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<p class="MsoNormal"><span style="mso-fareast-language:EN-US">Hi Shane,<o:p></o:p></span></p>
<p class="MsoNormal"><span style="mso-fareast-language:EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-US">Following up on robertos answer:<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-US">You could try the Normalized Difference Water Index (NDWI) which is computed for S-2 as:<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-US">ndwi = (B08-B11)/(B08+B11)<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-US">or alternatively<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-US">ndwi = (B03 - B08) / (B03 + B08)<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-US">See e.g.:
<a href="https://github.com/sentinel-hub/custom-scripts/blob/master/sentinel-2/ndwi/script.js">
https://github.com/sentinel-hub/custom-scripts/blob/master/sentinel-2/ndwi/script.js</a><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-US">You could also take a look at Sentinel-1 for flooding / water bodies. However, Sentinel-1 would have to be pre-processed in SNAP/gpt.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-US">Cheers<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-US">Stefan<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US">From:</span></b><span lang="EN-US"> grass-user <grass-user-bounces@lists.osgeo.org>
<b>On Behalf Of </b>Shane Carey<br>
<b>Sent:</b> fredag 7. desember 2018 17:35<br>
<b>To:</b> roberto.marzocchi@gmail.com<br>
<b>Cc:</b> grass-user grass-user <grass-user@lists.osgeo.org><br>
<b>Subject:</b> Re: [GRASS-user] Sentinel2- flooding<o:p></o:p></span></p>
<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal">Ok, thanks. <o:p></o:p></p>
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<p class="MsoNormal">Le gach dea ghui,<o:p></o:p></p>
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<p class="MsoNormal"><b><i><span style="color:#3D85C6;background:white">Shane Carey</span></i></b><o:p></o:p></p>
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<p class="MsoNormal"><b><i><span style="color:#3D85C6;background:white">GIS and Data Solutions Consultant</span></i></b><o:p></o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal">On Fri, Dec 7, 2018 at 2:45 PM Roberto Marzocchi <<a href="mailto:roberto.marzocchi@gmail.com">roberto.marzocchi@gmail.com</a>> wrote:<o:p></o:p></p>
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<p class="MsoNormal">I Think there isn't any tool pre-configured. You need to find an index to calculate "flooded" cells and then you can simply use r.mapcalc<o:p></o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal">R<o:p></o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal">Il giorno ven 7 dic 2018 alle ore 14:45 Shane Carey <<a href="mailto:careyshan@gmail.com" target="_blank">careyshan@gmail.com</a>> ha scritto:<o:p></o:p></p>
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<p class="MsoNormal">Hi,<o:p></o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal">I've obtained an image from sentinel2 where it shows flooding. Just wondering are there tools in Grass to classify an image in order to pull out these "flooded" pixels?<o:p></o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal">Thanks<o:p></o:p></p>
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<p class="MsoNormal">-- <o:p></o:p></p>
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<p class="MsoNormal">Le gach dea ghui,<o:p></o:p></p>
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<p class="MsoNormal"><b><i><span style="color:#3D85C6;background:white">Shane Carey</span></i></b><o:p></o:p></p>
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<p class="MsoNormal"><b><i><span style="color:#3D85C6;background:white">GIS and Data Solutions Consultant</span></i></b><o:p></o:p></p>
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