{"id":"https://openalex.org/W2792827505","doi":"https://doi.org/10.1109/tgrs.2018.2863224","title":"Learning Spectral-Spatial-Temporal Features via a Recurrent Convolutional Neural Network for Change Detection in Multispectral Imagery","display_name":"Learning Spectral-Spatial-Temporal Features via a Recurrent Convolutional Neural Network for Change Detection in Multispectral Imagery","publication_year":2018,"publication_date":"2018-11-20","ids":{"openalex":"https://openalex.org/W2792827505","doi":"https://doi.org/10.1109/tgrs.2018.2863224","mag":"2792827505"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2018.2863224","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tgrs.2018.2863224","pdf_url":"https://ieeexplore.ieee.org/ielx7/36/8620597/08541102.pdf","source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://ieeexplore.ieee.org/ielx7/36/8620597/08541102.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024379450","display_name":"Lichao Mou","orcid":"https://orcid.org/0000-0001-8407-6413"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Lichao Mou","raw_affiliation_strings":["Signal Processing in Earth Observation, Technical University of Munich, Munich, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Signal Processing in Earth Observation, Technical University of Munich, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006095323","display_name":"Lorenzo Bruzzone","orcid":"https://orcid.org/0000-0002-6036-459X"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Lorenzo Bruzzone","raw_affiliation_strings":["Department of Information Engineering and Computer Science, University of Trento, Trento, Italy"],"raw_orcid":"https://orcid.org/0000-0002-6036-459X","affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Computer Science, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068384981","display_name":"Xiao Xiang Zhu","orcid":"https://orcid.org/0000-0001-5530-3613"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Xiao Xiang Zhu","raw_affiliation_strings":["Signal Processing in Earth Observation, Technical University of Munich, Munich, Germany"],"raw_orcid":"https://orcid.org/0000-0001-5530-3613","affiliations":[{"raw_affiliation_string":"Signal Processing in Earth Observation, Technical University of Munich, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":{"value":1157,"currency":"EUR","value_usd":1247},"fwci":35.2151,"has_fulltext":true,"cited_by_count":635,"citation_normalized_percentile":{"value":0.99823277,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"57","issue":"2","first_page":"924","last_page":"935"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9855999946594238,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9769999980926514,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.8658304214477539},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.688237190246582},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6498641967773438},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6249444484710693},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.6235940456390381},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5687397718429565},{"id":"https://openalex.org/keywords/multispectral-pattern-recognition","display_name":"Multispectral pattern recognition","score":0.5247210264205933},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45622286200523376},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.23000088334083557}],"concepts":[{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.8658304214477539},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.688237190246582},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6498641967773438},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6249444484710693},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.6235940456390381},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5687397718429565},{"id":"https://openalex.org/C104541649","wikidata":"https://www.wikidata.org/wiki/Q6935090","display_name":"Multispectral pattern recognition","level":3,"score":0.5247210264205933},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45622286200523376},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.23000088334083557}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tgrs.2018.2863224","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tgrs.2018.2863224","pdf_url":"https://ieeexplore.ieee.org/ielx7/36/8620597/08541102.pdf","source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1803.02642","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1803.02642","pdf_url":"https://arxiv.org/pdf/1803.02642","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:iris.unitn.it:11572/250911","is_oa":true,"landing_page_url":"https://hdl.handle.net/11572/250911","pdf_url":"https://iris.unitn.it/bitstream/11572/250911/2/Learning_Spectral-Spatial-Temporal_Features_via_a_Recurrent_Convolutional_Neural_Network_for_Change_Detection_in_Multispectral_Imagery.pdf","source":{"id":"https://openalex.org/S4377196320","display_name":"Iris (University of Trento)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193223587","host_organization_name":"University of Trento","host_organization_lineage":["https://openalex.org/I193223587"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:elib.dlr.de:120596","is_oa":false,"landing_page_url":"https://elib.dlr.de/120596/","pdf_url":null,"source":{"id":"https://openalex.org/S4377196266","display_name":"elib (German Aerospace Center)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2898391981","host_organization_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","host_organization_lineage":["https://openalex.org/I2898391981"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Zeitschriftenbeitrag"}],"best_oa_location":{"id":"doi:10.1109/tgrs.2018.2863224","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tgrs.2018.2863224","pdf_url":"https://ieeexplore.ieee.org/ielx7/36/8620597/08541102.pdf","source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6662499415","display_name":null,"funder_award_id":"ERC-2016-StG-714087","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"},{"id":"https://openalex.org/G872314110","display_name":null,"funder_award_id":"VHNG-1018","funder_id":"https://openalex.org/F4320325698","funder_display_name":"Helmholtz Association"}],"funders":[{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"},{"id":"https://openalex.org/F4320325698","display_name":"Helmholtz Association","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2792827505.pdf","grobid_xml":"https://content.openalex.org/works/W2792827505.grobid-xml"},"referenced_works_count":71,"referenced_works":["https://openalex.org/W104184427","https://openalex.org/W1499255288","https://openalex.org/W1521436688","https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1610060839","https://openalex.org/W1661193476","https://openalex.org/W1669730594","https://openalex.org/W1686810756","https://openalex.org/W1810943226","https://openalex.org/W1963949604","https://openalex.org/W1979061792","https://openalex.org/W1998595580","https://openalex.org/W2006383776","https://openalex.org/W2011068521","https://openalex.org/W2064675550","https://openalex.org/W2083615851","https://openalex.org/W2097117768","https://openalex.org/W2097326416","https://openalex.org/W2098594213","https://openalex.org/W2104374858","https://openalex.org/W2118116484","https://openalex.org/W2122700624","https://openalex.org/W2127038040","https://openalex.org/W2134969826","https://openalex.org/W2136236240","https://openalex.org/W2147800946","https://openalex.org/W2163605009","https://openalex.org/W2165350297","https://openalex.org/W2328456116","https://openalex.org/W2412782625","https://openalex.org/W2431738724","https://openalex.org/W2494341560","https://openalex.org/W2538244214","https://openalex.org/W2547812480","https://openalex.org/W2572303978","https://openalex.org/W2584763393","https://openalex.org/W2586898334","https://openalex.org/W2587329506","https://openalex.org/W2598666589","https://openalex.org/W2600746131","https://openalex.org/W2612149202","https://openalex.org/W2624909539","https://openalex.org/W2737391801","https://openalex.org/W2757208835","https://openalex.org/W2760923572","https://openalex.org/W2764034829","https://openalex.org/W2768211636","https://openalex.org/W2782522152","https://openalex.org/W2786038065","https://openalex.org/W2787931417","https://openalex.org/W2792332881","https://openalex.org/W2804902458","https://openalex.org/W2829067510","https://openalex.org/W2884821995","https://openalex.org/W2903382683","https://openalex.org/W2952865063","https://openalex.org/W2964121744","https://openalex.org/W3101640299","https://openalex.org/W3104839310","https://openalex.org/W3105127913","https://openalex.org/W4240485910","https://openalex.org/W4251033893","https://openalex.org/W6604254268","https://openalex.org/W6629944422","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6731975103","https://openalex.org/W6737203840"],"related_works":["https://openalex.org/W2031512949","https://openalex.org/W2128126485","https://openalex.org/W4382563209","https://openalex.org/W2124952510","https://openalex.org/W2777937183","https://openalex.org/W2108633818","https://openalex.org/W1752760603","https://openalex.org/W1995889410","https://openalex.org/W4389779246","https://openalex.org/W3005969065"],"abstract_inverted_index":{"Change":[0],"detection":[1,47,139],"is":[2,32,72,108,144,176,198],"one":[3,67],"of":[4,146,157,210],"the":[5,81,98,149,158,177,211,218],"central":[6],"problems":[7],"in":[8,41,48,87,111,217],"earth":[9],"observation":[10],"and":[11,61,141,207],"was":[12],"extensively":[13],"investigated":[14],"over":[15],"recent":[16],"decades.":[17],"In":[18,90],"this":[19,52,175],"paper,":[20],"we":[21,54,173],"propose":[22],"a":[23,36,42,57,62,181],"novel":[24],"recurrent":[25,63,182],"convolutional":[26,58,183],"neural":[27,59,64],"network":[28,60,65,100,184,197],"(ReCNN)":[29],"architecture,":[30],"which":[31],"trained":[33,121],"to":[34,74,95,113,134,137],"learn":[35],"joint":[37],"spectral-spatial-temporal":[38],"feature":[39,78],"representation":[40],"unified":[43],"framework":[44],"for":[45,189],"change":[46,96,138],"multispectral":[49,202],"images.":[50,89],"To":[51],"end,":[53],"bring":[55],"together":[56],"into":[66],"end-to-end":[68,109],"network.":[69],"The":[70,195],"former":[71],"able":[73],"generate":[75],"rich":[76],"spectral-spatial":[77],"representations,":[79],"while":[80],"latter":[82],"effectively":[83],"analyzes":[84],"temporal":[85,150],"dependence":[86,151],"bitemporal":[88],"comparison":[91],"with":[92],"previous":[93],"approaches":[94],"detection,":[97],"proposed":[99,188,196,219],"architecture":[101,185],"possesses":[102],"three":[103],"distinctive":[104],"properties:":[105],"1)":[106],"it":[107,125,143],"trainable,":[110],"contrast":[112],"most":[114,156],"existing":[115],"methods":[116],"whose":[117],"components":[118],"are":[119],"separately":[120],"or":[122,168],"computed;":[123],"2)":[124],"naturally":[126],"harnesses":[127],"spatial":[128],"information":[129],"that":[130,160,180],"has":[131,186],"been":[132,187],"proven":[133],"be":[135],"beneficial":[136],"task;":[140],"3)":[142],"capable":[145],"adaptively":[147],"learning":[148],"between":[152],"multitemporal":[153,190],"images,":[154],"unlike":[155],"algorithms":[159],"use":[161],"fairly":[162],"simple":[163],"operation":[164],"like":[165],"image":[166,193],"differencing":[167],"stacking.":[169],"As":[170],"far":[171],"as":[172],"know,":[174],"first":[178],"time":[179],"remote":[191],"sensing":[192],"analysis.":[194],"validated":[199],"on":[200],"real":[201],"data":[203],"sets.":[204],"Both":[205],"visual":[206],"quantitative":[208],"analyses":[209],"experimental":[212],"results":[213],"demonstrate":[214],"competitive":[215],"performance":[216],"mode.":[220]},"counts_by_year":[{"year":2026,"cited_by_count":47},{"year":2025,"cited_by_count":84},{"year":2024,"cited_by_count":112},{"year":2023,"cited_by_count":89},{"year":2022,"cited_by_count":96},{"year":2021,"cited_by_count":76},{"year":2020,"cited_by_count":69},{"year":2019,"cited_by_count":53},{"year":2018,"cited_by_count":9}],"updated_date":"2026-08-29T07:29:34.045763","created_date":"2025-10-10T00:00:00"}
