{"id":"https://openalex.org/W2988401550","doi":"https://doi.org/10.1109/lgrs.2019.2948799","title":"Deep Feature Clustering for Remote Sensing Imagery Land Cover Analysis","display_name":"Deep Feature Clustering for Remote Sensing Imagery Land Cover Analysis","publication_year":2019,"publication_date":"2019-10-30","ids":{"openalex":"https://openalex.org/W2988401550","doi":"https://doi.org/10.1109/lgrs.2019.2948799","mag":"2988401550"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2019.2948799","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2019.2948799","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-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/A5000803509","display_name":"Rasha S. Gargees","orcid":"https://orcid.org/0000-0003-3087-2910"},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rasha S. Gargees","raw_affiliation_strings":["University of Missouri, Columbia, USA"],"raw_orcid":"https://orcid.org/0000-0003-3087-2910","affiliations":[{"raw_affiliation_string":"University of Missouri, Columbia, USA","institution_ids":["https://openalex.org/I76835614"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051712346","display_name":"Grant J. Scott","orcid":"https://orcid.org/0000-0001-5870-9387"},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Grant J. Scott","raw_affiliation_strings":["University of Missouri, Columbia, USA"],"raw_orcid":"https://orcid.org/0000-0001-5870-9387","affiliations":[{"raw_affiliation_string":"University of Missouri, Columbia, USA","institution_ids":["https://openalex.org/I76835614"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I76835614"],"apc_list":null,"apc_paid":null,"fwci":1.4155,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.84858026,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"17","issue":"8","first_page":"1386","last_page":"1390"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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":0.9998999834060669,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9955000281333923,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7641299962997437},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6324701309204102},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6214175224304199},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.6179722547531128},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6147183775901794},{"id":"https://openalex.org/keywords/geospatial-analysis","display_name":"Geospatial analysis","score":0.613554060459137},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.550103485584259},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5058662295341492},{"id":"https://openalex.org/keywords/satellite-imagery","display_name":"Satellite imagery","score":0.5044230222702026},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5043371915817261},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5021955966949463},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.47800031304359436},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44567161798477173},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36164212226867676},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.16162821650505066},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.15583735704421997}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7641299962997437},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6324701309204102},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6214175224304199},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.6179722547531128},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6147183775901794},{"id":"https://openalex.org/C9770341","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geospatial analysis","level":2,"score":0.613554060459137},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.550103485584259},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5058662295341492},{"id":"https://openalex.org/C2778102629","wikidata":"https://www.wikidata.org/wiki/Q725252","display_name":"Satellite imagery","level":2,"score":0.5044230222702026},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5043371915817261},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5021955966949463},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.47800031304359436},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44567161798477173},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36164212226867676},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.16162821650505066},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.15583735704421997},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2019.2948799","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2019.2948799","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.6000000238418579}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1912954554","https://openalex.org/W1983292896","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2592962403","https://openalex.org/W2617297862","https://openalex.org/W2626107033","https://openalex.org/W2734804095","https://openalex.org/W2774258507","https://openalex.org/W2795417538","https://openalex.org/W2884013100","https://openalex.org/W2910587630","https://openalex.org/W3103856189","https://openalex.org/W6684191040","https://openalex.org/W6738239618"],"related_works":["https://openalex.org/W4367313141","https://openalex.org/W2004086023","https://openalex.org/W2733999579","https://openalex.org/W2910751785","https://openalex.org/W2110217573","https://openalex.org/W4283374591","https://openalex.org/W4366547507","https://openalex.org/W4387891126","https://openalex.org/W4390100400","https://openalex.org/W2088899772"],"abstract_inverted_index":{"In":[0],"this":[1],"letter,":[2],"we":[3],"propose":[4],"a":[5,25,62,112],"chip-based":[6,101],"technique":[7],"for":[8,48,58,121],"large-scale,":[9],"automatic":[10],"land":[11,93,145],"cover":[12,94,146],"clustering":[13,102],"of":[14,66,90,107,114,127,147],"high-resolution":[15],"remote":[16],"sensing":[17],"imagery":[18,57,67],"(HR-RSI)":[19],"using":[20,98],"deep":[21,26,49],"visual":[22,78],"features":[23,79],"from":[24,70],"convolutional":[27],"neural":[28,50],"network":[29],"(DCNN)":[30],"along":[31],"with":[32],"the":[33,81,91,108,128,144,148],"fuzzy":[34,115],"c-means":[35],"algorithm.":[36],"The":[37,124],"proposed":[38,138],"method,":[39],"unlike":[40],"traditional":[41],"methods,":[42],"facilitates":[43],"utilizing":[44,80],"transfer":[45,82],"learning":[46],"techniques":[47],"models":[51],"that":[52,136],"are":[53],"fined-tuned":[54],"to":[55,76],"satellite":[56],"feature":[59,99],"extraction.":[60],"Then,":[61],"large":[63],"conterminous":[64],"region":[65],"is":[68,95,140],"acquired":[69],"HR-RSI":[71],"data":[72],"providers":[73],"and":[74,87,104,117,132],"scanned":[75],"extract":[77],"learned":[83],"model.":[84],"Broad-area":[85],"thematic":[86],"contextual":[88],"understanding":[89],"geographic":[92,133],"efficiently":[96],"achieved":[97],"reduction,":[100],"analysis,":[103,131],"geospatial":[105],"rendering":[106],"clusters.":[109],"We":[110],"explore":[111],"variety":[113],"clusterings":[116],"their":[118],"resulting":[119],"utility":[120],"spatial":[122,125],"analysis.":[123],"densities":[126],"clusters,":[129],"numerical":[130],"aggregations":[134],"show":[135],"our":[137],"approach":[139],"effective":[141],"in":[142],"examining":[143],"earth.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}