{"id":"https://openalex.org/W4382936624","doi":"https://doi.org/10.3390/rs15133384","title":"Crop Type Mapping Based on Polarization Information of Time Series Sentinel-1 Images Using Patch-Based Neural Network","display_name":"Crop Type Mapping Based on Polarization Information of Time Series Sentinel-1 Images Using Patch-Based Neural Network","publication_year":2023,"publication_date":"2023-07-03","ids":{"openalex":"https://openalex.org/W4382936624","doi":"https://doi.org/10.3390/rs15133384"},"language":"en","primary_location":{"id":"doi:10.3390/rs15133384","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15133384","pdf_url":"https://www.mdpi.com/2072-4292/15/13/3384/pdf?version=1688376437","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/2072-4292/15/13/3384/pdf?version=1688376437","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100685984","display_name":"Yuying Liu","orcid":"https://orcid.org/0000-0002-1902-3742"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuying Liu","raw_affiliation_strings":["College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"],"affiliations":[{"raw_affiliation_string":"College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102530718","display_name":"Xuecong Pu","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuecong Pu","raw_affiliation_strings":["College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"],"affiliations":[{"raw_affiliation_string":"College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088730924","display_name":"Zhangquan Shen","orcid":"https://orcid.org/0000-0003-4286-773X"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhangquan Shen","raw_affiliation_strings":["College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"],"affiliations":[{"raw_affiliation_string":"College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5088730924"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":5.2775,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.95016239,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"15","issue":"13","first_page":"3384","last_page":"3384"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9987999796867371,"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"}},"topics":[{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9987999796867371,"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"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.989300012588501,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9889000058174133,"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":0.6380515694618225},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6083362102508545},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5391557216644287},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4966495633125305},{"id":"https://openalex.org/keywords/cohens-kappa","display_name":"Cohen's kappa","score":0.4878559112548828},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47595903277397156},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45486682653427124},{"id":"https://openalex.org/keywords/polarimetry","display_name":"Polarimetry","score":0.439736545085907},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42564791440963745},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4196498394012451},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2948552370071411},{"id":"https://openalex.org/keywords/scattering","display_name":"Scattering","score":0.13112184405326843},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.11911693215370178},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11835044622421265},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.11539000272750854}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6380515694618225},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6083362102508545},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5391557216644287},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4966495633125305},{"id":"https://openalex.org/C163864269","wikidata":"https://www.wikidata.org/wiki/Q1107106","display_name":"Cohen's kappa","level":2,"score":0.4878559112548828},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47595903277397156},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45486682653427124},{"id":"https://openalex.org/C28493345","wikidata":"https://www.wikidata.org/wiki/Q899381","display_name":"Polarimetry","level":3,"score":0.439736545085907},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42564791440963745},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4196498394012451},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2948552370071411},{"id":"https://openalex.org/C191486275","wikidata":"https://www.wikidata.org/wiki/Q210028","display_name":"Scattering","level":2,"score":0.13112184405326843},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.11911693215370178},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11835044622421265},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.11539000272750854},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs15133384","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15133384","pdf_url":"https://www.mdpi.com/2072-4292/15/13/3384/pdf?version=1688376437","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:b60ee22e12d04e8d88cf1a583edbac38","is_oa":true,"landing_page_url":"https://doaj.org/article/b60ee22e12d04e8d88cf1a583edbac38","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 13, p 3384 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/13/3384/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15133384","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 15; Issue 13; Pages: 3384","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs15133384","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15133384","pdf_url":"https://www.mdpi.com/2072-4292/15/13/3384/pdf?version=1688376437","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":"Zero hunger","id":"https://metadata.un.org/sdg/2","score":0.6200000047683716}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4382936624.pdf"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W1485009520","https://openalex.org/W1661523325","https://openalex.org/W1998281138","https://openalex.org/W2038622951","https://openalex.org/W2057343563","https://openalex.org/W2064675550","https://openalex.org/W2078985447","https://openalex.org/W2090314256","https://openalex.org/W2097272115","https://openalex.org/W2110242546","https://openalex.org/W2133989913","https://openalex.org/W2171688314","https://openalex.org/W2335925837","https://openalex.org/W2397355252","https://openalex.org/W2487649765","https://openalex.org/W2604086375","https://openalex.org/W2728388975","https://openalex.org/W2737391801","https://openalex.org/W2743142445","https://openalex.org/W2783608381","https://openalex.org/W2785681726","https://openalex.org/W2792827505","https://openalex.org/W2897656581","https://openalex.org/W2901719150","https://openalex.org/W2910478295","https://openalex.org/W2914237936","https://openalex.org/W2914272072","https://openalex.org/W2921359348","https://openalex.org/W2952411786","https://openalex.org/W2963391824","https://openalex.org/W2970680136","https://openalex.org/W3036016333","https://openalex.org/W3037002701","https://openalex.org/W3042854862","https://openalex.org/W3119404649","https://openalex.org/W3124539583","https://openalex.org/W3125947825","https://openalex.org/W3135196696","https://openalex.org/W3182299891","https://openalex.org/W3185030868","https://openalex.org/W3190941789","https://openalex.org/W3197307708","https://openalex.org/W3197824472","https://openalex.org/W3205560526","https://openalex.org/W6628852233","https://openalex.org/W6628877408","https://openalex.org/W6637210760","https://openalex.org/W6764455176","https://openalex.org/W6798911902","https://openalex.org/W7045993766"],"related_works":["https://openalex.org/W2026860918","https://openalex.org/W2035593284","https://openalex.org/W2225281849","https://openalex.org/W2612145225","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Large-scale":[0],"crop":[1,21,103,235],"mapping":[2,23],"is":[3,33],"of":[4,48,60,102,218],"fundamental":[5],"importance":[6],"to":[7,25,118,154,173,223,232],"tackle":[8],"food":[9],"security":[10],"problems.":[11],"SAR":[12,41],"remote":[13],"sensing":[14],"has":[15],"lately":[16],"received":[17],"great":[18],"attention":[19],"for":[20,85,132,185],"type":[22,104],"due":[24],"its":[26],"stability":[27],"in":[28,111,187,207,211],"the":[29,46,58,61,71,79,83,100,138,145,160,167,176,188,198,202,216],"revisit":[30],"cycle":[31],"and":[32,64,82,88,95,108,128,151,156,159,162,169,197,209,226],"not":[34],"hindered":[35],"by":[36,76,205],"cloud":[37],"cover.":[38],"However,":[39],"most":[40],"image-classification":[42],"studies":[43],"focused":[44],"on":[45],"application":[47],"backscattering":[49],"characteristics":[50],"with":[51,148],"machine":[52],"learning":[53],"models,":[54],"while":[55],"few":[56],"investigated":[57,69],"potential":[59],"polarization":[62,73,77,177,220],"decomposition":[63,178,221],"deep-learning":[65,224],"models.":[66],"This":[67,213],"study":[68,214],"whether":[70],"radar":[72],"information":[74,184],"mined":[75],"decomposition,":[78],"patch":[80,193],"strategy":[81],"approaches":[84],"combining":[86],"recurrent":[87],"convolutional":[89],"neural":[90],"networks":[91],"(Conv2d":[92],"+":[93,124,164],"LSTM":[94,165],"ConvLSTM2d)":[96],"could":[97,180],"effectively":[98],"improve":[99],"accuracy":[101,150,208],"mapping.":[105,236],"Sentinel-1":[106],"SLC":[107],"GRD":[109],"products":[110],"2020":[112],"were":[113],"collected":[114],"as":[115],"data":[116],"sources":[117],"extract":[119],"VH,":[120,125],"VV,":[121],"VH/VV,":[122],"VV":[123],"Entropy,":[126],"Anisotropy,":[127],"Alpha":[129],"7-dimensional":[130],"features":[131,179,222],"classification.":[133],"The":[134,191],"results":[135],"showed":[136],"that":[137],"three-dimensional":[139],"Convolutional":[140],"Neural":[141],"Network":[142],"(Conv3d)":[143],"was":[144,195],"best":[146],"classifier":[147],"an":[149],"kappa":[152],"up":[153],"88.9%":[155],"0.875,":[157],"respectively,":[158],"ConvLSTM2d":[161],"Conv2d":[163],"achieved":[166],"second":[168],"third":[170],"position.":[171],"Compared":[172],"backscatter":[174],"coefficients,":[175],"provide":[181],"additional":[182],"phase":[183],"classification":[186],"time":[189],"dimension.":[190],"optimal":[192],"size":[194],"17,":[196],"patch-based":[199],"Conv3d":[200],"outperformed":[201],"pixel-based":[203],"Conv1d":[204],"11.3%":[206],"0.128":[210],"kappa.":[212],"demonstrated":[215],"value":[217],"applying":[219],"models":[225],"provided":[227],"a":[228],"strong":[229],"technical":[230],"support":[231],"efficient":[233],"large-scale":[234]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2023-07-04T00:00:00"}
