{"id":"https://openalex.org/W3121188342","doi":"https://doi.org/10.1109/access.2021.3051196","title":"Big Data and Machine Learning With Hyperspectral Information in Agriculture","display_name":"Big Data and Machine Learning With Hyperspectral Information in Agriculture","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3121188342","doi":"https://doi.org/10.1109/access.2021.3051196","mag":"3121188342"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3051196","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3051196","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09328849.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09328849.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073635669","display_name":"Li-Minn Ang","orcid":"https://orcid.org/0000-0002-2402-7529"},"institutions":[{"id":"https://openalex.org/I174025329","display_name":"University of the Sunshine Coast","ror":"https://ror.org/016gb9e15","country_code":"AU","type":"education","lineage":["https://openalex.org/I174025329"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Kenneth Li-Minn Ang","raw_affiliation_strings":["School of Science and Engineering, University of the Sunshine Coast, Petrie, QLD, Australia"],"raw_orcid":"https://orcid.org/0000-0002-2402-7529","affiliations":[{"raw_affiliation_string":"School of Science and Engineering, University of the Sunshine Coast, Petrie, QLD, Australia","institution_ids":["https://openalex.org/I174025329"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085526572","display_name":"Jasmine Kah Phooi Seng","orcid":"https://orcid.org/0000-0002-8071-9044"},"institutions":[{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]},{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jasmine Kah Phooi Seng","raw_affiliation_strings":["School of Engineering and Information Technology, University of New South Wales, Canberra, ACT, Australia"],"raw_orcid":"https://orcid.org/0000-0002-8071-9044","affiliations":[{"raw_affiliation_string":"School of Engineering and Information Technology, University of New South Wales, Canberra, ACT, Australia","institution_ids":["https://openalex.org/I188329596","https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5073635669"],"corresponding_institution_ids":["https://openalex.org/I174025329"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":27.4394,"has_fulltext":true,"cited_by_count":192,"citation_normalized_percentile":{"value":0.99737098,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"9","issue":null,"first_page":"36699","last_page":"36718"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9807000160217285,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9804999828338623,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8485206365585327},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7172262072563171},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6890608668327332},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.6802636384963989},{"id":"https://openalex.org/keywords/precision-agriculture","display_name":"Precision agriculture","score":0.5873459577560425},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5519251823425293},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44772934913635254},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4376622438430786},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.403933048248291},{"id":"https://openalex.org/keywords/agriculture","display_name":"Agriculture","score":0.3476712107658386},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3426748514175415},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.27845755219459534},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.11634361743927002}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8485206365585327},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7172262072563171},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6890608668327332},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.6802636384963989},{"id":"https://openalex.org/C120217122","wikidata":"https://www.wikidata.org/wiki/Q740083","display_name":"Precision agriculture","level":3,"score":0.5873459577560425},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5519251823425293},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44772934913635254},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4376622438430786},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.403933048248291},{"id":"https://openalex.org/C118518473","wikidata":"https://www.wikidata.org/wiki/Q11451","display_name":"Agriculture","level":2,"score":0.3476712107658386},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3426748514175415},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27845755219459534},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.11634361743927002},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2021.3051196","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3051196","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09328849.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:559d635c306c4650bfa963e6a6f72bb0","is_oa":true,"landing_page_url":"https://doaj.org/article/559d635c306c4650bfa963e6a6f72bb0","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 36699-36718 (2021)","raw_type":"article"},{"id":"pmh:oai:eprints.qut.edu.au:214210","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306402607","display_name":"QUT ePrints (Queensland University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I160993911","host_organization_name":"Queensland University of Technology","host_organization_lineage":["https://openalex.org/I160993911"],"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":"IEEE Access","raw_type":"Contribution to Journal"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3051196","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3051196","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09328849.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","score":0.5299999713897705,"display_name":"Zero hunger"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3121188342.pdf","grobid_xml":"https://content.openalex.org/works/W3121188342.grobid-xml"},"referenced_works_count":85,"referenced_works":["https://openalex.org/W1923697677","https://openalex.org/W2014775865","https://openalex.org/W2025768430","https://openalex.org/W2032488374","https://openalex.org/W2039409148","https://openalex.org/W2082081125","https://openalex.org/W2095483845","https://openalex.org/W2104955141","https://openalex.org/W2113606819","https://openalex.org/W2136922672","https://openalex.org/W2151543530","https://openalex.org/W2163605009","https://openalex.org/W2292127689","https://openalex.org/W2381138071","https://openalex.org/W2412588858","https://openalex.org/W2587466508","https://openalex.org/W2591121333","https://openalex.org/W2593476953","https://openalex.org/W2607479420","https://openalex.org/W2614326984","https://openalex.org/W2727344147","https://openalex.org/W2734406139","https://openalex.org/W2738939205","https://openalex.org/W2742141965","https://openalex.org/W2761140038","https://openalex.org/W2765739551","https://openalex.org/W2766295554","https://openalex.org/W2772015038","https://openalex.org/W2775166040","https://openalex.org/W2790979755","https://openalex.org/W2793645503","https://openalex.org/W2794812819","https://openalex.org/W2809602495","https://openalex.org/W2829067510","https://openalex.org/W2885770726","https://openalex.org/W2886054370","https://openalex.org/W2889682228","https://openalex.org/W2891006103","https://openalex.org/W2894561647","https://openalex.org/W2895772881","https://openalex.org/W2897567604","https://openalex.org/W2899747753","https://openalex.org/W2901602754","https://openalex.org/W2901860299","https://openalex.org/W2901928690","https://openalex.org/W2908009020","https://openalex.org/W2909189847","https://openalex.org/W2913804921","https://openalex.org/W2919115771","https://openalex.org/W2921072760","https://openalex.org/W2922088567","https://openalex.org/W2946817927","https://openalex.org/W2947949571","https://openalex.org/W2951645895","https://openalex.org/W2953024850","https://openalex.org/W2954345346","https://openalex.org/W2963375395","https://openalex.org/W2964318286","https://openalex.org/W2966657623","https://openalex.org/W2969460967","https://openalex.org/W2971473896","https://openalex.org/W2979842301","https://openalex.org/W2982894653","https://openalex.org/W2983265666","https://openalex.org/W2985969959","https://openalex.org/W2987368014","https://openalex.org/W2988111912","https://openalex.org/W2988980823","https://openalex.org/W2995103261","https://openalex.org/W2998823444","https://openalex.org/W2999400086","https://openalex.org/W3000802654","https://openalex.org/W3001104841","https://openalex.org/W3002674187","https://openalex.org/W3004766864","https://openalex.org/W3006025044","https://openalex.org/W3006867319","https://openalex.org/W3011531216","https://openalex.org/W3106294914","https://openalex.org/W3115184262","https://openalex.org/W3145506661","https://openalex.org/W6640295612","https://openalex.org/W6675785006","https://openalex.org/W6676903177","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W4318664220","https://openalex.org/W2022304901","https://openalex.org/W2018850895","https://openalex.org/W2988577871","https://openalex.org/W1987483041","https://openalex.org/W3211006270","https://openalex.org/W4245858792","https://openalex.org/W2059191372"],"abstract_inverted_index":{"Hyperspectral":[0,69],"and":[1,6,18,26,35,58,66,102,118,160,172,176,187,192,212,223,248,253,267,281],"multispectral":[2,177,193,254],"information":[3,23,70,170,255,278],"processing":[4,171,256],"systems":[5],"technologies":[7,38],"have":[8,284,296],"demonstrated":[9],"its":[10],"usefulness":[11],"for":[12,181,190,226,251,292],"the":[13,30,59,80,114,123,164,205,221,232,261,298],"improvement":[14],"of":[15,45,61,83,100,108,143,207,234,263,301],"agricultural":[16,129],"productivity":[17],"practices":[19],"by":[20],"providing":[21],"useful":[22],"to":[24,122,137,146],"farmers":[25],"crop":[27,33,50,52,55],"managers":[28],"on":[29,166,241,287],"factors":[31],"affecting":[32],"status":[34],"growth.":[36],"These":[37],"are":[39],"widely":[40],"used":[41],"in":[42,87,128,153,195,229,276],"a":[43,88,97,140],"range":[44],"agriculture":[46,62,154,196,242,277,291],"applications":[47],"such":[48],"as":[49],"management,":[51],"yield":[53],"forecasting,":[54],"disease":[56],"detection,":[57],"monitoring":[60],"land":[63],"usage,":[64],"water,":[65],"soil":[67],"conditions.":[68],"sensing":[71,131],"can":[72],"acquire":[73],"several":[74],"hundred":[75],"spectral":[76,103,224],"bands":[77],"that":[78],"cover":[79],"electromagnetic":[81],"spectrum":[82],"an":[84],"observational":[85],"scene":[86],"single":[89],"acquisition.":[90],"The":[91,105,179,200,294],"resulting":[92],"hyperspectral":[93,106,175,191,252,288],"data":[94,115,125,194,228,282,289],"cube":[95],"contains":[96],"large":[98],"volume":[99,119],"spatial":[101,222],"information.":[104],"sequence":[107],"images":[109],"or":[110,168],"video":[111],"further":[112,203],"increases":[113],"generation":[116],"velocity":[117],"which":[120,217],"lead":[121],"Big":[124,156,183,227,244],"challenges":[126],"particularly":[127],"remote":[130],"applications.":[132],"This":[133],"paper":[134,201],"is":[135,197],"structured":[136],"first":[138],"give":[139],"comprehensive":[141],"review":[142,239],"representative":[144],"studies":[145],"provide":[147],"insights":[148],"into":[149,219],"significant":[150],"research":[151],"efforts":[152],"using":[155,208],"data,":[157,184,245],"machine":[158,185,210,246,265],"learning":[159,162,186,189,211,247,250,266],"deep":[161,188,249],"with":[163,174,243],"focus":[165],"frameworks":[167],"architectures,":[169],"analytics":[173,283],"data.":[178],"potential":[180,206,262],"utilizing":[182],"very":[198],"promising.":[199],"then":[202],"explores":[204],"ensemble":[209,264],"scalable":[213,268],"parallel":[214,269],"discriminant":[215,270],"analysis":[216,271],"takes":[218],"consideration":[220],"components":[225],"agriculture.":[230],"To":[231],"best":[233],"our":[235,302],"knowledge,":[236],"no":[237],"similar":[238],"study":[240],"has":[257,272],"been":[258,274,285],"reported.":[259],"Furthermore,":[260],"not":[273],"explored":[275],"processing.":[279],"Experiments":[280],"performed":[286],"from":[290],"validation.":[293],"results":[295],"shown":[297],"good":[299],"performance":[300],"approach.":[303]},"counts_by_year":[{"year":2026,"cited_by_count":14},{"year":2025,"cited_by_count":54},{"year":2024,"cited_by_count":45},{"year":2023,"cited_by_count":37},{"year":2022,"cited_by_count":32},{"year":2021,"cited_by_count":10}],"updated_date":"2026-05-28T09:10:13.091523","created_date":"2025-10-10T00:00:00"}