Try our open source python package available through PyPI
or conda-forge
that merges tiles from the open AWS registry of Copernicus 30 meter DEM. (Obviously: I am one of the library developers). We are using this for InSAR processing, so there are few more basic transformations that the library can do, which you can read about on the homepage.
https://github.com/ACCESS-Cloud-Based-InSAR/dem-stitcher
bounds = [-119.085, 33.402, -118.984, 35.435]
X, p = stitch_dem(bounds,
dem_name='glo_30',
dst_ellipsoidal_height=False,
dst_area_or_point='Point')
# X is an m x n numpy array
# p is a dictionary (or a rasterio profile) including relevant GIS metadata
Hope this helps. Lots of information on the page. Can also utilize other global tiles such as NASADEM.
Related: You could also download one of the zipped geojsons
from the library here, unzip it, load it into QGIS, and then click the URLs for tiles you are interested. That seems like that might be good too. For Copernicus 30 meter tiles, the file name is glo_30.geojson.zip
.
It's probably because the default STAC api, the stac-to-dc tool pointing to is from https://earth-search.aws.element84.com/v0/ and it doesn't have a STAC collection called 's1_rtc'.
If you change your STAC url to the one from Digital Earth Africa, they seem to have a collection called 's1_rtc'. Hopefully this would add new datasets to your datacube index.
stac-to-dc --bbox='26,-10,25,-11' --collections='s1_rtc' --datetime='2020-01-01/2021-9-20' --catalog-href='https://explorer.digitalearth.africa/stac'
Best Answer
Great question. The easiest way to do this is using RIO STAC, which was developed by the magnificent Vincent Sarago. I use it programmatically (from Python).
Make sure you enable the Projection extension, but other than that, that's all you need to do.
Here's some code that does it.
And example is this: