{"id":"https://openalex.org/W2069567669","doi":"https://doi.org/10.1117/12.2178400","title":"Geological applications of machine learning on hyperspectral remote sensing data","display_name":"Geological applications of machine learning on hyperspectral remote sensing data","publication_year":2015,"publication_date":"2015-02-27","ids":{"openalex":"https://openalex.org/W2069567669","doi":"https://doi.org/10.1117/12.2178400","mag":"2069567669"},"language":"en","primary_location":{"id":"doi:10.1117/12.2178400","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2178400","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","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/A5103534794","display_name":"Chi\u2010Hang Tse","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"C. H. Tse","raw_affiliation_strings":["The Univ. of Hong Kong (Hong Kong, China)","The Univ. of Hong Kong, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Univ. of Hong Kong (Hong Kong, China)","institution_ids":[]},{"raw_affiliation_string":"The Univ. of Hong Kong, Hong Kong, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086466377","display_name":"Yiliang Li","orcid":"https://orcid.org/0000-0002-2242-0941"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yi-liang Li","raw_affiliation_strings":["The Univ. of Hong Kong (Hong Kong, China)","The Univ. of Hong Kong, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Univ. of Hong Kong (Hong Kong, China)","institution_ids":[]},{"raw_affiliation_string":"The Univ. of Hong Kong, Hong Kong, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008832723","display_name":"Edmund Y. Lam","orcid":"https://orcid.org/0000-0001-6268-950X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Edmund Y. Lam","raw_affiliation_strings":["The Univ. of Hong Kong (Hong Kong, China)","The Univ. of Hong Kong, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Univ. of Hong Kong (Hong Kong, China)","institution_ids":[]},{"raw_affiliation_string":"The Univ. of Hong Kong, Hong Kong, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4452,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.76912578,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"9405","issue":null,"first_page":"940512","last_page":"940512"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9998999834060669,"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":0.9998999834060669,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9869999885559082,"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/T10770","display_name":"Soil Geostatistics and Mapping","score":0.9829999804496765,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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":0.963451087474823},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7962383031845093},{"id":"https://openalex.org/keywords/mars-exploration-program","display_name":"Mars Exploration Program","score":0.641228437423706},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5779397487640381},{"id":"https://openalex.org/keywords/imaging-spectrometer","display_name":"Imaging spectrometer","score":0.5151909589767456},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47888773679733276},{"id":"https://openalex.org/keywords/data-processing","display_name":"Data processing","score":0.47744184732437134},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4567824602127075},{"id":"https://openalex.org/keywords/data-cube","display_name":"Data cube","score":0.43697771430015564},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.4341227412223816},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.4294506311416626},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3385782241821289},{"id":"https://openalex.org/keywords/spectrometer","display_name":"Spectrometer","score":0.28870320320129395},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.1586749255657196},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.10257959365844727}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.963451087474823},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7962383031845093},{"id":"https://openalex.org/C83260615","wikidata":"https://www.wikidata.org/wiki/Q6773121","display_name":"Mars Exploration Program","level":2,"score":0.641228437423706},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5779397487640381},{"id":"https://openalex.org/C183852935","wikidata":"https://www.wikidata.org/wiki/Q6002848","display_name":"Imaging spectrometer","level":3,"score":0.5151909589767456},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47888773679733276},{"id":"https://openalex.org/C138827492","wikidata":"https://www.wikidata.org/wiki/Q6661985","display_name":"Data processing","level":2,"score":0.47744184732437134},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4567824602127075},{"id":"https://openalex.org/C78168278","wikidata":"https://www.wikidata.org/wiki/Q5227269","display_name":"Data cube","level":2,"score":0.43697771430015564},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.4341227412223816},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.4294506311416626},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3385782241821289},{"id":"https://openalex.org/C33390570","wikidata":"https://www.wikidata.org/wiki/Q188463","display_name":"Spectrometer","level":2,"score":0.28870320320129395},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.1586749255657196},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.10257959365844727},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1117/12.2178400","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2178400","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"},{"id":"pmh:oai:hub.hku.hk:10722/211420","is_oa":false,"landing_page_url":"http://hdl.handle.net/10722/211420","pdf_url":null,"source":{"id":"https://openalex.org/S4377196271","display_name":"The HKU Scholars Hub (University of Hong Kong)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I889458895","host_organization_name":"University of Hong Kong","host_organization_lineage":["https://openalex.org/I889458895"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference_Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1503398984","https://openalex.org/W1988315030","https://openalex.org/W2002222589","https://openalex.org/W2010353627","https://openalex.org/W2015091271","https://openalex.org/W2027442956","https://openalex.org/W2064150126","https://openalex.org/W2084338539","https://openalex.org/W2091397530","https://openalex.org/W2100921418","https://openalex.org/W2101234009","https://openalex.org/W2101661856","https://openalex.org/W2107616450","https://openalex.org/W2119936234","https://openalex.org/W2120147741","https://openalex.org/W2126230369","https://openalex.org/W2211548590","https://openalex.org/W3019286073","https://openalex.org/W3023114228","https://openalex.org/W4302076086","https://openalex.org/W6671350475","https://openalex.org/W6673181334","https://openalex.org/W6675354045","https://openalex.org/W6677676636","https://openalex.org/W6678478995"],"related_works":["https://openalex.org/W2746742660","https://openalex.org/W2082586825","https://openalex.org/W1982418987","https://openalex.org/W3112209948","https://openalex.org/W2889956472","https://openalex.org/W2561005839","https://openalex.org/W2138540356","https://openalex.org/W2119473622","https://openalex.org/W2474469778","https://openalex.org/W2000725643"],"abstract_inverted_index":{"The":[0,152,174],"CRISM":[1,128],"imaging":[2],"spectrometer":[3],"orbiting":[4],"Mars":[5,135],"has":[6],"been":[7,119],"producing":[8],"a":[9],"vast":[10],"amount":[11,186],"of":[12,23,42,53,67,111,115,182,187],"data":[13,25,63,154,166,189],"in":[14,20,46],"the":[15,21,62,65,75,85,159,169,184],"visible":[16],"to":[17,48,95,109,123,194],"infrared":[18],"wavelengths":[19],"form":[22],"hyperspectral":[24,129,188],"cubes.":[26],"These":[27],"data,":[28],"compared":[29,157],"with":[30,127,158],"those":[31],"obtained":[32],"from":[33,78,132,168],"previous":[34],"remote":[35],"sensing":[36],"techniques,":[37],"yield":[38],"an":[39,49,105],"unprecedented":[40],"level":[41,52],"detailed":[43,198],"spectral":[44,162],"resolution":[45],"additional":[47],"ever":[50],"increasing":[51],"spatial":[54],"information.":[55],"A":[56,113,137],"major":[57],"challenge":[58,86],"brought":[59],"about":[60],"by":[61,87,121],"is":[64,141,180],"burden":[66],"processing":[68,183],"and":[69,73,100,102,125,143,164,190],"interpreting":[70],"these":[71],"datasets":[72],"extract":[74],"relevant":[76],"information":[77],"it.":[79],"This":[80],"research":[81],"aims":[82],"at":[83],"approaching":[84],"exploring":[88],"machine":[89,138],"learning":[90,94,139,145],"methods":[91,146],"especially":[92],"unsupervised":[93,144],"achieve":[96],"cluster":[97],"density":[98],"estimation":[99],"classification,":[101],"ultimately":[103],"devising":[104],"efficient":[106],"means":[107],"leading":[108],"identification":[110],"minerals.":[112],"set":[114],"software":[116],"tools":[117],"have":[118],"constructed":[120],"Python":[122],"access":[124],"experiment":[126],"cubes":[130],"selected":[131],"two":[133],"specific":[134],"locations.":[136],"pipeline":[140],"proposed":[142],"were":[147],"implemented":[148],"onto":[149],"pre-processed":[150],"datasets.":[151],"resulting":[153],"clusters":[155],"are":[156],"published":[160],"ASTER":[161],"library":[163],"browse":[165],"products":[167],"Planetary":[170],"Data":[171],"System":[172],"(PDS).":[173],"result":[175],"demonstrated":[176],"that":[177],"this":[178],"approach":[179],"capable":[181],"huge":[185],"potentially":[191],"providing":[192],"guidance":[193],"scientists":[195],"for":[196],"more":[197],"studies.":[199]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}