{"id":"https://openalex.org/W4387803619","doi":"https://doi.org/10.1109/igarss52108.2023.10282518","title":"Detection of Flood Area Caused by Typhoon Hagibis Using Learning-Based Method with Sentinel-1 Data","display_name":"Detection of Flood Area Caused by Typhoon Hagibis Using Learning-Based Method with Sentinel-1 Data","publication_year":2023,"publication_date":"2023-07-16","ids":{"openalex":"https://openalex.org/W4387803619","doi":"https://doi.org/10.1109/igarss52108.2023.10282518"},"language":"en","primary_location":{"id":"doi:10.1109/igarss52108.2023.10282518","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss52108.2023.10282518","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 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/A5018049781","display_name":"Takahiro Igarashi","orcid":"https://orcid.org/0009-0002-6654-9007"},"institutions":[{"id":"https://openalex.org/I104946051","display_name":"Nihon University","ror":"https://ror.org/05jk51a88","country_code":"JP","type":"education","lineage":["https://openalex.org/I104946051"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Takahiro Igarashi","raw_affiliation_strings":["Nihon University,Graduate School of Engineering,Koriyama,Japan,963-8642"],"affiliations":[{"raw_affiliation_string":"Nihon University,Graduate School of Engineering,Koriyama,Japan,963-8642","institution_ids":["https://openalex.org/I104946051"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018544723","display_name":"Hiroyuki Wakabayashi","orcid":"https://orcid.org/0000-0002-2243-0314"},"institutions":[{"id":"https://openalex.org/I104946051","display_name":"Nihon University","ror":"https://ror.org/05jk51a88","country_code":"JP","type":"education","lineage":["https://openalex.org/I104946051"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroyuki Wakabayashi","raw_affiliation_strings":["Nihon University,College of Engineering,Koriyama,Japan,963-8642"],"affiliations":[{"raw_affiliation_string":"Nihon University,College of Engineering,Koriyama,Japan,963-8642","institution_ids":["https://openalex.org/I104946051"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5018049781"],"corresponding_institution_ids":["https://openalex.org/I104946051"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.142821,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":null,"first_page":"7202","last_page":"7205"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10930","display_name":"Flood Risk Assessment and Management","score":0.9775000214576721,"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"}},"topics":[{"id":"https://openalex.org/T10930","display_name":"Flood Risk Assessment and Management","score":0.9775000214576721,"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"}},{"id":"https://openalex.org/T11483","display_name":"Tropical and Extratropical Cyclones Research","score":0.954200029373169,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9520000219345093,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/typhoon","display_name":"Typhoon","score":0.910694420337677},{"id":"https://openalex.org/keywords/flood-myth","display_name":"Flood myth","score":0.7614264488220215},{"id":"https://openalex.org/keywords/flooding","display_name":"Flooding (psychology)","score":0.7102065086364746},{"id":"https://openalex.org/keywords/paddy-field","display_name":"Paddy field","score":0.6786050796508789},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.6172127723693848},{"id":"https://openalex.org/keywords/hydrology","display_name":"Hydrology (agriculture)","score":0.44486573338508606},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.43290841579437256},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.41312843561172485},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.2767772078514099},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.22965112328529358},{"id":"https://openalex.org/keywords/geotechnical-engineering","display_name":"Geotechnical engineering","score":0.18488141894340515},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.15609106421470642},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.13987082242965698},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.13427338004112244}],"concepts":[{"id":"https://openalex.org/C181654704","wikidata":"https://www.wikidata.org/wiki/Q140588","display_name":"Typhoon","level":2,"score":0.910694420337677},{"id":"https://openalex.org/C74256435","wikidata":"https://www.wikidata.org/wiki/Q134052","display_name":"Flood myth","level":2,"score":0.7614264488220215},{"id":"https://openalex.org/C186594467","wikidata":"https://www.wikidata.org/wiki/Q1429176","display_name":"Flooding (psychology)","level":2,"score":0.7102065086364746},{"id":"https://openalex.org/C85582077","wikidata":"https://www.wikidata.org/wiki/Q842623","display_name":"Paddy field","level":2,"score":0.6786050796508789},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.6172127723693848},{"id":"https://openalex.org/C76886044","wikidata":"https://www.wikidata.org/wiki/Q2883300","display_name":"Hydrology (agriculture)","level":2,"score":0.44486573338508606},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.43290841579437256},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.41312843561172485},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.2767772078514099},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.22965112328529358},{"id":"https://openalex.org/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.18488141894340515},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.15609106421470642},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.13987082242965698},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.13427338004112244},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss52108.2023.10282518","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss52108.2023.10282518","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.44999998807907104}],"awards":[],"funders":[{"id":"https://openalex.org/F4320325182","display_name":"Chiba University","ror":"https://ror.org/01hjzeq58"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1490653832","https://openalex.org/W1993345130","https://openalex.org/W2005779189","https://openalex.org/W2044465660","https://openalex.org/W2063907334","https://openalex.org/W2074504304","https://openalex.org/W2122166205","https://openalex.org/W2138002125","https://openalex.org/W2153635508","https://openalex.org/W2156606791","https://openalex.org/W2292718396","https://openalex.org/W2462089918","https://openalex.org/W2771197060","https://openalex.org/W2793927960","https://openalex.org/W2910355480","https://openalex.org/W2910531141","https://openalex.org/W2943433165","https://openalex.org/W4239510810","https://openalex.org/W4313139018"],"related_works":["https://openalex.org/W2322294131","https://openalex.org/W4377023816","https://openalex.org/W2381913349","https://openalex.org/W3125308484","https://openalex.org/W4392617234","https://openalex.org/W2368202014","https://openalex.org/W2044728225","https://openalex.org/W2001663785","https://openalex.org/W2031888665","https://openalex.org/W2923835640"],"abstract_inverted_index":{"Typhoon":[0,77],"Hagibis":[1],"hit":[2],"Koriyama":[3,73],"City":[4,74],"in":[5,31,46,64,72,99,103,112,121,133,146],"Fukushima":[6],"Prefecture,":[7],"Japan,":[8],"on":[9],"October":[10],"13,":[11],"2019.":[12],"The":[13,92,108],"outflow":[14],"of":[15,157],"the":[16,32,37,60,97,100,113,126,129,155,162,170,183,190],"rivers,":[17],"such":[18],"as":[19,175],"Abukuma,":[20],"Sasahara,":[21],"Yata,":[22],"and":[23,68,89,105,149],"Ouse,":[24],"caused":[25,39,75],"flood":[26,38,163],"damage":[27,40],"to":[28,41,58,83,95,143],"built-up":[29,66,114,147],"areas":[30,67,148],"city":[33],"center.":[34],"In":[35],"addition,":[36],"rice":[42,47,69,134,150],"production":[43],"because":[44],"flooding":[45,145],"paddies":[48],"happened":[49],"just":[50],"before":[51],"harvest":[52],"time.":[53],"Our":[54],"research":[55],"objective":[56,93],"is":[57,94],"clarify":[59],"Sentinel-1":[61,84],"backscattering":[62,101,109,130,167],"change":[63,168],"inundated":[65],"paddy":[70,135,151],"fields":[71,152],"by":[76,153,186],"Hagibis.":[78],"Backscattering":[79],"analysis":[80],"was":[81,119],"applied":[82,139],"data":[85],"acquired":[86],"before,":[87],"during,":[88],"after":[90],"flooding.":[91],"find":[96],"difference":[98],"coefficient":[102,110,131],"non-flood":[104],"flooded":[106],"areas.":[107],"increases":[111],"area":[115],"during":[116],"flooding,":[117],"which":[118],"significant":[120],"a":[122,140,176],"residential":[123],"area.":[124],"On":[125],"other":[127],"hand,":[128],"decreases":[132],"fields.":[136],"We":[137,160],"also":[138],"learning-based":[141],"method":[142],"detect":[144],"using":[154,166],"results":[156],"this":[158],"study.":[159],"evaluated":[161],"detection":[164,184],"accuracy":[165,185],"with":[169],"support":[171],"vector":[172],"machine":[173],"(SVM)":[174],"classifier.":[177],"Furthermore,":[178],"adding":[179],"texture":[180],"information":[181],"improved":[182],"about":[187],"0.15":[188],"for":[189],"Kappa":[191],"coefficient.":[192]},"counts_by_year":[],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}