{"id":"https://openalex.org/W4223547253","doi":"https://doi.org/10.3390/rs14081825","title":"A Self-Trained Model for Cloud, Shadow and Snow Detection in Sentinel-2 Images of Snow- and Ice-Covered Regions","display_name":"A Self-Trained Model for Cloud, Shadow and Snow Detection in Sentinel-2 Images of Snow- and Ice-Covered Regions","publication_year":2022,"publication_date":"2022-04-10","ids":{"openalex":"https://openalex.org/W4223547253","doi":"https://doi.org/10.3390/rs14081825"},"language":"en","primary_location":{"id":"doi:10.3390/rs14081825","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14081825","pdf_url":"https://www.mdpi.com/2072-4292/14/8/1825/pdf?version=1650351855","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/2072-4292/14/8/1825/pdf?version=1650351855","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077503279","display_name":"Kamal Gopikrishnan Nambiar","orcid":"https://orcid.org/0000-0002-5840-4935"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Kamal Gopikrishnan Nambiar","raw_affiliation_strings":["Chair of Multimedia Communications and Signal Processing, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, 91054 Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Chair of Multimedia Communications and Signal Processing, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, 91054 Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059061090","display_name":"Veniamin I. Morgenshtern","orcid":"https://orcid.org/0000-0002-3565-7788"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Veniamin I. Morgenshtern","raw_affiliation_strings":["Chair of Multimedia Communications and Signal Processing, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, 91054 Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Chair of Multimedia Communications and Signal Processing, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, 91054 Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021805902","display_name":"Philipp Hochreuther","orcid":"https://orcid.org/0000-0001-7780-1525"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Philipp Hochreuther","raw_affiliation_strings":["Institute of Geography, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, 91054 Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Geography, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, 91054 Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066538856","display_name":"Thorsten Seehaus","orcid":"https://orcid.org/0000-0001-5055-8959"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Thorsten Seehaus","raw_affiliation_strings":["Institute of Geography, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, 91054 Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Geography, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, 91054 Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077777079","display_name":"Matthias Braun","orcid":"https://orcid.org/0000-0001-5169-1567"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Matthias Holger Braun","raw_affiliation_strings":["Institute of Geography, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, 91054 Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Geography, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, 91054 Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5059061090"],"corresponding_institution_ids":["https://openalex.org/I181369854"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":1341,"currency":"EUR","value_usd":1446},"fwci":3.3954,"has_fulltext":true,"cited_by_count":27,"citation_normalized_percentile":{"value":0.92655084,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"14","issue":"8","first_page":"1825","last_page":"1825"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10644","display_name":"Cryospheric studies and observations","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10644","display_name":"Cryospheric studies and observations","score":0.9997000098228455,"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/T10466","display_name":"Meteorological Phenomena and Simulations","score":0.9923999905586243,"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/T10930","display_name":"Flood Risk Assessment and Management","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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":0.8006104230880737},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6453148126602173},{"id":"https://openalex.org/keywords/unavailability","display_name":"Unavailability","score":0.5993168354034424},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5397515892982483},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.47429683804512024},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45945626497268677},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.4509741961956024},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.41380494832992554},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3441469669342041},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.12093320488929749},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.08541169762611389}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8006104230880737},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6453148126602173},{"id":"https://openalex.org/C2780505938","wikidata":"https://www.wikidata.org/wiki/Q17093282","display_name":"Unavailability","level":2,"score":0.5993168354034424},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5397515892982483},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.47429683804512024},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45945626497268677},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.4509741961956024},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.41380494832992554},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3441469669342041},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.12093320488929749},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.08541169762611389},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/rs14081825","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14081825","pdf_url":"https://www.mdpi.com/2072-4292/14/8/1825/pdf?version=1650351855","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:a8bc1f90e526433aaa0eafd07ecafa6c","is_oa":true,"landing_page_url":"https://doaj.org/article/a8bc1f90e526433aaa0eafd07ecafa6c","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 14, Iss 8, p 1825 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/8/1825/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14081825","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 14; Issue 8; Pages: 1825","raw_type":"Text"},{"id":"pmh:oai:ub.uni-erlangen.de-opus:19214","is_oa":true,"landing_page_url":"https://nbn-resolving.org/urn:nbn:de:bvb:29-opus4-192140","pdf_url":null,"source":{"id":"https://openalex.org/S4306401636","display_name":"OPUS Repository (Kooperativer Bibliotheksverbund Berlin-Brandenburg)","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs14081825","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14081825","pdf_url":"https://www.mdpi.com/2072-4292/14/8/1825/pdf?version=1650351855","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":[],"awards":[{"id":"https://openalex.org/G8330397625","display_name":null,"funder_award_id":"Funding","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320318240","display_name":"European Space Agency","ror":"https://ror.org/03wd9za21"},{"id":"https://openalex.org/F4320320873","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57"},{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4223547253.pdf","grobid_xml":"https://content.openalex.org/works/W4223547253.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1905829557","https://openalex.org/W1936750108","https://openalex.org/W1997887332","https://openalex.org/W2017209939","https://openalex.org/W2022106079","https://openalex.org/W2025745000","https://openalex.org/W2028240797","https://openalex.org/W2066633241","https://openalex.org/W2109020989","https://openalex.org/W2166251851","https://openalex.org/W2460672227","https://openalex.org/W2463021868","https://openalex.org/W2480078828","https://openalex.org/W2517986957","https://openalex.org/W2583993537","https://openalex.org/W2584156879","https://openalex.org/W2600148249","https://openalex.org/W2605847660","https://openalex.org/W2734629852","https://openalex.org/W2748715875","https://openalex.org/W2802828972","https://openalex.org/W2810069315","https://openalex.org/W2908549901","https://openalex.org/W2914757358","https://openalex.org/W2914834436","https://openalex.org/W2917440533","https://openalex.org/W2923782278","https://openalex.org/W2946072066","https://openalex.org/W2950314938","https://openalex.org/W2982640424","https://openalex.org/W2985601188","https://openalex.org/W3035003500","https://openalex.org/W3035160371","https://openalex.org/W3039086093","https://openalex.org/W3080368312","https://openalex.org/W3100944043","https://openalex.org/W3110002552","https://openalex.org/W3153500217","https://openalex.org/W3173374491","https://openalex.org/W4206767072","https://openalex.org/W4255029902","https://openalex.org/W6639824700","https://openalex.org/W6735132182","https://openalex.org/W6793632581","https://openalex.org/W6797150090","https://openalex.org/W6807204952"],"related_works":["https://openalex.org/W1841747458","https://openalex.org/W2790662084","https://openalex.org/W2960184797","https://openalex.org/W4285827401","https://openalex.org/W3104734424","https://openalex.org/W4226289457","https://openalex.org/W2954384599","https://openalex.org/W3209779739","https://openalex.org/W2738221750","https://openalex.org/W3134595075"],"abstract_inverted_index":{"Screening":[0],"clouds,":[1],"shadows,":[2],"and":[3,24,44,82,109,191,197],"snow":[4],"is":[5,120],"a":[6,59,65,83,99,111,129],"critical":[7],"pre-processing":[8],"step":[9],"in":[10,42,103,139,150],"many":[11],"remote-sensing":[12,210],"data":[13,21],"processing":[14],"pipelines":[15],"that":[16,30,63],"operate":[17],"on":[18,71,164],"satellite":[19],"image":[20],"from":[22],"polar":[23,43],"high":[25,45],"mountain":[26,46],"regions.":[27,47],"We":[28,143,200],"observe":[29],"the":[31,34,49,76,93,106,137,140,145,155,165,175,188],"results":[32],"of":[33,51,92,184],"state-of-the-art":[35],"Fmask":[36,78,189],"algorithm":[37],"are":[38,133],"not":[39],"very":[40],"accurate":[41],"Given":[48],"unavailability":[50],"large,":[52],"labeled":[53],"Sentinel-2":[54,72],"training":[55,81,126,136,149,213],"datasets,":[56],"we":[57,97],"present":[58],"multi-stage":[60],"self-training":[61],"approach":[62,203],"trains":[64],"model":[66,116,138,147,179],"to":[67,105,123,173,187],"perform":[68],"semantic":[69],"segmentation":[70,157],"L1C":[73],"images":[74],"using":[75],"noisy":[77,176],"labels":[79,127],"for":[80,87,128,135,208,212],"small":[84,166],"human-labeled":[85,167],"dataset":[86],"validation.":[88],"At":[89],"each":[90,118,151],"stage":[91,108,119,152],"proposed":[94],"iterative":[95],"framework,":[96],"use":[98],"larger":[100],"network":[101],"architecture":[102],"comparison":[104],"previous":[107],"train":[110],"new":[112,125],"model.":[113],"The":[114],"trained":[115],"at":[117],"then":[121],"used":[122,134],"generate":[124],"bigger":[130],"dataset,":[131],"which":[132,194],"next":[141],"stage.":[142],"select":[144],"best":[146],"during":[148],"by":[153],"evaluating":[154],"multi-class":[156],"metric,":[158],"mean":[159],"Intersection":[160],"over":[161],"Union":[162],"(mIoU),":[163],"validation":[168],"dataset.":[169],"This":[170],"effectively":[171],"helps":[172],"correct":[174],"labels.":[177,218],"Our":[178],"achieved":[180,195],"an":[181],"overall":[182],"accuracy":[183],"93%":[185],"compared":[186],"4":[190],"Sen2Cor":[192],"2.8,":[193],"75%":[196],"76%,":[198],"respectively.":[199],"believe":[201],"our":[202],"can":[204],"also":[205],"be":[206],"adapted":[207],"other":[209],"applications":[211],"deep-learning":[214],"models":[215],"with":[216],"imprecise":[217]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}