{"id":"https://openalex.org/W4407449791","doi":"https://doi.org/10.1109/access.2025.3542038","title":"A Hyperspectral Classification Method Based on Deep Learning and Dimension Reduction for Ground Environmental Monitoring","display_name":"A Hyperspectral Classification Method Based on Deep Learning and Dimension Reduction for Ground Environmental Monitoring","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4407449791","doi":"https://doi.org/10.1109/access.2025.3542038"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3542038","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3542038","pdf_url":null,"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://doi.org/10.1109/access.2025.3542038","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057348374","display_name":"Zhe Qiao","orcid":"https://orcid.org/0000-0003-4771-0512"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]},{"id":"https://openalex.org/I4210160629","display_name":"China Information Technology Security Evaluation Center","ror":"https://ror.org/053cexp66","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210160629"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiao Zhe","raw_affiliation_strings":["China Mobile Ltd., Information Security Management and Operation Center, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Mobile Ltd., Information Security Management and Operation Center, Beijing, China","institution_ids":["https://openalex.org/I180662265","https://openalex.org/I4210160629"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101471154","display_name":"Wei Gao","orcid":"https://orcid.org/0000-0003-2734-8886"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Gao","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100374170","display_name":"Chen Zhang","orcid":"https://orcid.org/0000-0003-2068-7279"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Zhang","raw_affiliation_strings":["China Mobile Group Design Institute Company Ltd., Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Mobile Group Design Institute Company Ltd., Beijing, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108835094","display_name":"Gang Du","orcid":null},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Du","raw_affiliation_strings":["China Mobile Group Design Institute Company Ltd., Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Mobile Group Design Institute Company Ltd., Beijing, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103683114","display_name":"Yan Li","orcid":null},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Li","raw_affiliation_strings":["China Mobile Group Design Institute Company Ltd., Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Mobile Group Design Institute Company Ltd., Beijing, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108521676","display_name":"Desheng Chen","orcid":"https://orcid.org/0009-0003-4129-0526"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Desheng Chen","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5057348374"],"corresponding_institution_ids":["https://openalex.org/I180662265","https://openalex.org/I4210160629"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":12.1209,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.98439376,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"13","issue":null,"first_page":"29969","last_page":"29982"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9990000128746033,"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":0.9990000128746033,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9628000259399414,"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":0.8255316019058228},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.6797124743461609},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6363261938095093},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6264899969100952},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5658636689186096},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.502408504486084},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4950210452079773},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39690566062927246},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3796602487564087},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1626744568347931},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.12955689430236816}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8255316019058228},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.6797124743461609},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6363261938095093},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6264899969100952},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5658636689186096},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.502408504486084},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4950210452079773},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39690566062927246},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3796602487564087},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1626744568347931},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.12955689430236816},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3542038","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3542038","pdf_url":null,"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:44debc5a9c31415ea15a2ef58c1ae1ac","is_oa":true,"landing_page_url":"https://doaj.org/article/44debc5a9c31415ea15a2ef58c1ae1ac","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":"IEEE Access, Vol 13, Pp 29969-29982 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3542038","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3542038","pdf_url":null,"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/13","score":0.49000000953674316,"display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G5949983300","display_name":null,"funder_award_id":"62301040","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W2033213769","https://openalex.org/W2067869061","https://openalex.org/W2097900616","https://openalex.org/W2100495367","https://openalex.org/W2110798204","https://openalex.org/W2127229869","https://openalex.org/W2128728535","https://openalex.org/W2136922672","https://openalex.org/W2150355110","https://openalex.org/W2166056814","https://openalex.org/W2170302354","https://openalex.org/W2187089797","https://openalex.org/W2500751094","https://openalex.org/W2607476064","https://openalex.org/W2962770389","https://openalex.org/W2963557263","https://openalex.org/W2996892897","https://openalex.org/W3046027728","https://openalex.org/W3046819794","https://openalex.org/W3098388691","https://openalex.org/W3122774149","https://openalex.org/W3142104381","https://openalex.org/W3146431338","https://openalex.org/W3164816634","https://openalex.org/W3170051579","https://openalex.org/W4256310901","https://openalex.org/W4283813834","https://openalex.org/W4290647413","https://openalex.org/W4306153721","https://openalex.org/W4387218348","https://openalex.org/W4390236223","https://openalex.org/W4390582117","https://openalex.org/W4390692639","https://openalex.org/W4391733570","https://openalex.org/W4392817973","https://openalex.org/W4393337124","https://openalex.org/W4399364209","https://openalex.org/W4403183452","https://openalex.org/W4403674752","https://openalex.org/W4406125504"],"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/W2404757046","https://openalex.org/W2070598848","https://openalex.org/W2019190440","https://openalex.org/W3034864990","https://openalex.org/W2292979300"],"abstract_inverted_index":{"Hyperspectral":[0],"remote":[1,60,158,264],"sensing":[2,61,159,265],"images":[3],"exhibit":[4,274],"high":[5],"dimensionality,":[6],"a":[7,54,87],"large":[8],"volume":[9],"of":[10,36,76,100,114,162,210,223,249,254,279],"data,":[11],"and":[12,24,51,83,103,118,166,179,199,216,230,239,286],"significant":[13],"redundant":[14],"information.":[15],"Before":[16],"using":[17],"deep":[18,88,123,131,201],"learning":[19,89,132,202],"methods":[20],"for":[21,58,126,174,184,204],"ground":[22,101,255,269],"monitoring":[23],"classification,":[25,205,267],"dimension":[26,186,193,245],"reduction":[27,73,112,194,226],"is":[28,63,152,170,214,228],"often":[29],"necessary.":[30],"In":[31],"response":[32],"to":[33,96,107],"the":[34,110,115,122,127,142,153,167,175,208,211,221,237],"limitations":[35],"traditional":[37,77],"principal":[38],"component":[39],"analysis":[40],"in":[41,149,262,277],"achieving":[42,268],"comprehensive":[43],"feature":[44],"extraction,":[45],"which":[46,65],"may":[47],"impact":[48,120],"classification":[49,56,99,212],"accuracy":[50,209,281,284],"computational":[52],"efficiency,":[53],"combined":[55,242],"method":[57],"hyperspectral":[59,157,263],"data":[62,185],"proposed,":[64],"uses":[66],"t-Distributed":[67],"Stochastic":[68],"Neighbor":[69],"Embedding":[70],"(t-SNE)":[71],"dimensionality":[72,111,225],"algorithm":[74,117],"instead":[75],"Principal":[78],"Component":[79],"Analysis":[80],"(PCA)":[81],"algorithm,":[82],"combines":[84],"it":[85],"with":[86,243],"network":[90,124,133],"model":[91],"Hybrid":[92],"Spectral":[93],"Network":[94,137],"(HybridSN),":[95],"achieve":[97],"accurate":[98],"cover":[102],"roof":[104],"materials.":[105],"Simultaneously,":[106],"further":[108],"validate":[109],"effect":[113],"t-SNE":[116,180,244],"its":[119],"on":[121,218],"model,":[125],"same":[128],"dataset,":[129,177],"another":[130],"Deep":[134],"Feature":[135],"Fusion":[136],"(DFFN)":[138],"was":[139],"set":[140],"as":[141,171],"experimental":[143,233],"control":[144],"group.":[145],"The":[146,232],"dataset":[147,160,164],"used":[148,183],"this":[150,219],"article":[151],"publicly":[154],"available":[155],"aerial":[156],"University":[161],"Pavia":[163],"(UP),":[165],"main":[168],"process":[169],"follows:":[172],"Firstly,":[173],"UP":[176],"PCA":[178],"algorithms":[181,227],"are":[182,195,247],"reduction.":[187],"Subsequently,":[188],"these":[189],"two":[190],"datasets":[191],"after":[192],"input":[196],"into":[197],"HybridSN":[198,238],"DFFN":[200,240],"models":[203,241],"respectively.":[206],"Finally,":[207],"results":[213,234],"assessed,":[215],"based":[217],"evaluation,":[220],"effectiveness":[222],"different":[224],"compared":[229],"analyzed.":[231],"demonstrate":[235],"that":[236],"reduction,":[246],"capable":[248],"effectively":[250],"extracting":[251],"hybrid":[252],"species":[253],"objects,":[256],"while":[257],"pre-serving":[258],"clear":[259],"edge":[260],"information":[261],"image":[266],"environment":[270],"monitoring.":[271],"They":[272],"also":[273],"superior":[275],"performance":[276],"terms":[278],"overall":[280],"(OA),":[282],"average":[283],"(AA),":[285],"Kappa":[287],"coefficient.":[288]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9}],"updated_date":"2026-04-06T07:47:59.780226","created_date":"2025-10-10T00:00:00"}
