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2

@pigreco answer should works. Here a simplest solution without the spatialite process (step 1 to 2 are the same). Load your .dxf and export (save as...) as shapefile (or spatialite / postgis). On the new layer, use the Field Calculator (accessible from the main toolbar or from the attribute table). Setup the new column (name and type, virtual or not ...


3

If it is 3D DXF, follow the steps: import the dxf in QGIS (DRAG & DROP or CTRL + V); save as vectors (as the right mouse button); add new field Z (integer); Browser Panel to create a new database spatialite; DBManager to import the shape in the newly created database; run the update query; step 1 step 2 step 3 - add new field Z step 5 -DB ...


0

First you will want to generate a raster surface. To do that you want to start with points with values. You should be able to create a point file with the values from the analytical results that you have (assuming you have coordinate values in your table). Then the size of the raster surface that you create will depend on the spatial density of points that ...


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I've experienced the same problems you area having in your second method. I exported a Raster to a Vector and try to and use v.generalise and I get mostly smooth polygons with the occasional 'stepped' boundary which appears to have been unaffected by the algorithm. I found a process that worked for my task, not sure if its the best way but thought i'd share ...


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 ...


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If there isn't good agreement between the datasets you can't really expect much, but all these vector solutions are pretty labour intensive. I would create two DEMs and mess with some masking in the interface area of the 2 data sets to set up some averaging or weighting rules based on initial results. If you want quick and dirty convert both rasters to ...


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By default any interpolation (projecting/resampling) will be nearest neighbour and this is the issue most of the time (meant for categorical data NOT continuous). I would say focal majority is a poor choice as I would imagine the cells all have unique float values. Better off with the mean. You could also change the interpolation to bilinear and just use ...



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