{"id":"https://openalex.org/W4403336786","doi":"https://doi.org/10.3390/rs16203778","title":"Predicting Rock Hardness and Abrasivity Using Hyperspectral Imaging Data and Random Forest Regressor Model","display_name":"Predicting Rock Hardness and Abrasivity Using Hyperspectral Imaging Data and Random Forest Regressor Model","publication_year":2024,"publication_date":"2024-10-11","ids":{"openalex":"https://openalex.org/W4403336786","doi":"https://doi.org/10.3390/rs16203778"},"language":"en","primary_location":{"id":"doi:10.3390/rs16203778","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16203778","pdf_url":null,"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://doi.org/10.3390/rs16203778","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068280110","display_name":"Saleh Ghadernejad","orcid":"https://orcid.org/0000-0001-5262-7188"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Saleh Ghadernejad","raw_affiliation_strings":["Department of Civil and Mineral Engineering, The University of Toronto, Toronto, ON M5S 1A4, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Civil and Mineral Engineering, The University of Toronto, Toronto, ON M5S 1A4, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065939074","display_name":"Kamran Esmaeili","orcid":"https://orcid.org/0000-0003-3949-5648"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Kamran Esmaeili","raw_affiliation_strings":["Department of Civil and Mineral Engineering, The University of Toronto, Toronto, ON M5S 1A4, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Civil and Mineral Engineering, The University of Toronto, Toronto, ON M5S 1A4, Canada","institution_ids":["https://openalex.org/I185261750"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5065939074"],"corresponding_institution_ids":["https://openalex.org/I185261750"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.267,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.77346154,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"16","issue":"20","first_page":"3778","last_page":"3778"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12282","display_name":"Mineral Processing and Grinding","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T12282","display_name":"Mineral Processing and Grinding","score":0.9998000264167786,"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/T11837","display_name":"Iron and Steelmaking Processes","score":0.9902999997138977,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9858999848365784,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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":0.6734832525253296},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5143653154373169},{"id":"https://openalex.org/keywords/soil-science","display_name":"Soil science","score":0.46149903535842896},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.44161564111709595},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.38982415199279785},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.36344853043556213},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.14779630303382874},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.08807581663131714}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6734832525253296},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5143653154373169},{"id":"https://openalex.org/C159390177","wikidata":"https://www.wikidata.org/wiki/Q9161265","display_name":"Soil science","level":1,"score":0.46149903535842896},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.44161564111709595},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.38982415199279785},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.36344853043556213},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.14779630303382874},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.08807581663131714}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs16203778","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16203778","pdf_url":null,"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:b4592204873c454b95859aa3a4e5214a","is_oa":true,"landing_page_url":"https://doaj.org/article/b4592204873c454b95859aa3a4e5214a","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 16, Iss 20, p 3778 (2024)","raw_type":"article"},{"id":"pmh:oai:utoronto.scholaris.ca:1807/139825","is_oa":true,"landing_page_url":"http://hdl.handle.net/1807/139825","pdf_url":null,"source":{"id":"https://openalex.org/S7407055458","display_name":"TSpace","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":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":{"id":"doi:10.3390/rs16203778","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16203778","pdf_url":null,"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":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.7400000095367432}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W1978256505","https://openalex.org/W1989403019","https://openalex.org/W2028741642","https://openalex.org/W2047430897","https://openalex.org/W2051011292","https://openalex.org/W2058596513","https://openalex.org/W2067732615","https://openalex.org/W2097998348","https://openalex.org/W2099115613","https://openalex.org/W2129033354","https://openalex.org/W2147349042","https://openalex.org/W2151238122","https://openalex.org/W2167598218","https://openalex.org/W2277912244","https://openalex.org/W2316331446","https://openalex.org/W2323187287","https://openalex.org/W2527344479","https://openalex.org/W2549511516","https://openalex.org/W2618851150","https://openalex.org/W2793081731","https://openalex.org/W2797779281","https://openalex.org/W2883324463","https://openalex.org/W2911964244","https://openalex.org/W2912688419","https://openalex.org/W2945071234","https://openalex.org/W2955059592","https://openalex.org/W2967663220","https://openalex.org/W2968748626","https://openalex.org/W2971403197","https://openalex.org/W2995559220","https://openalex.org/W3009894809","https://openalex.org/W3039164821","https://openalex.org/W3085033577","https://openalex.org/W3122990674","https://openalex.org/W3155731460","https://openalex.org/W3198884202","https://openalex.org/W3199255357","https://openalex.org/W3201102006","https://openalex.org/W3207817009","https://openalex.org/W3216471280","https://openalex.org/W4214941347","https://openalex.org/W4220759041","https://openalex.org/W4220831108","https://openalex.org/W4252434178","https://openalex.org/W4255909838","https://openalex.org/W4281629158","https://openalex.org/W4281648222","https://openalex.org/W4307814254","https://openalex.org/W4310444651","https://openalex.org/W4311532677","https://openalex.org/W4313430785","https://openalex.org/W4384007548","https://openalex.org/W4387763012","https://openalex.org/W4390268639","https://openalex.org/W4399997159","https://openalex.org/W4401218819","https://openalex.org/W4402885423","https://openalex.org/W6674385629","https://openalex.org/W6694834807","https://openalex.org/W6766576792","https://openalex.org/W6794172776"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2070598848","https://openalex.org/W2385371209","https://openalex.org/W4250051149","https://openalex.org/W2083270190","https://openalex.org/W1991437568"],"abstract_inverted_index":{"This":[0],"study":[1],"aimed":[2],"to":[3,119],"develop":[4,120],"predictive":[5,121],"models":[6,122,136],"for":[7,102,123,178],"rock":[8,33,40,124,139,182],"hardness":[9,53,65,125,140,183],"and":[10,44,47,54,67,82,85,95,126,141,151,172,180,184],"abrasivity":[11,55,69,127,142,185],"based":[12,91],"on":[13,92],"hyperspectral":[14,170],"imaging":[15],"data,":[16],"providing":[17],"valuable":[18],"information":[19],"without":[20],"interrupting":[21],"the":[22,57,96,111,134,155,162],"mining":[23,188],"processes.":[24,189],"The":[25,52,74,129,165],"data":[26,75,145,171],"collection":[27],"stage":[28],"first":[29],"involved":[30,77],"scanning":[31],"159":[32],"samples":[34,58],"collected":[35],"from":[36],"6":[37],"different":[38],"blasted":[39],"piles":[41],"using":[42],"visible":[43],"near-infrared":[45],"(VNIR)":[46],"short-wave":[48],"infrared":[49],"(SWIR)":[50],"sensors.":[51],"of":[56,143,149],"were":[59],"then":[60],"determined":[61],"through":[62],"Leeb":[63],"rebound":[64],"(LRH)":[66],"Cerchar":[68],"index":[70],"(CAI)":[71],"tests,":[72],"respectively.":[73],"preprocessing":[76],"radiometric":[78],"correction,":[79],"background":[80],"removal,":[81],"staking":[83],"VNIR":[84],"SWIR":[86,163],"images.":[87],"An":[88],"integrated":[89,169],"approach":[90],"K-means":[93],"clustering":[94],"band":[97],"ratio":[98],"concept":[99],"was":[100,117],"employed":[101,118],"feature":[103],"extraction,":[104],"resulting":[105],"in":[106],"28":[107],"band-ratio-based":[108],"features.":[109],"Afterward,":[110],"random":[112],"forest":[113],"regressor":[114],"(RFR)":[115],"algorithm":[116],"separately.":[128],"performance":[130],"assessment":[131],"showed":[132],"that":[133,168],"developed":[135],"can":[137],"estimate":[138],"unseen":[144],"with":[146,154],"R2":[147],"scores":[148],"0.74":[150],"0.79,":[152],"respectively,":[153],"most":[156],"influential":[157],"features":[158],"located":[159],"mainly":[160],"within":[161],"region.":[164],"results":[166],"indicate":[167],"RFR":[173],"technique":[174],"have":[175],"strong":[176],"potential":[177],"practical":[179],"efficient":[181],"characterization":[186],"during":[187]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}
