{"id":"https://openalex.org/W3009518842","doi":"https://doi.org/10.3390/rs12050832","title":"Synergistic Use of Multi-Temporal RADARSAT-2 and VEN\u00b5S Data for Crop Classification Based on 1D Convolutional Neural Network","display_name":"Synergistic Use of Multi-Temporal RADARSAT-2 and VEN\u00b5S Data for Crop Classification Based on 1D Convolutional Neural Network","publication_year":2020,"publication_date":"2020-03-04","ids":{"openalex":"https://openalex.org/W3009518842","doi":"https://doi.org/10.3390/rs12050832","mag":"3009518842"},"language":"en","primary_location":{"id":"doi:10.3390/rs12050832","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12050832","pdf_url":"https://www.mdpi.com/2072-4292/12/5/832/pdf?version=1583331495","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/2072-4292/12/5/832/pdf?version=1583331495","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021411883","display_name":"Chunhua Liao","orcid":"https://orcid.org/0000-0002-5504-206X"},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Chunhua Liao","raw_affiliation_strings":["Department of Geography, The University of Western Ontario, London, ON N6A 5C2, Canada"],"raw_orcid":"https://orcid.org/0000-0002-5504-206X","affiliations":[{"raw_affiliation_string":"Department of Geography, The University of Western Ontario, London, ON N6A 5C2, Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006022882","display_name":"Jinfei Wang","orcid":"https://orcid.org/0000-0002-8404-0530"},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Jinfei Wang","raw_affiliation_strings":["Department of Geography, The University of Western Ontario, London, ON N6A 5C2, Canada"],"raw_orcid":"https://orcid.org/0000-0002-8404-0530","affiliations":[{"raw_affiliation_string":"Department of Geography, The University of Western Ontario, London, ON N6A 5C2, Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082102192","display_name":"Qinghua Xie","orcid":"https://orcid.org/0000-0003-4293-3354"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinghua Xie","raw_affiliation_strings":["School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan 430074, China"],"raw_orcid":"https://orcid.org/0000-0003-4293-3354","affiliations":[{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan 430074, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038202213","display_name":"Ayman Al Baz","orcid":null},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ayman Al Baz","raw_affiliation_strings":["Department of Geography, The University of Western Ontario, London, ON N6A 5C2, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geography, The University of Western Ontario, London, ON N6A 5C2, Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016410509","display_name":"Xiaodong Huang","orcid":"https://orcid.org/0000-0002-3573-718X"},"institutions":[{"id":"https://openalex.org/I4210116398","display_name":"Applied GeoSolutions (United States)","ror":"https://ror.org/02gnmy268","country_code":"US","type":"company","lineage":["https://openalex.org/I4210116398"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaodong Huang","raw_affiliation_strings":["Applied Geosolutions, Durham, NH 03824, USA"],"raw_orcid":"https://orcid.org/0000-0002-3573-718X","affiliations":[{"raw_affiliation_string":"Applied Geosolutions, Durham, NH 03824, USA","institution_ids":["https://openalex.org/I4210116398"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083012711","display_name":"Jiali Shang","orcid":"https://orcid.org/0000-0001-9114-1500"},"institutions":[{"id":"https://openalex.org/I1331897569","display_name":"Agriculture and Agri-Food Canada","ror":"https://ror.org/051dzs374","country_code":"CA","type":"government","lineage":["https://openalex.org/I1331897569","https://openalex.org/I2802286613"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jiali Shang","raw_affiliation_strings":["Research Branch, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Branch, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada","institution_ids":["https://openalex.org/I1331897569"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000455378","display_name":"Yongjun He","orcid":"https://orcid.org/0000-0002-1656-560X"},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Yongjun He","raw_affiliation_strings":["Department of Geography, The University of Western Ontario, London, ON N6A 5C2, Canada"],"raw_orcid":"https://orcid.org/0000-0002-1656-560X","affiliations":[{"raw_affiliation_string":"Department of Geography, The University of Western Ontario, London, ON N6A 5C2, Canada","institution_ids":["https://openalex.org/I125749732"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5006022882"],"corresponding_institution_ids":["https://openalex.org/I125749732"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":6.5923,"has_fulltext":false,"cited_by_count":63,"citation_normalized_percentile":{"value":0.97193587,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"12","issue":"5","first_page":"832","last_page":"832"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9979000091552734,"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"}},"topics":[{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9979000091552734,"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"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9973999857902527,"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/support-vector-machine","display_name":"Support vector machine","score":0.6084704399108887},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5785127878189087},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5495827794075012},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.545301079750061},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5126370787620544},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4791128635406494},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44950002431869507},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.42551755905151367},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.414242684841156},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1670069396495819}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6084704399108887},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5785127878189087},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5495827794075012},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.545301079750061},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5126370787620544},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4791128635406494},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44950002431869507},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.42551755905151367},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.414242684841156},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1670069396495819}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs12050832","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12050832","pdf_url":"https://www.mdpi.com/2072-4292/12/5/832/pdf?version=1583331495","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:3bb7857aa1a34a1f8e88a957f8e29c1f","is_oa":false,"landing_page_url":"https://doaj.org/article/3bb7857aa1a34a1f8e88a957f8e29c1f","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 12, Iss 5, p 832 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/12/5/832/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs12050832","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 5; Pages: 832","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs12050832","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12050832","pdf_url":"https://www.mdpi.com/2072-4292/12/5/832/pdf?version=1583331495","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":[{"score":0.75,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"awards":[{"id":"https://openalex.org/G3940606240","display_name":null,"funder_award_id":"SOAR-E-5489","funder_id":"https://openalex.org/F4320334436","funder_display_name":"Canadian Space Agency"},{"id":"https://openalex.org/G4702098219","display_name":null,"funder_award_id":"IT11581","funder_id":"https://openalex.org/F4320322675","funder_display_name":"Mitacs"}],"funders":[{"id":"https://openalex.org/F4320322675","display_name":"Mitacs","ror":"https://ror.org/00cjrc276"},{"id":"https://openalex.org/F4320334436","display_name":"Canadian Space Agency","ror":"https://ror.org/03a1gte98"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W3009518842.pdf"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1985154454","https://openalex.org/W2014158985","https://openalex.org/W2032054003","https://openalex.org/W2041241239","https://openalex.org/W2064675550","https://openalex.org/W2078587853","https://openalex.org/W2078985447","https://openalex.org/W2095705004","https://openalex.org/W2097272115","https://openalex.org/W2136625467","https://openalex.org/W2140412267","https://openalex.org/W2161773957","https://openalex.org/W2166307050","https://openalex.org/W2247062920","https://openalex.org/W2278948991","https://openalex.org/W2295598076","https://openalex.org/W2342893289","https://openalex.org/W2594466018","https://openalex.org/W2604086375","https://openalex.org/W2606788270","https://openalex.org/W2619577109","https://openalex.org/W2783608381","https://openalex.org/W2789676998","https://openalex.org/W2886493749","https://openalex.org/W2896998982","https://openalex.org/W2897936062","https://openalex.org/W2899931790","https://openalex.org/W2903282641","https://openalex.org/W2903980171","https://openalex.org/W2918958705","https://openalex.org/W2921317791","https://openalex.org/W2929637356","https://openalex.org/W2963131120","https://openalex.org/W2982365707","https://openalex.org/W2986339177","https://openalex.org/W4239510810","https://openalex.org/W6631190155","https://openalex.org/W6674330103"],"related_works":["https://openalex.org/W4318664220","https://openalex.org/W2771047279","https://openalex.org/W4388409104","https://openalex.org/W2124951708","https://openalex.org/W1544811710","https://openalex.org/W4396689146","https://openalex.org/W4200112873","https://openalex.org/W2955796858","https://openalex.org/W2004826645","https://openalex.org/W4372048956"],"abstract_inverted_index":{"Annual":[0],"crop":[1,48,100,122,235],"inventory":[2],"information":[3,40],"is":[4,45],"important":[5],"for":[6,47,121,187,216],"many":[7],"agriculture":[8],"applications":[9],"and":[10,23,34,38,78,83,113,118,134,143,163,179,204,214,237,244],"government":[11],"statistics.":[12],"The":[13,56,176,208,223],"synergistic":[14],"use":[15],"of":[16,41,59,88,95,241,251],"multi-temporal":[17,74,116,155,242],"polarimetric":[18,39,76],"synthetic":[19],"aperture":[20],"radar":[21],"(SAR)":[22],"available":[24],"multispectral":[25,165],"remote":[26,80],"sensing":[27,81],"data":[28,120,157,166,194,246],"can":[29,247],"reduce":[30],"the":[31,36,42,86,93,126,148,151,154,170,192,196,212,227,238,249],"temporal":[32],"gaps":[33],"provide":[35],"spectral":[37],"crops,":[43],"which":[44],"effective":[46],"classification":[49,236],"in":[50,99,234],"areas":[51,72],"with":[52,125,191],"frequent":[53],"cloud":[54],"interference.":[55],"main":[57],"objectives":[58],"this":[60,103],"study":[61],"are":[62],"to":[63,69,84],"develop":[64],"a":[65,105,231],"deep":[66,96],"learning":[67,97,136],"model":[68],"map":[70],"agricultural":[71],"using":[73],"full":[75],"SAR":[77],"multi-spectral":[79],"data,":[82],"evaluate":[85],"influence":[87],"different":[89],"input":[90],"features":[91],"on":[92,115],"performance":[94,250],"methods":[98,137],"classification.":[101,123],"In":[102],"study,":[104],"one-dimensional":[106],"convolutional":[107],"neural":[108],"network":[109],"(Conv1D)":[110],"was":[111,221],"proposed":[112],"tested":[114],"RADARSAT-2":[117,156,243],"VEN\u00b5S":[119,164,193,245],"Compared":[124],"Multi-Layer":[127],"Perceptron":[128],"(MLP),":[129],"Recurrent":[130],"Neural":[131],"Network":[132],"(RNN)":[133],"non-deep":[135],"including":[138],"XGBoost,":[139],"Random":[140],"Forest":[141],"(RF),":[142],"Support":[144],"Vector":[145],"Machina":[146],"(SVM),":[147],"Conv1D":[149,188,220],"performed":[150],"best":[152],"when":[153,189,219],"(Pauli":[158],"decomposition":[159,178],"or":[160],"coherency":[161,180,228],"matrix)":[162],"were":[167],"fused":[168,190],"by":[169,195],"Minimum":[171],"Noise":[172],"Fraction":[173],"(MNF)":[174],"transformation.":[175],"Pauli":[177],"matrix":[181,229],"gave":[182],"similar":[183],"overall":[184],"accuracy":[185],"(OA)":[186],"MNF":[197,209,239],"transformation":[198,210,240],"(OA":[199],"=":[200],"96.65":[201],"\u00b1":[202,206],"1.03%":[203],"96.72":[205],"0.77%).":[207],"improved":[211],"OA":[213],"F-score":[215],"most":[217],"classes":[218],"used.":[222],"results":[224],"reveal":[225],"that":[226],"has":[230],"great":[232],"potential":[233],"enhance":[248],"Conv1D.":[252]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":1}],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2020-03-13T00:00:00"}