{"id":"https://openalex.org/W3037587714","doi":"https://doi.org/10.3390/rs12122010","title":"A New End-to-End Multi-Dimensional CNN Framework for Land Cover/Land Use Change Detection in Multi-Source Remote Sensing Datasets","display_name":"A New End-to-End Multi-Dimensional CNN Framework for Land Cover/Land Use Change Detection in Multi-Source Remote Sensing Datasets","publication_year":2020,"publication_date":"2020-06-23","ids":{"openalex":"https://openalex.org/W3037587714","doi":"https://doi.org/10.3390/rs12122010","mag":"3037587714"},"language":"en","primary_location":{"id":"doi:10.3390/rs12122010","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12122010","pdf_url":"https://www.mdpi.com/2072-4292/12/12/2010/pdf","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/12/12/2010/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018156889","display_name":"Seyd Teymoor Seydi","orcid":"https://orcid.org/0000-0002-3678-4877"},"institutions":[{"id":"https://openalex.org/I23946033","display_name":"University of Tehran","ror":"https://ror.org/05vf56z40","country_code":"IR","type":"education","lineage":["https://openalex.org/I23946033"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Seyd Teymoor Seydi","raw_affiliation_strings":["School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran 14174-66191, Iran"],"raw_orcid":"https://orcid.org/0000-0002-3678-4877","affiliations":[{"raw_affiliation_string":"School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran 14174-66191, Iran","institution_ids":["https://openalex.org/I23946033"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003591539","display_name":"Mahdi Hasanlou","orcid":"https://orcid.org/0000-0002-7254-4475"},"institutions":[{"id":"https://openalex.org/I23946033","display_name":"University of Tehran","ror":"https://ror.org/05vf56z40","country_code":"IR","type":"education","lineage":["https://openalex.org/I23946033"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mahdi Hasanlou","raw_affiliation_strings":["School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran 14174-66191, Iran"],"raw_orcid":"https://orcid.org/0000-0002-7254-4475","affiliations":[{"raw_affiliation_string":"School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran 14174-66191, Iran","institution_ids":["https://openalex.org/I23946033"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020765155","display_name":"Meisam Amani","orcid":"https://orcid.org/0000-0002-9495-4010"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Meisam Amani","raw_affiliation_strings":["Wood Environment &amp; Infrastructure Solutions, Ottawa, ON K2E 7K3, Canada"],"raw_orcid":"https://orcid.org/0000-0002-9495-4010","affiliations":[{"raw_affiliation_string":"Wood Environment &amp; Infrastructure Solutions, Ottawa, ON K2E 7K3, Canada","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5020765155"],"corresponding_institution_ids":[],"apc_list":{"value":2500,"currency":"CHF","value_usd":2784},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2784},"fwci":7.5587,"has_fulltext":true,"cited_by_count":122,"citation_normalized_percentile":{"value":0.9760161,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"12","issue":"12","first_page":"2010","last_page":"2010"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9952999949455261,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.989799976348877,"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":0.809675931930542},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6590136885643005},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.6389577984809875},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5967090129852295},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5072945952415466},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49352943897247314},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.4694494903087616},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.4670632779598236},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.45706334710121155},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45340365171432495},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.4265989363193512},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4175414443016052},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3874852657318115},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2251291573047638},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.17677122354507446},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.0762915313243866},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.0702202320098877}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.809675931930542},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6590136885643005},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.6389577984809875},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5967090129852295},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5072945952415466},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49352943897247314},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.4694494903087616},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.4670632779598236},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.45706334710121155},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45340365171432495},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.4265989363193512},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4175414443016052},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3874852657318115},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2251291573047638},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.17677122354507446},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0762915313243866},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0702202320098877},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs12122010","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12122010","pdf_url":"https://www.mdpi.com/2072-4292/12/12/2010/pdf","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:346a5421374b4dcd9f4c92a6e346ec41","is_oa":true,"landing_page_url":"https://doaj.org/article/346a5421374b4dcd9f4c92a6e346ec41","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":"Remote Sensing, Vol 12, Iss 12, p 2010 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/12/12/2010/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs12122010","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Remote Sensing; Volume 12; Issue 12; Pages: 2010","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs12122010","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12122010","pdf_url":"https://www.mdpi.com/2072-4292/12/12/2010/pdf","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Life in Land","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334537","display_name":"T\u00e9l\u00e9com Paris","ror":"https://ror.org/01naq7912"},{"id":"https://openalex.org/F4320336050","display_name":"Office National d'\u00e9tudes et de Recherches A\u00e9rospatiales","ror":"https://ror.org/005y2ap84"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3037587714.pdf","grobid_xml":"https://content.openalex.org/works/W3037587714.grobid-xml"},"referenced_works_count":81,"referenced_works":["https://openalex.org/W169052826","https://openalex.org/W1483184156","https://openalex.org/W1533861849","https://openalex.org/W1555161590","https://openalex.org/W1964669384","https://openalex.org/W1965395441","https://openalex.org/W1979061792","https://openalex.org/W2001298088","https://openalex.org/W2006383776","https://openalex.org/W2085567910","https://openalex.org/W2089327948","https://openalex.org/W2095705004","https://openalex.org/W2096328930","https://openalex.org/W2097936357","https://openalex.org/W2105993120","https://openalex.org/W2110873156","https://openalex.org/W2134969826","https://openalex.org/W2157026765","https://openalex.org/W2159872961","https://openalex.org/W2314785379","https://openalex.org/W2334023959","https://openalex.org/W2403156809","https://openalex.org/W2518815253","https://openalex.org/W2623572502","https://openalex.org/W2736719870","https://openalex.org/W2752439463","https://openalex.org/W2773926432","https://openalex.org/W2783608381","https://openalex.org/W2809254203","https://openalex.org/W2883305476","https://openalex.org/W2884223658","https://openalex.org/W2884276099","https://openalex.org/W2889211735","https://openalex.org/W2891248708","https://openalex.org/W2896365540","https://openalex.org/W2898923688","https://openalex.org/W2900587135","https://openalex.org/W2905181079","https://openalex.org/W2910071851","https://openalex.org/W2910587630","https://openalex.org/W2911648799","https://openalex.org/W2911976185","https://openalex.org/W2912323362","https://openalex.org/W2914272072","https://openalex.org/W2914331134","https://openalex.org/W2914676574","https://openalex.org/W2917189553","https://openalex.org/W2921886782","https://openalex.org/W2939880928","https://openalex.org/W2948638562","https://openalex.org/W2953308875","https://openalex.org/W2963273475","https://openalex.org/W2965608468","https://openalex.org/W2967626412","https://openalex.org/W2969662039","https://openalex.org/W2979967919","https://openalex.org/W2980725593","https://openalex.org/W2983391997","https://openalex.org/W2984954051","https://openalex.org/W2990689524","https://openalex.org/W2991575127","https://openalex.org/W2994033677","https://openalex.org/W2995054852","https://openalex.org/W2997968425","https://openalex.org/W3000451586","https://openalex.org/W3002041678","https://openalex.org/W3002349559","https://openalex.org/W3003841907","https://openalex.org/W3004839151","https://openalex.org/W3005491787","https://openalex.org/W3009850435","https://openalex.org/W3011614889","https://openalex.org/W3015167329","https://openalex.org/W3080110180","https://openalex.org/W3099831940","https://openalex.org/W6606879723","https://openalex.org/W6674330103","https://openalex.org/W6692201896","https://openalex.org/W6751795543","https://openalex.org/W6753547298","https://openalex.org/W6771744290"],"related_works":["https://openalex.org/W2022304901","https://openalex.org/W2018850895","https://openalex.org/W2988577871","https://openalex.org/W2758145160","https://openalex.org/W4205174160","https://openalex.org/W1973197867","https://openalex.org/W3005969065","https://openalex.org/W4281675222","https://openalex.org/W2568271140","https://openalex.org/W2153381734"],"abstract_inverted_index":{"The":[0,87,144,173],"diversity":[1],"of":[2,17,85,120,137,148,159,175,195,206,239],"change":[3,47,121],"detection":[4],"(CD)":[5],"methods":[6,35],"and":[7,42,49,98,109,112,127,142,146,167,184,235,248,251,256,266],"the":[8,64,75,83,96,106,113,118,149,176,193,196,199,212,216,220,231,240,252,257],"limitations":[9],"in":[10,39],"generalizing":[11],"these":[12],"techniques":[13],"using":[14,155,198],"different":[15,157,189,229],"types":[16,136,158],"remote":[18,160,222],"sensing":[19,161,223],"datasets":[20,163],"over":[21],"various":[22],"study":[23],"areas":[24],"have":[25,36],"been":[26,37],"a":[27,58],"challenge":[28],"for":[29],"CD":[30,34,60,90,151,177,197,209,224,242],"applications.":[31],"Additionally,":[32,131],"most":[33],"implemented":[38],"two":[40],"intensive":[41],"time-consuming":[43],"steps:":[44],"(a)":[45],"predicting":[46],"areas,":[48],"(b)":[50],"decision":[51],"on":[52,63,105,117,125],"predicted":[53],"areas.":[54],"In":[55],"this":[56],"study,":[57],"novel":[59],"framework":[61],"based":[62,124],"convolutional":[65],"neural":[66],"network":[67,91],"(CNN)":[68],"is":[69],"proposed":[70,88,150,200,217,241],"to":[71,80,204],"not":[72],"only":[73],"address":[74],"aforementioned":[76],"problems":[77],"but":[78],"also":[79,180],"considerably":[81],"improve":[82],"level":[84],"accuracy.":[86],"CNN-based":[89],"contains":[92],"three":[93,135,156],"parallel":[94],"channels:":[95],"first":[97],"second":[99],"channels,":[100],"respectively,":[101,250],"extract":[102],"deep":[103,122,129],"features":[104,123],"original":[107],"first-":[108],"second-time":[110],"imagery":[111],"third":[114],"channel":[115,133],"focuses":[116],"extraction":[119],"differencing":[126],"staking":[128],"features.":[130],"each":[132],"includes":[134],"convolution":[138],"kernels:":[139],"1D-,":[140],"2D-,":[141],"3D-dilated-convolution.":[143],"effectiveness":[145],"reliability":[147],"method":[152,201,218,243],"are":[153,179,202,244,262],"evaluated":[154,181],"benchmark":[162],"(i.e.,":[164],"multispectral,":[165],"hyperspectral,":[166],"Polarimetric":[168],"Synthetic":[169],"Aperture":[170],"RADAR":[171],"(PolSAR)).":[172],"results":[174,194,213],"maps":[178],"both":[182],"visually":[183],"statistically":[185],"by":[186],"calculating":[187],"nine":[188],"accuracy":[190],"indices.":[191],"Moreover,":[192],"compared":[203],"those":[205],"several":[207],"state-of-the-art":[208],"algorithms.":[210],"All":[211],"prove":[214],"that":[215],"outperforms":[219],"other":[221],"techniques.":[225],"For":[226],"instance,":[227],"considering":[228],"scenarios,":[230],"Overall":[232],"Accuracies":[233],"(OAs)":[234],"Kappa":[236],"Coefficients":[237],"(KCs)":[238],"better":[245],"than":[246,264],"95.89%":[247],"0.805,":[249],"Miss":[253],"Detection":[254],"(MD)":[255],"False":[258],"Alarm":[259],"(FA)":[260],"rates":[261],"lower":[263],"12%":[265],"3%,":[267],"respectively.":[268]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":20},{"year":2024,"cited_by_count":25},{"year":2023,"cited_by_count":22},{"year":2022,"cited_by_count":19},{"year":2021,"cited_by_count":22},{"year":2020,"cited_by_count":5}],"updated_date":"2026-08-16T07:02:28.622633","created_date":"2025-10-10T00:00:00"}
