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4

This will be possible with the Project tool with ArcGIS 10.4 (already available as pre-release). An additional parameter 'Vertical' allows you to specify an input and output vertical coordinate system, in addition to the horizontal coordinate system: This new parameter is mentioned in this What's new in 10.4 document (without much detail).


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The offset that you have between your bathymetry and your elevation model relates to the difference between the Mean Seal Level (MSL) and the Lowest Astronomical Tide (LAT). From the well written text found here we can read that: The MSL surface is in a state of gravitational equilibrium. It can be regarded as extending under the continents and is a ...


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A great tool that is often used for vertical datum transformations is called V-datum, developed by NOAA. This is the tool that I have seen cited most often for similar tasks with a range of different datums including tidal. The V-datum docs has some information, as well as this gis.stackexchange answer on EGM96. I'm not familiar with lowest astronomical ...


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If you have access to Spatial Analyst, you could use the Zonal Statistics tool. You could treat each cell in the angled vector grid as a zone, and use Zontal Statistics to calculate the MEAN elevation within it.


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The comment by user Nir led me to the "Nibble" tool (Spatial Analyst Tools - Generalization). I had to do some preparations before I could use it and also some postprocessing. This is the model which works for me: This is the resulting DEM without the obstacle: And this are the watersheds and flow accumulations:


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In response to Jakob's suggestion to use Cut Fill, you could do a comparison of the original DEM and a depression-less DEM (a DEM resulting from using the Fill tool) and that should give you a volume for any given area showing as a sink on the original DEM.


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Use Point Cloud VIZ 2.1 where you will be able to import and export the lidar. Exporting the lidar has 2 options. The bare earth option, or all points options. Once exported you can import the *.vrt file in QGIS. The data will come as a geotiff where you will be able to manipulate further (contour, shade, etc.)


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It's hard to remember when under a crunch, but computer systems sometimes fail in partial or non-apparent forms. When you're being driven crazy by a an unexplainable failure, it's often best to lock the screen, take a quick walk about the floor or building, and work out a fallback procedure. Ask yourself: Could the data be bad? What other tool can I use ...


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you can subsample aster to 4 m and combine both DEMs using simple IF ELSE statements. Note that no new information will be created in the subsampling.


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PDAL can do this for you, and the easiest way to use PDAL is to install Docker Toolbox and then follow the PDAL Docker Tutorial to verify you have the basics working. Once you're confident things are good, run the following command on the data: docker run -v //c/Users/Howard:/data \ pdal/master \ pdal translate //data/point_cloud_classified.las ...


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At first, as you did not tell, you want to create a raster form the points. A similar question about this can be found here: How can I create an DEM from Point-Data Second, I think there are tools in grass, callable from qgis, to make a depressionless dem, like the r.fill.dir tool. Other GIS-people tend to use saga gis functions, as described here: ...


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I suggest you to explore the Generalisation toolbox. Usually different combinations of its tools are used for tasks like this. http://desktop.arcgis.com/en/arcmap/10.3/tools/cartography-toolbox/an-overview-of-the-generalization-toolset.htm


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You need to import it as a CSV file. Since you're new to GIS, I suggest you follow this tutorial: Importing Spreadsheets.


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Suggested workflow: Draw perpendiculars to road segments at regular step Interpolate them to 3D lines using DEM Convert vertices to points Find lowest point If it is “close enough” to centreline, road runs in depression This shows the test I’ve applied to check if already existing streams are matching newly developed DEM: You can also check results ...


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Since you are already using GME, you could try using isectpolyrst . Be sure to look at the link here and note that it excludes polygons that are outside the extent of the raster but I don't see any way to specifically address partial cells within a polygon so this answer may not address that concern either. Anyway I thought it looked like a viable option. ...



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