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Having done this with both airborne and terrestrial LiDAR, I would suggest using Whitebox. It has a fairly robust set of tools specifically for handling LiDAR data and it's quite fast at handling LAS files and can remove non-ground objects. Each tool has a pretty good description of how to use it and what options to select. It is also cross-platform (if ...


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Not a real solution ... but you may use r.carve first to burn the main flowline into the DEM. Then re-run r.flow on that. In order to find the main flowline, some v.net.* modules may help (shortest path perhaps). In essence, using a dual-step approach.


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If you would like to calculate GWR in R, you should try GWmodel. If you need to do it in Python, you can also use pygwr. GWmodel contains many geographically-weighted (GW) models including gwr (GW regression), gwpca(GW principal components analysis), gwda(GW Discriminant Analysis), gwr.generalised(Generalised GWR models, including Poisson and Binomial), ...


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Similar to Rob Skelly's suggestion, I would second using 30m SRTM data. I know Whitebox has a great tool for this that will download the SRTM files and process the DEM in one shot based on your area. From here you can create contour or basins from the DEM.


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You might try downloading the 30m SRTM for your region and deriving the contours yourself. It's available through EarthExplorer for free. Contours can be generated with the Raster > Extraction > Contour tool in QGIS.


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One of the easier ways to do this is with a spatial database such as PostGIS. Load your raster into the database using raster2pgsql (which is installed with PostGIS) and then load your rivers with shp2pgsql (also installed with PostGIS). Then, you can run a simple query that samples the elevation model at the end points of all your lines: select ...


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SetNull is one way to do this, then follow with IsNull to create a binary polygon and then Raster to Polygon (simplify). A simpler workflow would be to use Con (SA): In arcpy: outCon = Con(Raster("elevation") >= 5, 1, 0) arcpy.RasterToPolygon_conversion(outCon, "c:/output/NewLandSea.shp", "SIMPLIFY") The Con tool is available interactively using ...


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I came across a toolset that I have used for DEM and DTM extractions called the LAS Toolset. I use it in ArcGIS, however I believe that it also can be used independently. The download for the toolset is found at : http://www.cs.unc.edu/~isenburg/lastools/ Through this you can use filters to filter out all of the LAS points that are not ground/water for ...


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I am posting my answer in case this could prove useful to anyone jumping here in the future. In Raster Calculator I used: SetNull("DEM", "DEM", "Value <= 5") and it did the trick.


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This is very similar to a question the other day relating to rising water levels. You could likely use the Interpolate Shape tool (http://resources.arcgis.com/en/help/main/10.1/index.html#/Interpolate_Shape/00q90000006m000000/) in some fashion. The simplest way would probably be to reclass the dem ...


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You don't need to be updating row[1] for every feature, so cursor.updateRow(row) should be under the final else statement. Also, I'd suggest using with statements as closing is better supported: fc = r"C:\Points\Test.gdb\Points_3d" with arcpy.da.UpdateCursor (fc, ["Elevation","Slope"]) as cursor: firstRun = True for row in cursor: if ...


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There are several ways to accomplish what you want. You've left out some specifics such as what extensions you have available and what license level you're using, as well as how thoroughly you want to sample the raster (ie how fine is your grid). I'll make some assumptions. The simplest, if you want a point for every cell in the DEM, is the Raster to Point ...



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