3

I could reproduce these results with Landsat-8 panchromatic band. When you are using cv2.imread(fl,0) it reads image as greyscale 8 bit (0-255), you should either read it as cv2.imread(fl,cv2.IMREAD_UNCHANGED) or cv2.imread(fl,-1) since your original image has 16 bit depth (0-65535) as for the other question What are those numbers that I see in the arrays? ...


3

If you want to load a multi-band raster up, don't use raster() function, use brick() or stack() instead. raster() only opens single-band rasters, even from a multi-band raster (you can set the band you want to open). Rotate works with multi-band rasters, so you'll be fine after opening the file: r <- raster(nrow=18, ncol=36) m <- matrix(1:ncell(r), ...


2

Rasterio is one of the best possible solutions for extracting raster values for given x, y coordinates. import rasterio def interpz(vlist, dtmfile): with rasterio.open(dtmfile) as src: vals = list(src.sample(vlist)) return [(y[0], y[1],vals[x][0]) for x,y in enumerate(vlist)] dtm = "path/to/dtm" points = [(27.996317832013315, 41....


2

The quickest way without opening the python console would be to do the following: run 'split vector layer' which creates a separate file for each of your vector features. Make sure to select an output directory. Then open all the vector files in qgis. now run 'clip raster by mask layer' and click on 'Run as Batch Process...' button in the bottom left hand ...


2

This is a work in progress and is untested, but here is what you need to do: Rename the dimensions/coordinates of x/y so they are the same. xds = xds.rename_dims({"NX": "x", "NY": "y"}).rename_vars({"X": "x", "Y": "y"}).set_coords(["x", "y"]) Write the CRS ...


1

Get a polygon layer of the water surface, for example from OpenStreetMaps (OSM). See here how to download: https://gis.stackexchange.com/a/368774/88814. Another option is to use the QuickOSM plugin. You can use the OpenStreetMap tags natural=water (red on the screenshot) and natural=bay (blue). You will get many very small water features, so probably you ...


1

I had this issue too. To solve this, I have started the geotiff python package. It's a fairly new project and I discuss the roadmap here


1

Adding the layer as image source worked: https://docs.mapbox.com/mapbox-gl-js/style-spec/sources/#image


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