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6

Here are some options Lookup: (not sure) Zonal stats: The GRASS module r.statistics Focal stats: GRASS r.neighbors Nibble: (don't know) Iterate through VAT: I think that the concept of a VAT is specific to Arc*, but r.describe might get close. Combine: Just use GRASS r.mapcalc Mosaic: GRASS - r.patch or gdal_merge


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In R, the package CircStats is old and of rather limited scope and has been replaced by the more complete Circular package. There are tutorials and a book, Circular Statistics with R (2013, A. Pewsey, M. Neuhäuser, and G. D. Ruxton, Oxford University Press, 208 pp.) which explains how to use it (The R scripts can be downloaded from the resources site of the ...


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In addition to Micha's list, here is how you can nibble with GRASS 1) mask your image with r.mapcalc 2) with the resulting image, interpolate to the nearest neighbour using r.surf.nnbathy For combine, I would use r.cross but you can also do it using r.mapcalc with this algorithm For mosaic, I would use gdalbuildvrt: it is often not necessary to create a ...


2

You need to run r.sun, not r.sunmask for this task. There are also convenient GRASS GIS addons to run it in hourly or daily mode. You first need to extrude your buildings with v.extrude, then run the solar computation. See for extrusion "Extrude 2D polygons to 3D" and for a shadow example here. (image courtesy: Markus Neteler) (image courtesy: Vaclav ...


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you can convert your aspects into the sine and cosine, compute the mean of the sine's and the mean of the cosine's, then turn it back to aspect using atan2(sine,cosine). For more details, see Wikipedia


2

Ok, update after another couple of hours of trying. I think I solved the problem, more or less by accident. Since I digitized/simplified the grid structure by hand, one of the problems supposedly was, that a couple of lines would have intersections between their beginning and end points. It seems like a good idea to let QGIS handle this and use 'Split ...


1

The 'direction' you are referring to is known as the aspect of a slope. To calculate this for a raster DEM in QGIS you need to use the Raster > Analysis > DEM (Terrain models) tool which has a mode for aspect. There's a tutorial for working with terrain analysis in the QGIS Training Manual - lesson 8.3. Once you've generated an aspect raster from your DEM, ...


1

NetworkX (http://cheeseshop.python.org/pypi/networkx/) is a Python package with many functions for graph and network analysis. With this package installed you can solve the problem of generating a shortest distance matrix using the Python console in QGIS. All you need is a network layer (the edges) with a valid topology. The edges need at least 3 ...


1

Most textbooks suggest using atan2(Sigma(sin(x)), Sigma(cos(x))), however this is not always the right thing to do. For example, the average of 0, 0 and 90 degrees is atan( (sin(0)+sin(0)+sin(90)) / (cos(0)+cos(0)+cos(90)) ) = atan(1/2)= 26.56 deg, and not 30 deg as one may expect. Take a look at my article on CodeProject "Circular Values Math and ...


1

What are your region settings? I tried this set of commands, and succeeded to create a DEM with negative values, with no problems: # Set region to low resoution GRASS 7.0.0 (ITM):~ > g.region -p res=5 # The contour vector GRASS 7.0.0 (ITM):~ > v.db.select test_ctours cat|elev 1|-100 2|-80 3|-60 4|-40 5|-20 # Create rasterized contours GRASS 7.0.0 ...


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Very good points by @ChrisW. An alternative which may do what you seek is to first polygonize your line shapefile and then create your quadrants (I've included a simple example): I then used the Lines to polygons tool: Now you can use the Split features tool (from toolbar, Edit > Split features) which allows you to split your feature (line, polygon ...


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I'm not sure what the reason is for this duplications, but did you run v.clean with tool=rmdupl to remove duplicates? See also the v.clean documentation: http://grass.osgeo.org/grass70/manuals/v.clean.html


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I don't think that Adobe Illustrator can read UInt16 data, so you have to rescale your raster first with r.rescale to 0-255 values and then export it with r.out.gdal with option type=Byte to Byte datatype.



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