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    <title>topic Checking and enforcing dowstream Z constraint for synthetic streams in Water Resources Questions</title>
    <link>https://community.esri.com/t5/water-resources-questions/checking-and-enforcing-dowstream-z-constraint-for/m-p/216669#M1004</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Assume I've delineated planar (X, Y) stream breaklines to use them for enforcement of bare ground DEM derivation from high density lidar data (about 1 ground point per square meter or greater). To convert them into 3D breaklines I use a conflation process &lt;SPAN style="display: inline !important; float: none; background-color: transparent; color: #3d3d3d; font-family: Helvetica Neue,Helvetica,Arial,Lucida Grande,sans-serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px; word-wrap: break-word;"&gt;(&lt;/SPAN&gt;&lt;SPAN style="display: inline !important; float: none; background-color: transparent; color: #3d3d3d; font-family: Helvetica Neue,Helvetica,Arial,Lucida Grande,sans-serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px; word-wrap: break-word;"&gt;InterpolateShape&lt;/SPAN&gt;&lt;SPAN style="display: inline !important; float: none; background-color: transparent; color: #3d3d3d; font-family: Helvetica Neue,Helvetica,Arial,Lucida Grande,sans-serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px; word-wrap: break-word;"&gt;)&lt;/SPAN&gt; to populate the Z from the same lidar. Before using them for hydro enforcement in DEM derivation, one needs to see that the vertex elevations decrease monotonically in the downstream direction -&lt;SPAN style="display: inline !important; float: none; background-color: transparent; color: #3d3d3d; font-family: Helvetica Neue,Helvetica,Arial,Lucida Grande,sans-serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px; word-wrap: break-word;"&gt;due to ground vegetation noise and/or leftover structures in the lidar this is not always the case. Does anybody know of a tool/code to:&lt;/SPAN&gt;&lt;/P&gt;&lt;UL&gt;&lt;LI&gt;&lt;SPAN style="display: inline !important; float: none; background-color: transparent; color: #3d3d3d; font-family: Helvetica Neue,Helvetica,Arial,Lucida Grande,sans-serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px; word-wrap: break-word;"&gt;Check for downstream elevation monotonic decrease? &lt;/SPAN&gt;&lt;SPAN style="display: inline !important; float: none; background-color: transparent; color: #3d3d3d; font-family: Helvetica Neue,Helvetica,Arial,Lucida Grande,sans-serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px; word-wrap: break-word;"&gt;The tool would detect and tag (by feature ID and measure?), polyline segments where the stream deviates from strict downstream gradient. An illustration:&lt;/SPAN&gt;&lt;/LI&gt;&lt;/UL&gt;&lt;P style="padding-left: 30px;"&gt;&lt;SPAN style="display: inline !important; float: none; background-color: transparent; color: #3d3d3d; font-family: Helvetica Neue,Helvetica,Arial,Lucida Grande,sans-serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px; word-wrap: break-word;"&gt;&lt;IMG height="193" 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" width="703" /&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;UL&gt;&lt;LI&gt;Enforce the downstream Z monotonicity when errors are found? After enforcement the stream above would look something like:&lt;/LI&gt;&lt;/UL&gt;&lt;P style="padding-left: 30px;"&gt;&lt;IMG height="193" 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" width="703" /&gt;&lt;/P&gt;&lt;P&gt;It seems the functionality exists in the Defense Mapping + Production Mapping extensions (see &lt;A href="http://desktop.arcgis.com/en/arcmap/latest/extensions/defense-mapping/correcting-monotonicity-errors.htm"&gt;http://desktop.arcgis.com/en/arcmap/latest/extensions/defense-mapping/correcting-monotonicity-errors.htm&lt;/A&gt;), but these are of restricted distribution.&lt;/P&gt;&lt;P&gt;Thanks!&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Fri, 02 Feb 2018 15:46:04 GMT</pubDate>
    <dc:creator>RicardoLopez-Torrijos1</dc:creator>
    <dc:date>2018-02-02T15:46:04Z</dc:date>
    <item>
      <title>Checking and enforcing dowstream Z constraint for synthetic streams</title>
      <link>https://community.esri.com/t5/water-resources-questions/checking-and-enforcing-dowstream-z-constraint-for/m-p/216669#M1004</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Assume I've delineated planar (X, Y) stream breaklines to use them for enforcement of bare ground DEM derivation from high density lidar data (about 1 ground point per square meter or greater). To convert them into 3D breaklines I use a conflation process &lt;SPAN style="display: inline !important; float: none; background-color: transparent; color: #3d3d3d; font-family: Helvetica Neue,Helvetica,Arial,Lucida Grande,sans-serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px; word-wrap: break-word;"&gt;(&lt;/SPAN&gt;&lt;SPAN style="display: inline !important; float: none; background-color: transparent; color: #3d3d3d; font-family: Helvetica Neue,Helvetica,Arial,Lucida Grande,sans-serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px; word-wrap: break-word;"&gt;InterpolateShape&lt;/SPAN&gt;&lt;SPAN style="display: inline !important; float: none; background-color: transparent; color: #3d3d3d; font-family: Helvetica Neue,Helvetica,Arial,Lucida Grande,sans-serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px; word-wrap: break-word;"&gt;)&lt;/SPAN&gt; to populate the Z from the same lidar. Before using them for hydro enforcement in DEM derivation, one needs to see that the vertex elevations decrease monotonically in the downstream direction -&lt;SPAN style="display: inline !important; float: none; background-color: transparent; color: #3d3d3d; font-family: Helvetica Neue,Helvetica,Arial,Lucida Grande,sans-serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px; word-wrap: break-word;"&gt;due to ground vegetation noise and/or leftover structures in the lidar this is not always the case. Does anybody know of a tool/code to:&lt;/SPAN&gt;&lt;/P&gt;&lt;UL&gt;&lt;LI&gt;&lt;SPAN style="display: inline !important; float: none; background-color: transparent; color: #3d3d3d; font-family: Helvetica Neue,Helvetica,Arial,Lucida Grande,sans-serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px; word-wrap: break-word;"&gt;Check for downstream elevation monotonic decrease? &lt;/SPAN&gt;&lt;SPAN style="display: inline !important; float: none; background-color: transparent; color: #3d3d3d; font-family: Helvetica Neue,Helvetica,Arial,Lucida Grande,sans-serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px; word-wrap: break-word;"&gt;The tool would detect and tag (by feature ID and measure?), polyline segments where the stream deviates from strict downstream gradient. An illustration:&lt;/SPAN&gt;&lt;/LI&gt;&lt;/UL&gt;&lt;P style="padding-left: 30px;"&gt;&lt;SPAN style="display: inline !important; float: none; background-color: transparent; color: #3d3d3d; font-family: Helvetica Neue,Helvetica,Arial,Lucida Grande,sans-serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px; word-wrap: break-word;"&gt;&lt;IMG height="193" src="data:image/png;base64,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" width="703" /&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;UL&gt;&lt;LI&gt;Enforce the downstream Z monotonicity when errors are found? After enforcement the stream above would look something like:&lt;/LI&gt;&lt;/UL&gt;&lt;P style="padding-left: 30px;"&gt;&lt;IMG height="193" 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" width="703" /&gt;&lt;/P&gt;&lt;P&gt;It seems the functionality exists in the Defense Mapping + Production Mapping extensions (see &lt;A href="http://desktop.arcgis.com/en/arcmap/latest/extensions/defense-mapping/correcting-monotonicity-errors.htm"&gt;http://desktop.arcgis.com/en/arcmap/latest/extensions/defense-mapping/correcting-monotonicity-errors.htm&lt;/A&gt;), but these are of restricted distribution.&lt;/P&gt;&lt;P&gt;Thanks!&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Fri, 02 Feb 2018 15:46:04 GMT</pubDate>
      <guid>https://community.esri.com/t5/water-resources-questions/checking-and-enforcing-dowstream-z-constraint-for/m-p/216669#M1004</guid>
      <dc:creator>RicardoLopez-Torrijos1</dc:creator>
      <dc:date>2018-02-02T15:46:04Z</dc:date>
    </item>
    <item>
      <title>Re: Checking and enforcing dowstream Z constraint for synthetic streams</title>
      <link>https://community.esri.com/t5/water-resources-questions/checking-and-enforcing-dowstream-z-constraint-for/m-p/216670#M1005</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;The functionality I describe exist in... Arc Hydro! There are actually two tools, &lt;EM&gt;Toolbox &amp;gt; Arc Hydro Tools &amp;gt; Watershed Processing &amp;gt; Smooth 3D Line&lt;/EM&gt;: "Smooths 3D lines linearly in the digitized direction."&lt;/P&gt;&lt;P&gt;Another, applies the downstream constraint to a dendritic network, with a check that the constraint is kept at stream junctions. It is &lt;EM&gt;Toolbox &amp;gt; Arc Hydro Tools Python &amp;gt; Watershed Processing &amp;gt; Line Processing &amp;gt; Make 3D Line System &amp;gt; Make 3D Line System&lt;/EM&gt;: "Construct a 3D line from input 2D line by getting the Z value from the input DEM, and M value from the distance between the vertice and vertice[0].'. Activate the Z smoothing parameter to apply the constraint.&lt;/P&gt;&lt;P&gt;Thanks to Dean Djokic for the pointer, and to the AWRA GIS in Water Resources conference for having brought us together.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Tue, 01 May 2018 15:28:45 GMT</pubDate>
      <guid>https://community.esri.com/t5/water-resources-questions/checking-and-enforcing-dowstream-z-constraint-for/m-p/216670#M1005</guid>
      <dc:creator>RicardoLopez-Torrijos1</dc:creator>
      <dc:date>2018-05-01T15:28:45Z</dc:date>
    </item>
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