{"id":"https://openalex.org/W7135124208","doi":"https://doi.org/10.31449/inf.v50i9.11461","title":"Spectral\u2013Spatial Land Cover Mapping Using a Deep 3D Convolutional Neural Network on Hyperspectral Data","display_name":"Spectral\u2013Spatial Land Cover Mapping Using a Deep 3D Convolutional Neural Network on Hyperspectral Data","publication_year":2026,"publication_date":"2026-03-12","ids":{"openalex":"https://openalex.org/W7135124208","doi":"https://doi.org/10.31449/inf.v50i9.11461"},"language":null,"primary_location":{"id":"doi:10.31449/inf.v50i9.11461","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v50i9.11461","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/11461/6561","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.informatica.si/index.php/informatica/article/download/11461/6561","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114358418","display_name":"Assia Nouna","orcid":null},"institutions":[{"id":"https://openalex.org/I4210145365","display_name":"Universit\u00e9 Hassan 1er","ror":"https://ror.org/03cdvht47","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210145365"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Assia Nouna","raw_affiliation_strings":["Hassan First University of Settat, ENSA Berrechid, Laboratory LAMSAD, Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hassan First University of Settat, ENSA Berrechid, Laboratory LAMSAD, Morocco","institution_ids":["https://openalex.org/I4210145365"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114358417","display_name":"Soumaya Nouna","orcid":"https://orcid.org/0000-0002-5733-1631"},"institutions":[{"id":"https://openalex.org/I4210145365","display_name":"Universit\u00e9 Hassan 1er","ror":"https://ror.org/03cdvht47","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210145365"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Soumaya Nouna","raw_affiliation_strings":["Hassan First University of Settat, ENSA Berrechid, Laboratory LAMSAD, Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hassan First University of Settat, ENSA Berrechid, Laboratory LAMSAD, Morocco","institution_ids":["https://openalex.org/I4210145365"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092558648","display_name":"Ilyas Tammouch","orcid":"https://orcid.org/0000-0003-2752-4413"},"institutions":[{"id":"https://openalex.org/I4210155111","display_name":"National School of Mineral Industry","ror":"https://ror.org/04a41pr43","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210155111"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Ilyas Tammouch","raw_affiliation_strings":["National School of Mines of Rabat (ENSMR), Laboratory of Systems Engineering and Digital Transformation (LISTD), Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National School of Mines of Rabat (ENSMR), Laboratory of Systems Engineering and Digital Transformation (LISTD), Morocco","institution_ids":["https://openalex.org/I4210155111"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5128859459","display_name":"Amal Badoui","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164065","display_name":"Universit\u00e9 Hassan II Mohammedia","ror":"https://ror.org/058gnfy87","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210164065"]},{"id":"https://openalex.org/I99297268","display_name":"University of Hassan II Casablanca","ror":"https://ror.org/001q4kn48","country_code":"MA","type":"education","lineage":["https://openalex.org/I99297268"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Amal Badoui","raw_affiliation_strings":["Faculty of Science and Technology of Mohamedia Hassan II University of Casablanca , Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Science and Technology of Mohamedia Hassan II University of Casablanca , Morocco","institution_ids":["https://openalex.org/I99297268","https://openalex.org/I4210164065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32396673,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"50","issue":"9","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9110000133514404,"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"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9110000133514404,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.04879999905824661,"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/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.012000000104308128,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9114000201225281},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6904000043869019},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6234999895095825},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.614300012588501},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.5184999704360962},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.49320000410079956},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.44600000977516174},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4453999996185303},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4300000071525574}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9114000201225281},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6904000043869019},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6866999864578247},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6793000102043152},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6234999895095825},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.614300012588501},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.5184999704360962},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.49320000410079956},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.44600000977516174},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4453999996185303},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.44110000133514404},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4300000071525574},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.42660000920295715},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.39989998936653137},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.39719998836517334},{"id":"https://openalex.org/C78168278","wikidata":"https://www.wikidata.org/wiki/Q5227269","display_name":"Data cube","level":2,"score":0.38670000433921814},{"id":"https://openalex.org/C176641082","wikidata":"https://www.wikidata.org/wiki/Q2446767","display_name":"Spectral signature","level":2,"score":0.3743000030517578},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3531999886035919},{"id":"https://openalex.org/C53051483","wikidata":"https://www.wikidata.org/wiki/Q861555","display_name":"Cube (algebra)","level":2,"score":0.3215999901294708},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.3070000112056732},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3059000074863434},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.2996000051498413},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.2703000009059906},{"id":"https://openalex.org/C2986522900","wikidata":"https://www.wikidata.org/wiki/Q2178623","display_name":"Spatial relationship","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C114700698","wikidata":"https://www.wikidata.org/wiki/Q2882278","display_name":"Spectral bands","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2572999894618988}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.31449/inf.v50i9.11461","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v50i9.11461","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/11461/6561","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.31449/inf.v50i9.11461","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v50i9.11461","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/11461/6561","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7135124208.pdf","grobid_xml":"https://content.openalex.org/works/W7135124208.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recent":[0],"studies":[1],"have":[2],"demonstrated":[3],"that":[4,123],"incorporating":[5],"both":[6],"spectral":[7,37,104],"and":[8,33,45,66,103,120,169],"spatial":[9,31,40,102],"information":[10,32],"significantlyenhances":[11],"the":[12,34,74,86,97,124,136,167],"accuracy":[13],"of":[14,171],"hyperspectral":[15,78,176],"image":[16,177],"(HSI)":[17],"classification.":[18,69],"Since":[19],"HSI":[20,68],"data":[21],"is":[22],"commonly":[23],"structuredas":[24],"3D":[25,39,59],"cubes,":[26],"where":[27],"two":[28,116],"dimensions":[29],"represent":[30],"third":[35],"encodes":[36],"bands,applying":[38],"filtering":[41],"becomes":[42],"an":[43],"intuitive":[44],"effective":[46],"way":[47],"to":[48,99,132],"extract":[49],"spectral\u2013spatial":[50,160],"features":[51],"simultaneously.In":[52],"this":[53],"work,":[54],"we":[55],"propose":[56],"a":[57,82,107],"deep":[58],"Convolutional":[60],"Neural":[61],"Network":[62],"(3D\u2013CNN)":[63],"architecturefor":[64],"accurate":[65],"efficient":[67],"Unlike":[70],"many":[71],"previous":[72],"methods,":[73],"proposed":[75],"model":[76],"processesthe":[77],"cube":[79],"directly":[80],"as":[81],"volumetric":[83],"input,":[84],"eliminating":[85],"need":[87],"for":[88,174],"manual":[89],"feature":[90],"extractionor":[91],"dimensionality":[92],"reduction.":[93],"This":[94],"design":[95],"allows":[96],"network":[98],"jointly":[100],"learn":[101],"dependencieswhile":[105],"maintaining":[106],"compact":[108],"architecture":[109],"with":[110,135],"fewer":[111],"trainable":[112],"parameters.":[113],"Experimental":[114],"evaluationson":[115],"benchmark":[117],"datasets\u2014Pavia":[118],"University":[119],"Salinas":[121],"Valley\u2014demonstrate":[122],"proposedmodel":[125],"achieves":[126],"95%":[127],"overall":[128],"classification":[129],"accuracy,":[130],"compared":[131],"88%":[133],"obtained":[134],"conventionalK-Nearest":[137],"Neighbors":[138],"(KNN)":[139],"baseline.":[140],"The":[141],"3D\u2013CNN":[142],"consistently":[143],"outperforms":[144],"traditional":[145],"methods":[146],"acrossmost":[147],"land-cover":[148],"classes,":[149],"particularly":[150],"in":[151],"spectrally":[152],"similar":[153],"or":[154],"complex":[155],"regions,":[156],"confirming":[157],"its":[158],"effectivenessfor":[159],"land":[161],"cover":[162],"mapping.":[163],"These":[164],"results":[165],"highlight":[166],"practicality":[168],"robustness":[170],"deepvolumetric":[172],"learning":[173],"real-world":[175],"analysis":[178]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-13T00:00:00"}