Visualizing results from openeo jobs in Jupyter

Hi all.

I am currently processing some data for SW Spain (~200x300km area) and I want to visualize these results in Jupyter. Currently, I am downloading data locally and doing the drilldown that way, using xarray the holoviews / geoviews packages and the NetCDF4 file format.
Of course, the data source for the drill down is at least an order of magnitude larger than the map that I want to download in it’s entirety.
Enter Cloud Optimized Geotiffs (COGs). I want to directly query the COGs, so that I do not have to download the source files locally. I however do not have experience with COGs in general.
Looking at: Cloud Optimized GeoTIFF I see that rasterio has some options, but there are many libraries listed. Any recommendations on how to tackle interactive querying of COGS and plotting in python / jupyter? Definitely when querying a collection with more than just one Geotiff (how to find the area that you are looking for?)


Hi Jaap,

I don’t have a lot of experience with COGs in Python/Jupyter, but I’ve heard that leafmap has good support for STAC and COGs and that’s what I’d try first: GitHub - giswqs/leafmap: A Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment

Hope it helps,