{"id":"https://openalex.org/W4386895238","doi":"https://doi.org/10.3390/rs15184609","title":"Novel Land Cover Change Detection Deep Learning Framework with Very Small Initial Samples Using Heterogeneous Remote Sensing Images","display_name":"Novel Land Cover Change Detection Deep Learning Framework with Very Small Initial Samples Using Heterogeneous Remote Sensing Images","publication_year":2023,"publication_date":"2023-09-19","ids":{"openalex":"https://openalex.org/W4386895238","doi":"https://doi.org/10.3390/rs15184609"},"language":"en","primary_location":{"id":"doi:10.3390/rs15184609","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15184609","pdf_url":"https://www.mdpi.com/2072-4292/15/18/4609/pdf?version=1695128614","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/2072-4292/15/18/4609/pdf?version=1695128614","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100934632","display_name":"Yangpeng Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I181903023","display_name":"Xi'an Shiyou University","ror":"https://ror.org/040c7js64","country_code":"CN","type":"education","lineage":["https://openalex.org/I181903023"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yangpeng Zhu","raw_affiliation_strings":["School of Economics and Management, Xi\u2019an Shiyou University, Xi\u2019an 710065, China"],"affiliations":[{"raw_affiliation_string":"School of Economics and Management, Xi\u2019an Shiyou University, Xi\u2019an 710065, China","institution_ids":["https://openalex.org/I181903023"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113004816","display_name":"Qianyu Li","orcid":null},"institutions":[{"id":"https://openalex.org/I181903023","display_name":"Xi'an Shiyou University","ror":"https://ror.org/040c7js64","country_code":"CN","type":"education","lineage":["https://openalex.org/I181903023"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qianyu Li","raw_affiliation_strings":["School of Economics and Management, Xi\u2019an Shiyou University, Xi\u2019an 710065, China"],"affiliations":[{"raw_affiliation_string":"School of Economics and Management, Xi\u2019an Shiyou University, Xi\u2019an 710065, China","institution_ids":["https://openalex.org/I181903023"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047997045","display_name":"Zhiyong Lv","orcid":"https://orcid.org/0000-0003-2595-4794"},"institutions":[{"id":"https://openalex.org/I4210131919","display_name":"Xi'an University of Technology","ror":"https://ror.org/038avdt50","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyong Lv","raw_affiliation_strings":["School of Computer Science and Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China","institution_ids":["https://openalex.org/I4210131919"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040558555","display_name":"Nicola Falco","orcid":"https://orcid.org/0000-0003-3307-6098"},"institutions":[{"id":"https://openalex.org/I148283060","display_name":"Lawrence Berkeley National Laboratory","ror":"https://ror.org/02jbv0t02","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I148283060","https://openalex.org/I39565521"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nicola Falco","raw_affiliation_strings":["Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA"],"affiliations":[{"raw_affiliation_string":"Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA","institution_ids":["https://openalex.org/I148283060"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100934632"],"corresponding_institution_ids":["https://openalex.org/I181903023"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":0.4861,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.6860686,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"15","issue":"18","first_page":"4609","last_page":"4609"},"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9983000159263611,"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":0.9926000237464905,"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/change-detection","display_name":"Change detection","score":0.8039684295654297},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7408230900764465},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6793147921562195},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.5815147757530212},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5275532603263855},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.46204325556755066},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4025774300098419},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3792039453983307},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35103100538253784},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.1660265326499939},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.06819114089012146}],"concepts":[{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.8039684295654297},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7408230900764465},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6793147921562195},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.5815147757530212},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5275532603263855},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.46204325556755066},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4025774300098419},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3792039453983307},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35103100538253784},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.1660265326499939},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.06819114089012146},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs15184609","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15184609","pdf_url":"https://www.mdpi.com/2072-4292/15/18/4609/pdf?version=1695128614","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:15f211d66b5f4c1186a402bc9da13117","is_oa":true,"landing_page_url":"https://doaj.org/article/15f211d66b5f4c1186a402bc9da13117","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":"Remote Sensing, Vol 15, Iss 18, p 4609 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs15184609","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15184609","pdf_url":"https://www.mdpi.com/2072-4292/15/18/4609/pdf?version=1695128614","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":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.5}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386895238.pdf"},"referenced_works_count":73,"referenced_works":["https://openalex.org/W1965056035","https://openalex.org/W2036798369","https://openalex.org/W2042806874","https://openalex.org/W2056211433","https://openalex.org/W2062593139","https://openalex.org/W2083863337","https://openalex.org/W2140023211","https://openalex.org/W2161570034","https://openalex.org/W2176950688","https://openalex.org/W2233053992","https://openalex.org/W2488463887","https://openalex.org/W2519960185","https://openalex.org/W2530415363","https://openalex.org/W2604306584","https://openalex.org/W2735042947","https://openalex.org/W2769613401","https://openalex.org/W2779571083","https://openalex.org/W2789781087","https://openalex.org/W2791917037","https://openalex.org/W2792827505","https://openalex.org/W2793638091","https://openalex.org/W2794833245","https://openalex.org/W2808781521","https://openalex.org/W2885502514","https://openalex.org/W2891248708","https://openalex.org/W2894544606","https://openalex.org/W2922509574","https://openalex.org/W2935081211","https://openalex.org/W2954332586","https://openalex.org/W2973179191","https://openalex.org/W2985521021","https://openalex.org/W3009942016","https://openalex.org/W3015038817","https://openalex.org/W3035335060","https://openalex.org/W3036453075","https://openalex.org/W3047246571","https://openalex.org/W3049615702","https://openalex.org/W3081744000","https://openalex.org/W3098741497","https://openalex.org/W3102127038","https://openalex.org/W3108293152","https://openalex.org/W3127542860","https://openalex.org/W3131096279","https://openalex.org/W3142421496","https://openalex.org/W3144332889","https://openalex.org/W3151904266","https://openalex.org/W3182257909","https://openalex.org/W3182928821","https://openalex.org/W3189451737","https://openalex.org/W3199538063","https://openalex.org/W3211646616","https://openalex.org/W4205937042","https://openalex.org/W4206550078","https://openalex.org/W4213390660","https://openalex.org/W4281726412","https://openalex.org/W4283718418","https://openalex.org/W4285176380","https://openalex.org/W4308325132","https://openalex.org/W4313438466","https://openalex.org/W4366150256","https://openalex.org/W4366310757","https://openalex.org/W4376481071","https://openalex.org/W4381597277","https://openalex.org/W6641506149","https://openalex.org/W6727029182","https://openalex.org/W6761616155","https://openalex.org/W6782626842","https://openalex.org/W6784889261","https://openalex.org/W6790190628","https://openalex.org/W6798945365","https://openalex.org/W6801222320","https://openalex.org/W6806987155","https://openalex.org/W6839166376"],"related_works":["https://openalex.org/W2568858292","https://openalex.org/W1515964938","https://openalex.org/W2389381914","https://openalex.org/W3181296946","https://openalex.org/W2376528221","https://openalex.org/W4375867731","https://openalex.org/W2359428812","https://openalex.org/W196800607","https://openalex.org/W2153381734","https://openalex.org/W2050072374"],"abstract_inverted_index":{"Change":[0],"detection":[1,67,182],"with":[2,108,120,184,206,212,227,234,259],"heterogeneous":[3,29],"remote":[4,20,30],"sensing":[5,21,31],"images":[6,22,32],"(Hete-CD)":[7],"plays":[8],"a":[9,58,97,109,117,121,143,185,228],"significant":[10],"role":[11],"in":[12,16,80,84],"practical":[13],"applications,":[14],"particularly":[15],"cases":[17],"where":[18],"homogenous":[19],"are":[23,173,253],"unavailable.":[24],"However,":[25],"directly":[26],"comparing":[27],"bitemporal":[28],"(HRSIs)":[33],"to":[34,48,87,103,129,158,179],"measure":[35],"the":[36,50,54,88,152,160,220,250,260],"change":[37,66,133,181],"magnitude":[38],"is":[39,70,156],"unfeasible.":[40],"Numerous":[41],"deep":[42,75,245,265],"learning":[43,76,246,266],"methods":[44,241,263],"require":[45],"substantial":[46],"samples":[47,62,162,232],"train":[49],"module":[51],"adequately.":[52],"Moreover,":[53],"process":[55],"of":[56,61,91,112,188,200,231],"labeling":[57],"large":[59],"number":[60,90,111,187,230],"for":[63,101],"land":[64],"cover":[65],"using":[68],"HRSIs":[69],"time-consuming":[71],"and":[72,139,170,209,214,242,256,264],"labor-intensive.":[73],"Consequently,":[74],"networks":[77],"face":[78],"challenges":[79],"achieving":[81],"satisfactory":[82,105],"performance":[83,106,183],"Hete-CD":[85,102],"due":[86],"limited":[89,110,186],"training":[92],"samples.":[93,114,190],"This":[94,125],"study":[95],"proposes":[96],"novel":[98],"deep-learning":[99],"framework":[100,178,222],"achieve":[104,224],"even":[107],"initial":[113,165],"We":[115],"developed":[116],"multiscale":[118],"network":[119,169],"selected":[122,261],"kernel-attention":[123],"module.":[124],"design":[126],"allows":[127],"us":[128],"effectively":[130],"capture":[131],"different":[132],"targets":[134],"characterized":[135],"by":[136],"diverse":[137],"sizes":[138],"shapes.":[140],"In":[141],"addition,":[142],"simple":[144],"yet":[145],"effective":[146],"non-parameter":[147],"sample-enhanced":[148,171],"algorithm":[149,172],"that":[150,219],"utilizes":[151],"Pearson":[153],"correlation":[154],"coefficient":[155],"proposed":[157,168,221],"explore":[159],"potential":[161],"surrounding":[163],"every":[164],"sample.":[166],"The":[167,191],"integrated":[174],"into":[175],"an":[176],"iterative":[177],"improve":[180],"small":[189,229],"experimental":[192],"results":[193],"were":[194,204],"achieved":[195],"based":[196],"on":[197],"four":[198],"pairs":[199],"real":[201],"HRSIs,":[202],"which":[203],"acquired":[205],"Landsat-5,":[207],"Radarsat-2,":[208],"Sentinel-2":[210],"satellites":[211],"optical":[213],"SAR":[215],"sensors.":[216],"Results":[217],"indicated":[218],"could":[223],"competitive":[225],"accuracy":[226],"compared":[233,258],"some":[235],"state-of-the-art":[236,244],"methods,":[237,267],"including":[238],"three":[239],"traditional":[240,262],"nine":[243],"methods.":[247],"For":[248],"example,":[249],"improvement":[251],"rates":[252],"approximately":[254],"3.38%":[255],"1.99%":[257],"respectively.":[268]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-02-28T09:26:25.869077","created_date":"2025-10-10T00:00:00"}
