4
The problem you're seeing occurs when you load multiple tiles but the the gray scale interpretation of min/max is based on only one of the tiles. If other tiles have a different range, parts may be "blown out". Probably the easiest way to deal with this is to combine the tiles into a single raster, then load that raster. Alternatively, if you have only a few ...
3
How about something like this:
radius=5000 # Maximum distance
X=200000 # X coordinate of lookout
Y=500000 # Y coordinate of lookout
r.import dem.tif output=elev
g.region -a rast=elev
r.viewshed input=elev output=vshed max_distance=$radius coordinates=${X},${Y}
r.to.vect input=vshed output=vshed type=area
This should leave you with a raster named "...
3
Picking the contour interval has less to do with horizontal resolution of the DEM, 3m in your case, and is instead mediated by the accuracy of the elevation values.
Specifically, to produce valid contours without forcing the interpolation software to "guess" more than it reasonably should, the smallest interval you can make contours of is limited at ...
2
This can be done with R, visualized with the rgl package, and converting the DEM and image to mesh3d form with the quadmesh package.
Here I use another package ceramic from github to obtain the DEM and image, but you can replace those by reading the DEM with raster::raster() and the image with raster::brick().
## install.packages(c("remotes", "quadmesh", ...
2
Given a DEM and DSM:
Use raster calculator to compute height:
Compute zonal statistics for your shapefile using height raster:
Join table to shapefile and extrude geometries using fields created with Zonal statistics process:
1
You are trying to clip a raster using a mask layer.
Using Qgis, you can follow the following procedure.
Load your dem and polygon on the canvas
In the raster menu, go to Extraction -> Clip raster by mask layer
There, put your DEM as input layer, your polygon as mask layer. You can pretty much leave the other fields as default
In the Clipped(mask) field, ...
1
If you retrieved the data from LRO LOLA (LDEM GDR), you do need to multiply vertical (height) values by a "Scaling Factor" of 0.5:
From the documentation:
Conversion to local height (meters) is accomplished via the following equation:
Height = (Pixel Value * Scaling Factor)
Conversion to local Radius (meters) is computed as follows:
Radius = (Pixel ...
1
You can use the Raster Calculator to do arithmetic on a raster.
Enter an expression like moon@1 / 2 into the Raster Calculator Expression box and set an output layer path and format.
But I would check first that your data really is in half-metre units - check the metadata carefully and check that the basis you are comparing it with is right too.
1
If you can use R, it's raster package supports intuitive raster algebra that will make your task very simple. Try this:
library(raster)
rred <- brick(system.file("external/rlogo.grd", package="raster"))[['red']] ## MWE, use your data
values(rred) <- values(rred) - mean(values(rred))
rbad <- rred > 0
rgood <- rred <= 0
rmiss <- rred ==...
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