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Yes and you can automate this process with python grass.script or bash script (bat script in Windows). I test it in my system and the individual commands are (for my line vector named route and raster dem named utah_demUTM2): v.to.rast input=route value=1 output=route_raster r.thin input=route_raster output=route_raster_thin r.mapcalc ...


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If the least cost paths were extracted from a raster map, then I assume they would have line vertexes that fall on the raster cells (unless you used the knight's step but it may still work well enough). You could then: run v.patch on all your vector LCPs (I think this would be pretty fast even on a large number of vector maps) run v.to.points, which will ...


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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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Please consider to ask the authors and invite them to enhance the manual page. They will know best how to deal with the preparation of the input data.


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Have you enabled the advance interface :


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Under Windows you have a "special version" of QGIS with GRASS available: Start this special version and enable the now available grass-plugin: Go to Menu Bar / View / Panels and check, that its enabled (should be already by default) Go to Menu Bar / View / Toolbars and check, that its enabled (should be already by default)


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In 2.10.1 I'm able to access GRASS Tools panel, and GRASS toolbar by: Enabling GRASS plugin Go to Menu Bar / View / Panels and confirm GRASS Tools is checked Go to Menu Bar / View / Toolbars and confirm GRASS is checked Then, I'm able to click the 'New Mapset' button in the GRASS Toolbar.


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The GRASS GIS Landsat.toar module relies heavily on the article by Chavez from 1996 and you ought to read that for a full understanding on what happens. The implementation in GRASS GIS doesn't directly match the one seen in the paper, but I expect that this is a result of an aversion to the use of the trig-function 'sec' in GRASS GIS. 'TAUz' is the ...


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Export as PNG (r.out.png) and select Output World File. Load up QGIS and import the PNG file. Upon import you will need to select the Coordinate System and QGIS will read the associated .wld file to georeference the image.


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This is the stack I have been using for a couple of years: Ubuntu Server 12.04 GRASS 6.4 PyWPS 3 GRASS 7 is now packaged for Ubuntu 14.04 at the Ubuntu-GIS PPA. You could also try with those and then PyWPS 3. Note: PyWPS 4 is likely to be released in the next few months.


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it seems that my problem was in the GRASS algorithm I was using. Now, I've moved to GDAL algorithm named "Grid - InverseDistance To a Power" and it works. I don't really know what was wrong: my only suspect is that after running grass algorithm I would need to "convert" the grass raster map created to a "readble" raster, to be loaded in QGis correctly. I ...


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I started to dive into VTK - The Visualization ToolKit (VTK) is an open source, freely available software system for 3D computer graphics. It is pretty powerful and robust tool, seems to be able to do all the operations I asked for though I can't confirm it all yet. On the other hand it doesn't support datum and projection as is expected from GIS software. ...


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I think the simplest answer is no. The GRASS LIDAR docs state: v.in.lidar - (GRASS 7 only; GRASS must be compiled with libLAS support). Which the GRASS 7.0 Ubuntu packages do not appear to have. From the latest build log (amd64): GRASS is now configured for: x86_64-pc-linux-gnu ... GDAL support: yes GEOS support: ...


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I'd think twice before upgrading to GDAL 1.11 if I was you... I also broke my GDAL by installing GRASS 7, so I upgraded to GDAL 1.11.2, and QGIS 2.8. At first this seemed to so fix things, but then I noticed some strange behaviour in QGIS, which I now believe is caused by the new GDAL. When I load rasters, they often appear in wrong locations, and the ...


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Use r.composite to merge the bands back into a single raster. This is the example from the documentation page: r.composite blue=lsat7_2002_10 green=lsat7_2002_20 red=lsat7_2002_30 output=lsat7_2002_rgb Don't forget to set your region!


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Steven already shared a very good walk-through! I just want to add that you could also use the QGIS LecoS plugin (requires active numpy/scipy installation within your QGIS path) for this purpose. Especially for raster basic cleaning and edge extraction purposes. LecoS has a so-called landscape modifier since some time, which applies scipy's erosion ...


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I'm not sure how well this will work without trying on your specific raster, but a few pointers. I assume from your image you used Threshold in GIMP to give you a binary raster (inside field/outside field) Removing noise You can use GDAL Sieve to remove the 'salt and pepper' noise - those little holes within the fields. You can do this from QGIS (Raster ...


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Topology means "the rules and behaviors that model how points, lines, and polygons share coincident geometry." (Source.) These rules can apply specifically to geometry and how it is stored, or be created by you to check for certain things. Topology Checker looks at rules you have set up or chosen to apply to the data. Things like a line must be inside a ...


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Today (3 and half months later), I solved my problem with the update to new 2.10 (Pisa) version of QGIS.


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zoom to the extent you're after optionally, ctrl-b to save the extent rectangle select the polygons (drag over the whole canvas extent) vector > geometry tools > buffer (selected features only, distance .001 or less, dissolve results) This will expand the coastline outwards just enough to overlap across the line, the dissolve will 'heal' the gap. You ...


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As far as I know, before using v.net.salesman to get your route, you should connect your points layer to your network (line vector layer) using v.net op=connect [1] at nlayer=2 Once you connect your 12 points to your network as nodes, you'll be able to select your nodes layer from the "input nodes" dropdown menu. Hope this helps. Cheers, LluĂ­s [1] ...


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I would not be too sure that the downgrade from GDAL 1.11 to 1.10 was really clean. If you want to stick to that GDAL version, I suggest to re-build QGIS again with it. Upgrading to GDAL 1.11 is surely better, but if you need ecw support on Ubuntu, you might run into problems there (see Unable to install ECW support on lubuntu 14.04 for that). On the other ...


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Since you put GRASS into the tags, here's a solution based on GRASS: First, you need to know exactly what coordinate system the original data is in (as always with GRASS). I see that the *.prj file contains "TRANSVERSE MERCATOR" but it's not one of the standard UTM zones. Since you have not mentioned the EPSG code of this data, here's the proj4 string for ...


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since I'm from the debian/ubuntu universe it is called differently at centos/rhel... have a look at http://wiki.osgeo.org/wiki/Enterprise_Linux_GIS#How_to_enable_the_ELGIS6_repository at centos it is called grass-devel-* (see http://elgis.argeo.org/repos/6/elgis/x86_64/) remark: 6.4 is the old stable branch. I recommend 7.0 -> much more fun.



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