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6

I downloaded your contour geopackage. Open it with QGIS, right click the layer -> Layer CRS -> Set Layer CRS -> Search for "3912" -> OK Your contour lines should be where you want them


5

The herringbone pattern in your image is a classic indication that a Nearest Neighbor resampling occurred somewhere in your workflow. I suggest that you go back through each processing step and closely review each tool's Resampling options and make sure that you select either Bilinear or Cubic. For example, you mention that you conducted a reprojection, but ...


4

If I understand you correctly, the DEM contains the values (elevation) that you want to use to create your cross sectional visualizations to show faults or fractures in the terrain. You may want to look into getting your hands on some LiDAR point clouds of the area, which can be used to extract the bare earth only and create a digital terrain model (DTM, ...


4

The SRTM DEM has a ground resolution of 30 meters (1 arc-second), see https://en.wikipedia.org/wiki/Shuttle_Radar_Topography_Mission#Highest_Resolution_Global_Release and references. So the elevation is "averaged" over a 30x30 meter square. Average in quotes because it is not a mathematical operation, but a physical result of the backscattering of ...


4

Try the GDAL "Fill nodata" utility under Raster --> Analysis. Documentation on the tool can be read here.


3

It is all about definitions. If you assume that your peak is any cell, that is higher than 8 of its neighbors, you'll pick any tiny bump in your terrain: However if definition is any cell that is highest for neighborhood square 101*101, you'll get this: To locate mountain passes you'll need to isolate ridges first. Picture below shows divides between ...


3

You cant remove them, a raster has to be rectangular, but you can use Warp (reproject) to set nodata value to zero which will make them transparent:


2

Short answer The value for the raster resolution should be a bit more then 0.333 m, ca. around 0.34 meters. See below why. Value for 9 regularily spaced points per square meter Consider the image below and suppose the black square is 1m x 1m. Subdividing it in 9 equally sized squares (green dotted line) and getting the centroids of each (red dots), you have ...


2

select in Toolbox: gdal_merge. And merge your rasters


2

As of QGIS 3.22, there is a native if statement in the raster calculator that works very similarly to the ArcGIS equivalent. See the changelog entry. if(river_raster != -9999, river_raster, dem) Where -9999 is the nodata value of the river raster It's worth noting that the raster calculator supports virtual raster (in memory) outputs now too.


2

Split the roads into short segments, I use 20 m Drape to set Z of each road vertice from your DEM Symbolize your layer with graduated symbol, using the z values, for example with z_min($geometry)


2

As Bera recommend, you can merge your las files into one using lastools. You can set lasmerge to keep ground only also (-keep_class 2 on aditional command line parameters of lasmerge dialog box). To generate the DEM you can use LidarIDWInterpolation from Whiteboxtools. You can use this algorithm with the merged las file. Another thing you can try is to ...


2

You can't change data type from float32 to integer without loosing precision. The values will be rounded to the closest meter (or whatever crs unit you are using). I'm using Warp to change data type. The DEM is styled with a hillshade ffect: What you can do is to create a hillshade first, then convert this to integer:


1

It's probably a better idea to map the function, rather than using iterate. The former runs parallel and is much faster. Also, as your 'geometry' is a geometry object, there's no need to use .reduceToVectors, which can be computationally expensive. To calculate the elevation of each image in the collection: var calcMeanElev = function(img){ var eleAve = ...


1

You have, I believe, two options. First you can run GDAL utility gdal_merge, from the processing toolbox (Also appears under the Raster->Miscellaneous menu). You should check the "Place each input file into a separate band" option. Alternatively, just build a virtual raster (vrt) from the two rasters and use that in your segmentation procedure. ...


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