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5

The smoothing is actually a part of every hydrological analysis in gis (and in arcgis as well). The tool you may want to use is fill. This tool fills sinks and remove peaks, adding functionalities such as the z-limit factor. Shortly, z-limit allow to keep sinks / peaks that exceeds the parameter's value.


4

One approach that our amazing intern recently used, which turned out really well for us: Fill the DEM Calculate flow direction on the filled raster Accumulate the flow of the flow direction output Do a Con operation to set all cells with an accumulated flow over some threshold (that is meaningful for your geographic area and for your cell size) to be 1 and ...


2

Solution assumes your classes are topologically correct polygons, i.e. there are no gaps and overlaps between them. Class defined by value stored in field GRIDCODE #define boundary between polygons and delete outer ones arcpy.PolygonToLine_management(in_features="polygons", out_feature_class="D:/Scratch/lines2D.shp", neighbor_option="IDENTIFY_NEIGHBORS") ...


2

I would look at the English Environment Agency's website which will provide you with 2m, 1m and in some areas 50cm resolution DTMs and DSMs. All you need to do is find some drumlins, this paper Subglacial bedforms of the last British Ice Sheet, Anna L.C. Hughes, Chris D. Clark & Colm J. Jordan could help. Here's an area of drumlins in 1 metre Lidar from ...


2

I use the following procedure with great success. Open "Processing" toolbox inside QGIS, click on "SAGA", click on "Raster creation tools", and finally click on "Triangulation". In the "triangulation" dialog box, select the shape file that has the data points used to create the contour. Choose the attribute field that has the elevation data, specify the ...


1

I'm not sure if you can do this with any of the gdal cli tools, but I wrote something in python which accomplishes it: from osgeo import gdal from osgeo.gdalconst import GDT_Float32 import sys import numpy as np def fix_dem_nodata(raster_input, raster_output, nodata=0, threshold=-900): try: in_data, out_data = None, None # open ...


1

So just in case someone else encounters the same problem: this seems to work ! CREATE OR REPLACE FUNCTION drape(my_wkt text) RETURNS geometry AS $$ DECLARE geom3d geometry; BEGIN WITH line AS (SELECT my_wkt::geometry as geom), linemesure AS -- Add a mesure dimension to extract ...


1

This thread may help you. Which talks of using Euclidean distance and Con tool to select a particular cell based on a conditionality. Conditional reclassification of a raster you may try using Euclidean distance to select the neighbouring cell based on the condition of a boundary of river network and the elevation difference.


1

The eye dropper tool works wonders if you don't know what the color is but want to figure it out. http://www.esri.com/esri-news/arcwatch/1214/finding-colors-on-maps-is-easy-using-the-eye-dropper-tool The trick in your case is that there is an underlying hillshade that is interacting with the colors. I'd pick a low elevation and a high elevation with ...


1

combined the colored GeoTIFFs with: gdalbuildvrt -srcnodata "0 0 0" -addalpha ouput.vrt water_rgb.tif land_rgb.tif after that, I exported the vrt as 3 band GeoTIFF


1

Try Zonal Statistics or Zonal Statistics as Table Tool. The first I mentioned works with input raster dataset that you want to calculate statistics from and raster dataset or feature class that defines the zones. Only one statistics a ta time is supported here and you can select it from the drop-down menu. Result is raster dataset I think with the ...


1

Use Zonal Statistics or Zonal Statistics as Table. If you would like the result to be smallest elevation change then use DEM and pick RANGE as Statistics Type. If you would like the result to be minimum slope then use the result of Slope Tool instead of DEM and MINIMUM or the one thar suits you best as Statistics Type



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