{"id":"https://openalex.org/W4296339277","doi":"https://doi.org/10.1109/jstars.2022.3206246","title":"Mapping Dongting Lake Wetland Utilizing Time Series Similarity, Statistical Texture, and Superpixels With Sentinel-1 SAR Data","display_name":"Mapping Dongting Lake Wetland Utilizing Time Series Similarity, Statistical Texture, and Superpixels With Sentinel-1 SAR Data","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4296339277","doi":"https://doi.org/10.1109/jstars.2022.3206246"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2022.3206246","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2022.3206246","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/4609444/09895353.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/4609443/4609444/09895353.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103152430","display_name":"Hui Yang","orcid":"https://orcid.org/0000-0003-1888-0985"},"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"]},{"id":"https://openalex.org/I4210164522","display_name":"Pingxiang University","ror":"https://ror.org/05j5de504","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210164522"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hui Yang","raw_affiliation_strings":["School of Geography and Information Engineering, China University of Geosciences, Wuhan, China","Pingxiang Institute of Planning, Survey and Design, PingXiang, China","School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]},{"raw_affiliation_string":"Pingxiang Institute of Planning, Survey and Design, PingXiang, China","institution_ids":["https://openalex.org/I4210164522"]},{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088181131","display_name":"Xiuguo Liu","orcid":"https://orcid.org/0000-0002-0045-9642"},"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":"Xiuguo Liu","raw_affiliation_strings":["School of Geography and Information Engineering, China University of Geosciences, Wuhan, China","School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]},{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074230887","display_name":"Qihao Chen","orcid":"https://orcid.org/0000-0002-7250-8781"},"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":"Qihao Chen","raw_affiliation_strings":["School of Geography and Information Engineering, China University of Geosciences, Wuhan, China","School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]},{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025927671","display_name":"Yuanye Cao","orcid":null},"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":"Yuanye Cao","raw_affiliation_strings":["School of Geography and Information Engineering, China University of Geosciences, Wuhan, China","School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]},{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103152430"],"corresponding_institution_ids":["https://openalex.org/I3124059619","https://openalex.org/I4210164522"],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":0.8813,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.71018413,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"15","issue":null,"first_page":"8235","last_page":"8244"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9879000186920166,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T13282","display_name":"Automated Road and Building Extraction","score":0.9879000186920166,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9839000105857849,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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/T10930","display_name":"Flood Risk Assessment and Management","score":0.9829000234603882,"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/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.6143608093261719},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6123318672180176},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5619513988494873},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5351622700691223},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5309967994689941},{"id":"https://openalex.org/keywords/wetland","display_name":"Wetland","score":0.4847569167613983},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45387569069862366},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.42815446853637695},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3787420392036438},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.21912792325019836},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09682369232177734},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.07587754726409912}],"concepts":[{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.6143608093261719},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6123318672180176},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5619513988494873},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5351622700691223},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5309967994689941},{"id":"https://openalex.org/C67715294","wikidata":"https://www.wikidata.org/wiki/Q170321","display_name":"Wetland","level":2,"score":0.4847569167613983},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45387569069862366},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42815446853637695},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3787420392036438},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.21912792325019836},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09682369232177734},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.07587754726409912},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2022.3206246","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2022.3206246","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/4609444/09895353.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:28e04f0dcf4842aca33405bf94688633","is_oa":true,"landing_page_url":"https://doaj.org/article/28e04f0dcf4842aca33405bf94688633","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":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 8235-8244 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2022.3206246","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2022.3206246","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/4609444/09895353.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Life in Land","score":0.5400000214576721,"id":"https://metadata.un.org/sdg/15"}],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2935570825","display_name":null,"funder_award_id":"41771467","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G37568934","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7726157001","display_name":null,"funder_award_id":"Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4296339277.pdf","grobid_xml":"https://content.openalex.org/works/W4296339277.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W2007689604","https://openalex.org/W2082374526","https://openalex.org/W2771249998","https://openalex.org/W2782438771","https://openalex.org/W2793659031","https://openalex.org/W2805775763","https://openalex.org/W2806676663","https://openalex.org/W2883315788","https://openalex.org/W2896389649","https://openalex.org/W2902380808","https://openalex.org/W2907459272","https://openalex.org/W2920176286","https://openalex.org/W2981318632","https://openalex.org/W2984877667","https://openalex.org/W2987438891","https://openalex.org/W2997283504","https://openalex.org/W2997968425","https://openalex.org/W3003630756","https://openalex.org/W3041479205","https://openalex.org/W3047155368","https://openalex.org/W3047968556","https://openalex.org/W3095173607","https://openalex.org/W3124459988","https://openalex.org/W3133321747","https://openalex.org/W3160584945","https://openalex.org/W3195404120","https://openalex.org/W3196547638","https://openalex.org/W3210019702","https://openalex.org/W3216355561","https://openalex.org/W4205905914","https://openalex.org/W4206085500","https://openalex.org/W4206420443","https://openalex.org/W4206609058","https://openalex.org/W4224438781"],"related_works":["https://openalex.org/W2381193838","https://openalex.org/W2383007022","https://openalex.org/W1995429609","https://openalex.org/W2367678540","https://openalex.org/W2376642692","https://openalex.org/W1992980705","https://openalex.org/W2119012848","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"Wetland":[0],"is":[1,7],"of":[2,39,69,86,123,173,182,222,225],"significant":[3],"ecological":[4],"value,":[5],"which":[6],"very":[8],"important":[9],"and":[10,36,73,91,114,149,157,175,179,186,198],"challenging":[11],"for":[12],"large-scale":[13],"mapping.":[14],"Sentinel-1":[15],"can":[16],"continuously":[17],"record":[18],"wetland":[19,72],"changes":[20],"with":[21,160,190,203],"its":[22],"all-day,":[23],"all-weather":[24],"working":[25],"capability.":[26],"How":[27],"to":[28,45,63,82,103,152],"fully":[29],"utilize":[30,144],"multidimensional":[31],"information,":[32],"such":[33],"as":[34],"time":[35],"statistical":[37,79,167],"texture":[38,80,84,168],"Synthetic":[40],"Aperture":[41],"Radar":[42],"(SAR)":[43],"image,":[44],"classify":[46],"wetlands":[47],"more":[48],"accurately":[49],"has":[50],"become":[51],"a":[52,95],"research":[53],"focus.":[54],"Thus,":[55],"this":[56],"paper":[57],"constructed":[58],"Time":[59,138],"Series":[60,139],"Similarity":[61,140],"parameters":[62,81],"describe":[64,83],"the":[65,115,135,171,177,216,223],"temporal":[66],"change":[67],"information":[68,146],"targets":[70],"in":[71,163,219],"introduced":[74,166],"G":[75],"<sup":[76],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[77],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">0</sup>":[78],"characteristics":[85],"SAR":[87,137],"images.":[88],"Combining":[89],"multi-features":[90],"superpixels,":[92],"we":[93],"proposed":[94,136],"classification":[96,110,121,200],"method":[97],"based":[98],"on":[99],"Random":[100],"Forest":[101],"(RF)":[102],"map":[104],"Dongting":[105],"Lake":[106],"wetland.":[107,164],"The":[108,120,132,165],"overall":[109],"accuracy":[111,122],"was":[112,118,129,150],"97.57%,":[113],"Kappa":[116],"coefficient":[117],"0.97.":[119],"reed":[124,158,187],"beach,":[125,184],"grass":[126,155],"marsh":[127,156],"etc.":[128],"above":[130],"95%.":[131],"results":[133],"showed":[134],"features":[141,169],"could":[142,213],"effectively":[143,214],"dynamical":[145],"among":[147],"classes":[148],"helpful":[151],"identify":[153],"mudflat,":[154],"beach":[159],"high":[161,209],"dynamics":[162],"expressed":[170],"heterogeneity":[172],"targets,":[174],"enhanced":[176],"recognition":[178],"extraction":[180],"ability":[181],"forest":[183],"mudflat":[185],"beach.":[188],"Compared":[189],"Support":[191],"Vector":[192],"Machine":[193],"(SVM),":[194],"Decision":[195],"Tree":[196],"(DT)":[197],"RF":[199,202],"methods,":[201],"superpixels":[204,226],"optimized":[205],"not":[206],"only":[207],"got":[208],"precision":[210],"but":[211],"also":[212],"reduce":[215],"pepper-salt":[217],"error":[218],"classification,":[220],"because":[221],"consideration":[224],"context":[227],"information.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}