"funder_award_id":"ZR2020QD018","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"}],"funders":[{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4212838026.pdf"},"referenced_works_count":69,"referenced_works":["https://openalex.org/W1143553410","https://openalex.org/W1902027874","https://openalex.org/W1967412740","https://openalex.org/W1970039276","https://openalex.org/W1973975030","https://openalex.org/W1975844073","https://openalex.org/W1980317569","https://openalex.org/W1991023366","https://openalex.org/W2002519017","https://openalex.org/W2003780581","https://openalex.org/W2012749606","https://openalex.org/W2015583498","https://openalex.org/W2021455849","https://openalex.org/W2021527468","https://openalex.org/W2022470997","https://openalex.org/W2027878671","https://openalex.org/W2031491038","https://openalex.org/W2036769818","https://openalex.org/W2044193427","https://openalex.org/W2055537285","https://openalex.org/W2065548527","https://openalex.org/W2065991620","https://openalex.org/W2072275630","https://openalex.org/W2075336646","https://openalex.org/W2079381224","https://openalex.org/W2082858890","https://openalex.org/W2093628091","https://openalex.org/W2094626526","https://openalex.org/W2098057602","https://openalex.org/W2107552587","https://openalex.org/W2110764636","https://openalex.org/W2116699851","https://openalex.org/W2124890708","https://openalex.org/W2126320505","https://openalex.org/W2127229869","https://openalex.org/W2127495569","https://openalex.org/W2134328014","https://openalex.org/W2138973222","https://openalex.org/W2140405352","https://openalex.org/W2152404310","https://openalex.org/W2153889834","https://openalex.org/W2155074104","https://openalex.org/W2171098181","https://openalex.org/W2172063876","https://openalex.org/W2313808482","https://openalex.org/W2494395359","https://openalex.org/W2536669487","https://openalex.org/W2616976651","https://openalex.org/W2796055446","https://openalex.org/W2799870441","https://openalex.org/W2805267817","https://openalex.org/W2823336313","https://openalex.org/W2888119354","https://openalex.org/W2945254408","https://openalex.org/W2963947695","https://openalex.org/W2983354389","https://openalex.org/W3012012829","https://openalex.org/W3013803529","https://openalex.org/W3033351122","https://openalex.org/W3033900788","https://openalex.org/W3117817073","https://openalex.org/W3127490846","https://openalex.org/W3166936699","https://openalex.org/W6651292271","https://openalex.org/W6655771051","https://openalex.org/W6678410025","https://openalex.org/W6750192685","https://openalex.org/W6762633277","https://openalex.org/W7036815335"],"related_works":["https://openalex.org/W2089298795","https://openalex.org/W2773002387","https://openalex.org/W1980988957","https://openalex.org/W2766484909","https://openalex.org/W2101428145","https://openalex.org/W2802800261","https://openalex.org/W1992367803","https://openalex.org/W2163867257","https://openalex.org/W2338894643","https://openalex.org/W2898368675"],"abstract_inverted_index":{"The":[0,265],"emergence":[1],"of":[2,28,42,47,76,111,156,177,187,206,216,226,236,282],"hyperspectral":[3,16,175],"imagery":[4],"paved":[5],"a":[6,14,74,91,144,160,273],"new":[7,274],"way":[8],"for":[9,33,99,121,276],"rapid":[10,278],"mineral":[11,166],"mapping.":[12],"As":[13],"classical":[15],"classification":[17],"method,":[18,72],"spectral":[19,131,135,139,161],"matching":[20,55,128,146,263],"(SM)":[21],"can":[22,211],"automatically":[23],"map":[24],"the":[25,31,40,44,108,112,153,165,173,183,217,221,237,245,277],"spatial":[26],"distribution":[27],"minerals":[29,283],"without":[30],"need":[32],"selecting":[34],"training":[35],"samples.":[36],"However,":[37],"due":[38],"to":[39,59,106,151,163],"influence":[41],"noise,":[43],"mapping":[45,71,167,218,222,251,266],"accuracy":[46,223],"SM":[48,79],"is":[49,57,86,104],"usually":[50],"poor,":[51],"and":[52,78,88,93,115,123,143,194,201,209,224,231,256,279,284],"its":[53],"per-pixel":[54],"method":[56,97,147,267],"inefficient":[58],"some":[60],"extent.":[61],"To":[62],"solve":[63],"these":[64],"problems,":[65],"we":[66],"propose":[67],"an":[68],"unsupervised":[69],"clustering-matching":[70],"using":[73],"combination":[75],"k-means":[77,103],"(KSM).":[80],"First,":[81],"nonnegative":[82],"matrix":[83],"factorization":[84],"(NMF)":[85],"used":[87,120,150,239],"combined":[89,145],"with":[90,159,261],"simple":[92],"effective":[94],"NMF":[95,240],"initialization":[96,241],"(SMNMF)":[98],"feature":[100],"extraction.":[101],"Then,":[102],"implemented":[105],"get":[107],"cluster":[109,154],"centers":[110,155],"extracted":[113],"features":[114],"band":[116,157],"depth,":[117],"which":[118],"are":[119,149,196,228],"clustering":[122],"matching,":[124],"respectively.":[125],"Finally,":[126],"dimensionless":[127],"methods,":[129],"including":[130],"angle":[132,137,141],"mapper":[133],"(SAM),":[134],"correlation":[136],"(SCA),":[138],"gradient":[140],"(SGA),":[142],"(SCGA)":[148],"match":[152],"depth":[158],"library":[162],"obtain":[164],"results.":[168],"A":[169],"case":[170],"study":[171,271],"on":[172,190],"airborne":[174],"image":[176],"Cuprite,":[178],"Nevada,":[179],"USA,":[180],"demonstrated":[181],"that":[182],"average":[184],"overall":[185],"accuracies":[186],"KSM":[188,210],"based":[189],"SAM,":[191],"SCA,":[192],"SGA,":[193],"SCGA":[195,247],"approximately":[197],"22%,":[198,199],"35%,":[200],"33%":[202],"higher":[203,233],"than":[204,214,234],"those":[205,235],"SM,":[207],"respectively,":[208],"save":[212],"more":[213],"95%":[215],"time.":[219],"Moreover,":[220],"efficiency":[225],"SMNMF":[227],"about":[229],"15%":[230],"38%":[232],"widely":[238],"method.":[242],"In":[243],"addition,":[244],"proposed":[246,268],"could":[248],"achieve":[249],"promising":[250],"results":[252],"at":[253],"both":[254],"high":[255],"low":[257],"signal-to-noise":[258],"ratios":[259],"compared":[260],"other":[262,285],"methods.":[264],"in":[269],"this":[270],"provides":[272],"solution":[275],"autonomous":[280],"identification":[281],"fine":[286],"objects.":[287]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3}],"updated_date":"2026-01-15T23:16:33.117629","created_date":"2022-02-24T00:00:00"}
