I apologise in advance for this very general query. I am looking for pythonic ways to translate level-2 satellite data from a series of 2D irregularly gridded netCDF files to CoG. I very much see rio-cogeo as the last point in this chain, but I am wondering if you have recommendations about how to reach to a good "ingestion point" for it. So far, reprojecting from the original grid with rasterio/rio-xarray is causing me huge headaches (and yet they seem to recommended over osgeo gdal), and so I wondered if you have encountered, or can recommend, a similar workflow?
Things I want to avoid;
using large external packages (e.g. SNAP)
using GPL3 software (e.g. Satpy)
I realise that my problem is not the one you are trying to solve, but any advice would be appreciated.
Hi cogeotiff team,
I apologise in advance for this very general query. I am looking for pythonic ways to translate level-2 satellite data from a series of 2D irregularly gridded netCDF files to CoG. I very much see rio-cogeo as the last point in this chain, but I am wondering if you have recommendations about how to reach to a good "ingestion point" for it. So far, reprojecting from the original grid with rasterio/rio-xarray is causing me huge headaches (and yet they seem to recommended over osgeo gdal), and so I wondered if you have encountered, or can recommend, a similar workflow?
Things I want to avoid;
I realise that my problem is not the one you are trying to solve, but any advice would be appreciated.