{"id":"https://openalex.org/W1977991670","doi":"https://doi.org/10.1109/fskd.2010.5569721","title":"Multifractal based hyperion hyperspectral data mining","display_name":"Multifractal based hyperion hyperspectral data mining","publication_year":2010,"publication_date":"2010-08-01","ids":{"openalex":"https://openalex.org/W1977991670","doi":"https://doi.org/10.1109/fskd.2010.5569721","mag":"1977991670"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2010.5569721","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2010.5569721","pdf_url":null,"source":{"id":"https://openalex.org/S4363608217","display_name":"2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery","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/A5048975428","display_name":"Ziyong Zhou","orcid":"https://orcid.org/0000-0002-4198-6529"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ziyong Zhou","raw_affiliation_strings":["State Key Laboratory of Petroleum Resource and Prospecting, China University of Petroleum, Beijing, China, 102249"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Petroleum Resource and Prospecting, China University of Petroleum, Beijing, China, 102249","institution_ids":["https://openalex.org/I204553293"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5048975428"],"corresponding_institution_ids":["https://openalex.org/I204553293"],"apc_list":null,"apc_paid":null,"fwci":9.0506,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.96164092,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2109","last_page":"2113"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9807999730110168,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9325799942016602},{"id":"https://openalex.org/keywords/fractal","display_name":"Fractal","score":0.856311559677124},{"id":"https://openalex.org/keywords/multifractal-system","display_name":"Multifractal system","score":0.8403760194778442},{"id":"https://openalex.org/keywords/fractal-dimension","display_name":"Fractal dimension","score":0.7565993070602417},{"id":"https://openalex.org/keywords/spectral-signature","display_name":"Spectral signature","score":0.6372162103652954},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5727440118789673},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.562961995601654},{"id":"https://openalex.org/keywords/fractal-analysis","display_name":"Fractal analysis","score":0.5325077772140503},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5148507952690125},{"id":"https://openalex.org/keywords/signature","display_name":"Signature (topology)","score":0.5146813988685608},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.5083999037742615},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4783180058002472},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.46609583497047424},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4162450432777405},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4155437648296356},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37886321544647217},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3203203082084656},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.22289976477622986},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.18099147081375122},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.11636391282081604},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.08504152297973633}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9325799942016602},{"id":"https://openalex.org/C40636538","wikidata":"https://www.wikidata.org/wiki/Q81392","display_name":"Fractal","level":2,"score":0.856311559677124},{"id":"https://openalex.org/C133905733","wikidata":"https://www.wikidata.org/wiki/Q2629238","display_name":"Multifractal system","level":3,"score":0.8403760194778442},{"id":"https://openalex.org/C26546657","wikidata":"https://www.wikidata.org/wiki/Q1412452","display_name":"Fractal dimension","level":3,"score":0.7565993070602417},{"id":"https://openalex.org/C176641082","wikidata":"https://www.wikidata.org/wiki/Q2446767","display_name":"Spectral signature","level":2,"score":0.6372162103652954},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5727440118789673},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.562961995601654},{"id":"https://openalex.org/C162494671","wikidata":"https://www.wikidata.org/wiki/Q2845227","display_name":"Fractal analysis","level":4,"score":0.5325077772140503},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5148507952690125},{"id":"https://openalex.org/C2779696439","wikidata":"https://www.wikidata.org/wiki/Q7512811","display_name":"Signature (topology)","level":2,"score":0.5146813988685608},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.5083999037742615},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4783180058002472},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.46609583497047424},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4162450432777405},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4155437648296356},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37886321544647217},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3203203082084656},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.22289976477622986},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.18099147081375122},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.11636391282081604},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.08504152297973633},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fskd.2010.5569721","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2010.5569721","pdf_url":null,"source":{"id":"https://openalex.org/S4363608217","display_name":"2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W92056230","https://openalex.org/W1978189768","https://openalex.org/W1980690398","https://openalex.org/W1993650430","https://openalex.org/W2003721175","https://openalex.org/W2018038558","https://openalex.org/W2047577845","https://openalex.org/W2053457829","https://openalex.org/W2126727010","https://openalex.org/W2158270878","https://openalex.org/W6603768433"],"related_works":["https://openalex.org/W282492026","https://openalex.org/W4212788579","https://openalex.org/W1868966746","https://openalex.org/W2605357193","https://openalex.org/W2169163271","https://openalex.org/W2116069637","https://openalex.org/W1965262908","https://openalex.org/W2011014349","https://openalex.org/W1986922629","https://openalex.org/W2125813753"],"abstract_inverted_index":{"Traditional":[0],"methods":[1],"effectively":[2],"used":[3],"for":[4,94],"processing":[5],"multispectral":[6],"data":[7,21,35],"is":[8,30,47],"usually":[9],"limited":[10],"to":[11,32,49,74,87,139],"deal":[12],"with":[13],"hyperspectral":[14,34,141],"images,":[15],"which":[16],"are":[17],"characterized":[18],"by":[19,36],"massive":[20],"and":[22,44,78,112,122],"higher":[23],"spectral":[24,42,57,73],"resolution.":[25],"In":[26],"this":[27],"paper,":[28],"multifractal":[29,131],"introduced":[31],"mining":[33,140],"analyzing":[37],"the":[38,66,76,79,95,104,108,113,130],"holistic":[39],"feature":[40,123],"of":[41,55,68,115],"curve,":[43],"blanket":[45],"method":[46,133],"adopted":[48],"compute":[50],"fractal":[51,69,81,92,109,119],"dimension":[52],"(fractal":[53],"signature)":[54],"each":[56],"curve":[58],"within":[59],"Hyperion":[60,96],"image.":[61],"The":[62,98,125],"experimental":[63,99],"result":[64,100,127],"shows":[65],"advantage":[67],"signature":[70,82,93,110,120],"over":[71],"original":[72],"identify":[75],"objects,":[77],"down":[80],"may":[83,134],"be":[84,135],"more":[85],"effective":[86],"discriminate":[88],"objects":[89],"than":[90],"up":[91],"data.":[97,142],"also":[101],"indicates":[102],"that":[103,129],"initial":[105],"scale":[106],"affects":[107,117],"value,":[111],"number":[114],"bands":[116],"both":[118],"value":[121],"scale.":[124],"primary":[126],"implies":[128],"based":[132],"a":[136],"feasible":[137],"approach":[138]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2013,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
