Rapid flood inundation mapping by differencing water indices from pre- and post-flood Landsat images
Following flooding disasters, satellite images provide valuable information required for generating flood inundation maps. Multispectral or optical imagery can be used for generating flood maps when the inundated areas are not covered by clouds. We propose a rapid mapping method for identifying inun...
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Veröffentlicht in: | Frontiers of earth science 2021-03, Vol.15 (1), p.1-11 |
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description | Following flooding disasters, satellite images provide valuable information required for generating flood inundation maps. Multispectral or optical imagery can be used for generating flood maps when the inundated areas are not covered by clouds. We propose a rapid mapping method for identifying inundated areas based on the increase in the water index value between the pre- and post-flood satellite images. Values of the Normalized Difference Water Index ( NDWI) and Modified NDWI ( MNDWI) will be higher in the post-flood image for flooded areas compared to the pre-flood image. Based on a threshold value, pixels corresponding to the flooded areas can be separated from non-flooded areas. Inundation maps derived from differencing MNDWI values accurately captured the flooded areas. However the output image will be influenced by the choice of the pre-flood image, hence analysts have to avoid selecting pre-flood images acquired in drought or earlier flood years. Also the inundation maps generated using this method have to be overlaid on the post-flood satellite image in order to orient personnel to landscape features. Advantages of the proposed technique are that flood impacted areas can be identified rapidly, and that the pre-existing water bodies can be excluded from the inundation maps. Using pairs of other satellite data, several maps can be generated within a single flood which would enable emergency response agencies to focus on newly flooded areas. |
doi_str_mv | 10.1007/s11707-020-0818-0 |
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Multispectral or optical imagery can be used for generating flood maps when the inundated areas are not covered by clouds. We propose a rapid mapping method for identifying inundated areas based on the increase in the water index value between the pre- and post-flood satellite images. Values of the Normalized Difference Water Index ( NDWI) and Modified NDWI ( MNDWI) will be higher in the post-flood image for flooded areas compared to the pre-flood image. Based on a threshold value, pixels corresponding to the flooded areas can be separated from non-flooded areas. Inundation maps derived from differencing MNDWI values accurately captured the flooded areas. However the output image will be influenced by the choice of the pre-flood image, hence analysts have to avoid selecting pre-flood images acquired in drought or earlier flood years. Also the inundation maps generated using this method have to be overlaid on the post-flood satellite image in order to orient personnel to landscape features. Advantages of the proposed technique are that flood impacted areas can be identified rapidly, and that the pre-existing water bodies can be excluded from the inundation maps. Using pairs of other satellite data, several maps can be generated within a single flood which would enable emergency response agencies to focus on newly flooded areas.</description><identifier>ISSN: 2095-0195</identifier><identifier>EISSN: 2095-0209</identifier><identifier>DOI: 10.1007/s11707-020-0818-0</identifier><language>eng</language><publisher>Beijing: Higher Education Press</publisher><subject>Disasters ; Drought ; Earth and Environmental Science ; Earth Sciences ; Emergency preparedness ; Emergency response ; Flood mapping ; Flooded areas ; Flooding ; Floods ; Image acquisition ; Imagery ; inundation maps ; Landsat ; Landsat satellites ; Mapping ; MNDWI ; NDWI ; Rapid Flood Mapping (RFM) ; Remote sensing ; Research Article ; Satellite data ; Satellite imagery ; Satellites ; Spaceborne remote sensing</subject><ispartof>Frontiers of earth science, 2021-03, Vol.15 (1), p.1-11</ispartof><rights>Copyright reserved, 2020, Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature</rights><rights>Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2020</rights><rights>Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2020.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c431t-fd7158e71de72266b099b0b2340352426710452eb8a50e18730768f3ddae6f683</citedby><cites>FETCH-LOGICAL-c431t-fd7158e71de72266b099b0b2340352426710452eb8a50e18730768f3ddae6f683</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11707-020-0818-0$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11707-020-0818-0$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>SIVANPILLAI, Ramesh</creatorcontrib><creatorcontrib>JACOBS, Kevin M.</creatorcontrib><creatorcontrib>MATTILIO, Chloe M.</creatorcontrib><creatorcontrib>PISKORSKI, Ela V.</creatorcontrib><title>Rapid flood inundation mapping by differencing water indices from pre- and post-flood Landsat images</title><title>Frontiers of earth science</title><addtitle>Front. Earth Sci</addtitle><description>Following flooding disasters, satellite images provide valuable information required for generating flood inundation maps. Multispectral or optical imagery can be used for generating flood maps when the inundated areas are not covered by clouds. We propose a rapid mapping method for identifying inundated areas based on the increase in the water index value between the pre- and post-flood satellite images. Values of the Normalized Difference Water Index ( NDWI) and Modified NDWI ( MNDWI) will be higher in the post-flood image for flooded areas compared to the pre-flood image. Based on a threshold value, pixels corresponding to the flooded areas can be separated from non-flooded areas. Inundation maps derived from differencing MNDWI values accurately captured the flooded areas. However the output image will be influenced by the choice of the pre-flood image, hence analysts have to avoid selecting pre-flood images acquired in drought or earlier flood years. Also the inundation maps generated using this method have to be overlaid on the post-flood satellite image in order to orient personnel to landscape features. Advantages of the proposed technique are that flood impacted areas can be identified rapidly, and that the pre-existing water bodies can be excluded from the inundation maps. Using pairs of other satellite data, several maps can be generated within a single flood which would enable emergency response agencies to focus on newly flooded areas.</description><subject>Disasters</subject><subject>Drought</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Emergency preparedness</subject><subject>Emergency response</subject><subject>Flood mapping</subject><subject>Flooded areas</subject><subject>Flooding</subject><subject>Floods</subject><subject>Image acquisition</subject><subject>Imagery</subject><subject>inundation maps</subject><subject>Landsat</subject><subject>Landsat satellites</subject><subject>Mapping</subject><subject>MNDWI</subject><subject>NDWI</subject><subject>Rapid Flood Mapping (RFM)</subject><subject>Remote sensing</subject><subject>Research Article</subject><subject>Satellite data</subject><subject>Satellite imagery</subject><subject>Satellites</subject><subject>Spaceborne remote sensing</subject><issn>2095-0195</issn><issn>2095-0209</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9kF1LwzAUhoMoOHQ_wLuA19WTtPnopQy_YCCIXoe0SbuMLalJh-zfm1LFuwVCzgnvcxIehG4I3BEAcZ8IESAKoFCAJLKAM7SgULPppj7_q0nNLtEypS3kJUXe1QKZdz04g7tdCAY7f_BGjy54vNfD4HyPmyM2rutstL6d-m892piDxrU24S6GPR6iLbD2Bg8hjcU8aZ37pEfs9rq36RpddHqX7PL3vEKfT48fq5di_fb8unpYF21VkowaQZi0ghgrKOW8gbpuoKFlBSWjFeWCQMWobaRmYIkUJQguu9IYbXnHZXmFbue5QwxfB5tGtQ2H6POTijLCBOcUSE6ROdXGkFK0nRpi_mc8KgJq8qlmnyrbU5NPBZmhM5Ny1vc2_k8-BckZ2rh-kw2abCollaX50dl4Cv0BNGaJBw</recordid><startdate>20210301</startdate><enddate>20210301</enddate><creator>SIVANPILLAI, Ramesh</creator><creator>JACOBS, Kevin M.</creator><creator>MATTILIO, Chloe M.</creator><creator>PISKORSKI, Ela V.</creator><general>Higher Education Press</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7TG</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><scope>SOI</scope></search><sort><creationdate>20210301</creationdate><title>Rapid flood inundation mapping by differencing water indices from pre- and post-flood Landsat images</title><author>SIVANPILLAI, Ramesh ; JACOBS, Kevin M. ; MATTILIO, Chloe M. ; PISKORSKI, Ela V.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c431t-fd7158e71de72266b099b0b2340352426710452eb8a50e18730768f3ddae6f683</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Disasters</topic><topic>Drought</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Emergency preparedness</topic><topic>Emergency response</topic><topic>Flood mapping</topic><topic>Flooded areas</topic><topic>Flooding</topic><topic>Floods</topic><topic>Image acquisition</topic><topic>Imagery</topic><topic>inundation maps</topic><topic>Landsat</topic><topic>Landsat satellites</topic><topic>Mapping</topic><topic>MNDWI</topic><topic>NDWI</topic><topic>Rapid Flood Mapping (RFM)</topic><topic>Remote sensing</topic><topic>Research Article</topic><topic>Satellite data</topic><topic>Satellite imagery</topic><topic>Satellites</topic><topic>Spaceborne remote sensing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>SIVANPILLAI, Ramesh</creatorcontrib><creatorcontrib>JACOBS, Kevin M.</creatorcontrib><creatorcontrib>MATTILIO, Chloe M.</creatorcontrib><creatorcontrib>PISKORSKI, Ela V.</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Environment Abstracts</collection><jtitle>Frontiers of earth science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>SIVANPILLAI, Ramesh</au><au>JACOBS, Kevin M.</au><au>MATTILIO, Chloe M.</au><au>PISKORSKI, Ela V.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Rapid flood inundation mapping by differencing water indices from pre- and post-flood Landsat images</atitle><jtitle>Frontiers of earth science</jtitle><stitle>Front. Earth Sci</stitle><date>2021-03-01</date><risdate>2021</risdate><volume>15</volume><issue>1</issue><spage>1</spage><epage>11</epage><pages>1-11</pages><issn>2095-0195</issn><eissn>2095-0209</eissn><abstract>Following flooding disasters, satellite images provide valuable information required for generating flood inundation maps. Multispectral or optical imagery can be used for generating flood maps when the inundated areas are not covered by clouds. We propose a rapid mapping method for identifying inundated areas based on the increase in the water index value between the pre- and post-flood satellite images. Values of the Normalized Difference Water Index ( NDWI) and Modified NDWI ( MNDWI) will be higher in the post-flood image for flooded areas compared to the pre-flood image. Based on a threshold value, pixels corresponding to the flooded areas can be separated from non-flooded areas. Inundation maps derived from differencing MNDWI values accurately captured the flooded areas. However the output image will be influenced by the choice of the pre-flood image, hence analysts have to avoid selecting pre-flood images acquired in drought or earlier flood years. Also the inundation maps generated using this method have to be overlaid on the post-flood satellite image in order to orient personnel to landscape features. Advantages of the proposed technique are that flood impacted areas can be identified rapidly, and that the pre-existing water bodies can be excluded from the inundation maps. Using pairs of other satellite data, several maps can be generated within a single flood which would enable emergency response agencies to focus on newly flooded areas.</abstract><cop>Beijing</cop><pub>Higher Education Press</pub><doi>10.1007/s11707-020-0818-0</doi><tpages>11</tpages></addata></record> |
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subjects | Disasters Drought Earth and Environmental Science Earth Sciences Emergency preparedness Emergency response Flood mapping Flooded areas Flooding Floods Image acquisition Imagery inundation maps Landsat Landsat satellites Mapping MNDWI NDWI Rapid Flood Mapping (RFM) Remote sensing Research Article Satellite data Satellite imagery Satellites Spaceborne remote sensing |
title | Rapid flood inundation mapping by differencing water indices from pre- and post-flood Landsat images |
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