{"@context":{"@vocab":"https://cir.nii.ac.jp/schema/1.0/","rdfs":"http://www.w3.org/2000/01/rdf-schema#","dc":"http://purl.org/dc/elements/1.1/","dcterms":"http://purl.org/dc/terms/","foaf":"http://xmlns.com/foaf/0.1/","prism":"http://prismstandard.org/namespaces/basic/2.0/","cinii":"http://ci.nii.ac.jp/ns/1.0/","datacite":"https://schema.datacite.org/meta/kernel-4/","ndl":"http://ndl.go.jp/dcndl/terms/","jpcoar":"https://github.com/JPCOAR/schema/blob/master/2.0/"},"@id":"https://cir.nii.ac.jp/crid/1360848656344801664.json","@type":"Article","productIdentifier":[{"identifier":{"@type":"DOI","@value":"10.1007/s11069-010-9638-y"}},{"identifier":{"@type":"URI","@value":"http://link.springer.com/content/pdf/10.1007/s11069-010-9638-y.pdf"}},{"identifier":{"@type":"URI","@value":"http://link.springer.com/article/10.1007/s11069-010-9638-y/fulltext.html"}},{"identifier":{"@type":"URI","@value":"http://link.springer.com/content/pdf/10.1007/s11069-010-9638-y"}}],"resourceType":"学術雑誌論文(journal article)","dc:title":[{"@value":"Flood monitoring, mapping and assessing capabilities using RADARSAT remote sensing, GIS and ground data for Bangladesh"}],"description":[{"notation":[{"@value":"Remote sensing is the most practical method available to managers of flood-prone areas for quantifying and mapping flood impacts. This study explored large inundation areas in the Maghna River Basin, around the northeastern Bangladesh, as determined from passive sensor LANDSAT data and the cloud-penetrating capabilities of the active sensors of the remote imaging microwave RADARSAT. This study also used passive sensor LANDSAT wet and dry images for the year 2000. Spatial resolution was 30 m by 30 m for comparisons of the inundation area with RADARSAT images. RADARSAT images with spatial resolution of 50 m by 50 m were used for frequency analysis of floods from 2000 to 2004. Time series images for 2004 were also used. RADARSAT remote sensing data, GIS data, and ground data were used for the purpose of flood monitoring, mapping and assessing. A supervised classification technique was used for this processing. They were processed for creating a maximum water extent map and for estimating inundation areas. The results of this study indicated that the maximum extent of the inundation area as estimated using RADARSAT satellite imaging was about 29, 900.72 km2 in 2004, which corresponded well with the heavy rainfall around northeast region, as seen at the Bhairab Bazar station and with the highest water level of the Ganges–Brahmaputra–Meghna (GBM) Rivers. A composite of 5 years of RADARSAT inundation maps from 2000 to 2004, GIS data, and damage data, was used to create unique flood hazard maps. Using the damage data for 2004 and the GIS data, a set of damage maps was also created. These maps are expected to be useful for future planning and flood disaster management. Thus, it has been demonstrated that RADARSAT imaging data acquired over the Bangladesh have the ability to precisely assess and clarify inundation areas allowing for successful flood monitoring, mapping and disaster management."}]}],"creator":[{"@id":"https://cir.nii.ac.jp/crid/1380848656344801670","@type":"Researcher","foaf:name":[{"@value":"Roxana Hoque"}]},{"@id":"https://cir.nii.ac.jp/crid/1380848656344801676","@type":"Researcher","foaf:name":[{"@value":"Daichi Nakayama"}]},{"@id":"https://cir.nii.ac.jp/crid/1380848656344801675","@type":"Researcher","foaf:name":[{"@value":"Hiroshi Matsuyama"}]},{"@id":"https://cir.nii.ac.jp/crid/1380848656344801674","@type":"Researcher","foaf:name":[{"@value":"Jun Matsumoto"}]}],"publication":{"publicationIdentifier":[{"@type":"PISSN","@value":"0921030X"},{"@type":"EISSN","@value":"15730840"}],"prism:publicationName":[{"@value":"Natural Hazards"}],"dc:publisher":[{"@value":"Springer Science and Business Media LLC"}],"prism:publicationDate":"2010-10-20","prism:volume":"57","prism:number":"2","prism:startingPage":"525","prism:endingPage":"548"},"reviewed":"false","dc:rights":["http://www.springer.com/tdm"],"url":[{"@id":"http://link.springer.com/content/pdf/10.1007/s11069-010-9638-y.pdf"},{"@id":"http://link.springer.com/article/10.1007/s11069-010-9638-y/fulltext.html"},{"@id":"http://link.springer.com/content/pdf/10.1007/s11069-010-9638-y"}],"createdAt":"2010-10-18","modifiedAt":"2019-06-05","project":[{"@id":"https://cir.nii.ac.jp/crid/1040000782066817664","@type":"Project","projectIdentifier":[{"@type":"KAKEN","@value":"21251005"},{"@type":"JGN","@value":"JP21251005"},{"@type":"URI","@value":"https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-21251005/"}],"notation":[{"@language":"ja","@value":"ベンガル湾縁辺における自然災害との共生を目指した在地のネットワーク型国際共同研究"},{"@language":"en","@value":"International Networking Project to Cope with Natural Hazards on the Periphery of Bengal Bay"}]}],"relatedProduct":[{"@id":"https://cir.nii.ac.jp/crid/1360002215353033472","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"Assessing the degree of flood damage to rice crops in the Chao Phraya delta, Thailand, using MODIS satellite imaging"}]},{"@id":"https://cir.nii.ac.jp/crid/1360285715177016704","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"Review article: Detection of inundation areas due to the  2015 Kanto and Tohoku torrential rain in Japan based  on multi-temporal ALOS-2 imagery"}]},{"@id":"https://cir.nii.ac.jp/crid/1360292619139625856","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Estimating the extent of floods in Bangladesh using SPOT 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