{"id":"https://openalex.org/W2992097261","doi":"https://doi.org/10.1109/whispers.2019.8921163","title":"Geochemical And Hyperspectral Data Fusion For Drill-Core Mineral Mapping","display_name":"Geochemical And Hyperspectral Data Fusion For Drill-Core Mineral Mapping","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2992097261","doi":"https://doi.org/10.1109/whispers.2019.8921163","mag":"2992097261"},"language":"en","primary_location":{"id":"doi:10.1109/whispers.2019.8921163","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2019.8921163","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5063936944","display_name":"Cecilia Contreras","orcid":"https://orcid.org/0000-0002-4758-6550"},"institutions":[{"id":"https://openalex.org/I2801798921","display_name":"Helmholtz-Zentrum Dresden-Rossendorf","ror":"https://ror.org/01zy2cs03","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921"]},{"id":"https://openalex.org/I4210148560","display_name":"Helmholtz Institute Freiberg for Resource Technology","ror":"https://ror.org/04kdb0j04","country_code":"DE","type":"government","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Cecilia Contreras","raw_affiliation_strings":["Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany","institution_ids":["https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055884274","display_name":"Mahdi Khodadadzadeh","orcid":"https://orcid.org/0000-0001-7899-738X"},"institutions":[{"id":"https://openalex.org/I2801798921","display_name":"Helmholtz-Zentrum Dresden-Rossendorf","ror":"https://ror.org/01zy2cs03","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921"]},{"id":"https://openalex.org/I4210148560","display_name":"Helmholtz Institute Freiberg for Resource Technology","ror":"https://ror.org/04kdb0j04","country_code":"DE","type":"government","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Mahdi Khodadadzadeh","raw_affiliation_strings":["Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany","institution_ids":["https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043971532","display_name":"Laura Tu\u015fa","orcid":null},"institutions":[{"id":"https://openalex.org/I2801798921","display_name":"Helmholtz-Zentrum Dresden-Rossendorf","ror":"https://ror.org/01zy2cs03","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921"]},{"id":"https://openalex.org/I4210148560","display_name":"Helmholtz Institute Freiberg for Resource Technology","ror":"https://ror.org/04kdb0j04","country_code":"DE","type":"government","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Laura Tusa","raw_affiliation_strings":["Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany","institution_ids":["https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005230043","display_name":"Christina Loidolt","orcid":null},"institutions":[{"id":"https://openalex.org/I2801798921","display_name":"Helmholtz-Zentrum Dresden-Rossendorf","ror":"https://ror.org/01zy2cs03","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921"]},{"id":"https://openalex.org/I4210148560","display_name":"Helmholtz Institute Freiberg for Resource Technology","ror":"https://ror.org/04kdb0j04","country_code":"DE","type":"government","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christina Loidolt","raw_affiliation_strings":["Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany","institution_ids":["https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080950597","display_name":"Raimon Tolosana\u2010Delgado","orcid":"https://orcid.org/0000-0001-9847-0462"},"institutions":[{"id":"https://openalex.org/I2801798921","display_name":"Helmholtz-Zentrum Dresden-Rossendorf","ror":"https://ror.org/01zy2cs03","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921"]},{"id":"https://openalex.org/I4210148560","display_name":"Helmholtz Institute Freiberg for Resource Technology","ror":"https://ror.org/04kdb0j04","country_code":"DE","type":"government","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Raimon Tolosana-Delgado","raw_affiliation_strings":["Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany","institution_ids":["https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067490750","display_name":"Richard Gloaguen","orcid":"https://orcid.org/0000-0002-4383-473X"},"institutions":[{"id":"https://openalex.org/I2801798921","display_name":"Helmholtz-Zentrum Dresden-Rossendorf","ror":"https://ror.org/01zy2cs03","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921"]},{"id":"https://openalex.org/I4210148560","display_name":"Helmholtz Institute Freiberg for Resource Technology","ror":"https://ror.org/04kdb0j04","country_code":"DE","type":"government","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Richard Gloaguen","raw_affiliation_strings":["Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany","institution_ids":["https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9997000098228455,"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/T12282","display_name":"Mineral Processing and Grinding","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9775000214576721,"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":0.9448853731155396},{"id":"https://openalex.org/keywords/vnir","display_name":"VNIR","score":0.6881000995635986},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6019585132598877},{"id":"https://openalex.org/keywords/drill","display_name":"Drill","score":0.5508661866188049},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.550523579120636},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5431011319160461},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.47467875480651855},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46484723687171936},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.44491827487945557},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4385956823825836},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.2783864736557007},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09869101643562317}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9448853731155396},{"id":"https://openalex.org/C5457282","wikidata":"https://www.wikidata.org/wiki/Q7907352","display_name":"VNIR","level":3,"score":0.6881000995635986},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6019585132598877},{"id":"https://openalex.org/C173736775","wikidata":"https://www.wikidata.org/wiki/Q58964","display_name":"Drill","level":2,"score":0.5508661866188049},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.550523579120636},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5431011319160461},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.47467875480651855},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46484723687171936},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.44491827487945557},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4385956823825836},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.2783864736557007},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09869101643562317},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/whispers.2019.8921163","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2019.8921163","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.47999998927116394,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1980849679","https://openalex.org/W1983865151","https://openalex.org/W2016268312","https://openalex.org/W2082920669","https://openalex.org/W2765263221","https://openalex.org/W2901128450","https://openalex.org/W2911964244","https://openalex.org/W2953949196","https://openalex.org/W6756891151"],"related_works":["https://openalex.org/W2002304416","https://openalex.org/W1928576716","https://openalex.org/W2243385566","https://openalex.org/W2767899554","https://openalex.org/W4312435297","https://openalex.org/W2972669861","https://openalex.org/W1986821285","https://openalex.org/W3185961193","https://openalex.org/W2112656425","https://openalex.org/W2985667127"],"abstract_inverted_index":{"Hyperspectral":[0],"imaging":[1],"is":[2,103,149],"increasingly":[3],"being":[4],"used":[5,41],"in":[6,33,79,165,187],"the":[7,11,18,69,138,143,180,189],"mining":[8],"industry":[9],"for":[10,76,92,116],"investigation":[12],"of":[13,25,71,100,140,161,193],"drill-core":[14,44,80],"samples.":[15],"It":[16],"provides":[17,183],"means":[19],"to":[20,42,88,104,155],"analyze":[21],"a":[22,34,94,111,117],"large":[23],"amount":[24],"cores":[26],"considerably":[27],"faster":[28],"than":[29],"traditional":[30,144],"methods":[31],"and":[32,36,53,62,107,131,191],"non-invasive":[35],"non-destructive":[37],"manner.":[38],"Traditional":[39],"approaches":[40],"analyse":[43],"hyperspectral":[45,81,108,135,166],"data":[46,91,109,167],"are":[47,60,171,196],"mainly":[48],"based":[49],"on":[50],"visual":[51],"observations":[52],"need":[54],"significant":[55,163],"human":[56],"interactions.":[57],"Thus,":[58],"they":[59],"time-consuming":[61],"subjective.":[63],"In":[64],"this":[65,84,101],"paper,":[66],"we":[67,86,123,153],"explore":[68],"use":[70,89,156],"supervised":[72],"machine":[73,112],"learning":[74,113],"techniques":[75],"mineral":[77,120,185],"mapping":[78,121],"data.":[82,136],"For":[83,137,151],"purpose,":[85],"suggest":[87],"geochemical":[90,106],"generating":[93],"training":[95,173],"set.":[96],"The":[97],"main":[98],"contribution":[99],"work":[102],"fuse":[105],"within":[110],"framework.":[114],"Moreover,":[115],"more":[118],"complete":[119],"task,":[122],"integrate":[124],"visible":[125],"near-infrared":[126],"(VNIR),":[127],"short-wave":[128],"infrared":[129,133],"(SWIR)":[130],"long-wave":[132],"(LWIR)":[134],"extraction":[139],"input":[141],"features,":[142],"Principal":[145],"Component":[146],"Analysis":[147],"(PCA)":[148],"implemented.":[150],"classification,":[152],"propose":[154],"Random":[157],"Forest":[158],"(RF)":[159],"because":[160],"its":[162],"performance":[164],"classification":[168],"when":[169],"there":[170],"few":[172],"samples":[174],"available.":[175],"Experimental":[176],"results":[177],"show":[178],"that":[179],"proposed":[181],"method":[182],"comprehensive":[184],"maps":[186],"which":[188],"distribution":[190],"patterns":[192],"different":[194],"minerals":[195],"well":[197],"characterised.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}