{"id":"https://openalex.org/W2989109473","doi":"https://doi.org/10.1109/igarss.2019.8897922","title":"A Semi-Supervised Crop-Type Classification Based on Sentinel-2 NDVI Satellite Image Time Series And Phenological Parameters","display_name":"A Semi-Supervised Crop-Type Classification Based on Sentinel-2 NDVI Satellite Image Time Series And Phenological Parameters","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2989109473","doi":"https://doi.org/10.1109/igarss.2019.8897922","mag":"2989109473"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2019.8897922","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8897922","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024342243","display_name":"Yady Tatiana Solano\u2010Correa","orcid":"https://orcid.org/0000-0002-4867-1837"},"institutions":[{"id":"https://openalex.org/I2277624104","display_name":"Fondazione Bruno Kessler","ror":"https://ror.org/01j33xk10","country_code":"IT","type":"facility","lineage":["https://openalex.org/I2277624104"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Yady Tatiana Solano-Correa","raw_affiliation_strings":["Center for Information and Communication Technology, Fondazione Bruno Kessler, Trento, Italy"],"affiliations":[{"raw_affiliation_string":"Center for Information and Communication Technology, Fondazione Bruno Kessler, Trento, Italy","institution_ids":["https://openalex.org/I2277624104"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087668203","display_name":"Francesca Bovolo","orcid":"https://orcid.org/0000-0003-3104-7656"},"institutions":[{"id":"https://openalex.org/I2277624104","display_name":"Fondazione Bruno Kessler","ror":"https://ror.org/01j33xk10","country_code":"IT","type":"facility","lineage":["https://openalex.org/I2277624104"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Francesca Bovolo","raw_affiliation_strings":["Center for Information and Communication Technology, Fondazione Bruno Kessler, Trento, Italy"],"affiliations":[{"raw_affiliation_string":"Center for Information and Communication Technology, Fondazione Bruno Kessler, Trento, Italy","institution_ids":["https://openalex.org/I2277624104"]}]},{"author_position":"last","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":["Dept. of Information Engineering and Computer Science, University of Trento, Trento, Italy"],"affiliations":[{"raw_affiliation_string":"Dept. of Information Engineering and Computer Science, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5024342243"],"corresponding_institution_ids":["https://openalex.org/I2277624104"],"apc_list":null,"apc_paid":null,"fwci":2.5924,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.89568606,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"457","last_page":"460"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.998199999332428,"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":0.998199999332428,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9868000149726868,"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"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.984000027179718,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6746445894241333},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5963560342788696},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.5257866382598877},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.485980361700058},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47821304202079773},{"id":"https://openalex.org/keywords/normalized-difference-vegetation-index","display_name":"Normalized Difference Vegetation Index","score":0.4721634089946747},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4708024263381958},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4701020121574402},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4696098268032074},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4647575616836548},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4470345079898834},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44125375151634216},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4078989624977112},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3889278173446655},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.15901273488998413}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6746445894241333},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5963560342788696},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.5257866382598877},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.485980361700058},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47821304202079773},{"id":"https://openalex.org/C1549246","wikidata":"https://www.wikidata.org/wiki/Q718775","display_name":"Normalized Difference Vegetation Index","level":3,"score":0.4721634089946747},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4708024263381958},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4701020121574402},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4696098268032074},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4647575616836548},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4470345079898834},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44125375151634216},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4078989624977112},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3889278173446655},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.15901273488998413},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C25989453","wikidata":"https://www.wikidata.org/wiki/Q446746","display_name":"Leaf area index","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"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:10.1109/igarss.2019.8897922","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8897922","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:iris.unitn.it:11572/247218","is_oa":false,"landing_page_url":"http://hdl.handle.net/11572/247218","pdf_url":null,"source":{"id":"https://openalex.org/S4306401913","display_name":"Institutional Research Information System (Universit\u00e0 degli Studi di 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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2042645898","https://openalex.org/W2151978020","https://openalex.org/W2307094448","https://openalex.org/W2755284214","https://openalex.org/W2767953525","https://openalex.org/W2901960267","https://openalex.org/W2913633272","https://openalex.org/W4302190632"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2803445926"],"abstract_inverted_index":{"Crop-type":[0,137],"classification":[1,46,138],"has":[2],"been":[3],"attracting":[4],"a":[5,24,66,105,110],"lot":[6],"of":[7,17,27,52,74,104,122],"attention":[8],"in":[9,47,71,94,134],"recent":[10],"years.":[11],"In":[12,37],"particular":[13],"since":[14],"the":[15,18,38,123],"launch":[16],"Sentinel-2":[19],"(S2)":[20],"satellite":[21,35],"which":[22],"combines":[23],"large":[25],"amount":[26],"spectral":[28],"and":[29,86,90,98,101],"spatial":[30,89],"information,":[31],"compared":[32,140],"to":[33,141],"previous":[34],"generations.":[36],"literature,":[39],"several":[40],"methods":[41],"exist":[42],"that":[43,82],"perform":[44,60],"crop":[45],"time":[48,96],"series,":[49],"but":[50],"most":[51],"them:":[53],"i)":[54],"work":[55],"at":[56,84],"pixel":[57],"level;":[58],"ii)":[59],"single-data":[61],"analysis;":[62],"and/or":[63],"iii)":[64],"consider":[65],"single":[67],"feature.":[68],"This":[69,77],"results":[70],"low":[72],"performance":[73],"state-of-the-art":[75,142],"methods.":[76,143],"paper":[78],"presents":[79],"an":[80,116,129],"approach":[81,125],"works":[83],"object-level":[85],"exploits":[87],"both":[88],"temporal":[91],"information":[92],"coded":[93],"NDVI":[95],"series":[97],"phenological":[99],"parameters":[100],"takes":[102],"advantage":[103],"semi-supervised":[106],"paradigm":[107],"by":[108],"combining":[109],"new":[111],"hierarchical":[112],"correlation":[113],"clustering":[114],"with":[115],"artificial":[117],"neural":[118],"network.":[119],"The":[120],"effectiveness":[121],"proposed":[124],"was":[126,139],"corroborated":[127],"over":[128],"intensive":[130],"cultivated":[131],"area":[132],"located":[133],"Barrax,":[135],"Spain.":[136]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":7}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
