Convert backscatter data to geotiffs for each NISAR GCOV product in a given directory

nisar_gcov_to_geotiff.py

import os
from concurrent.futures import ProcessPoolExecutor
from pathlib import Path

from osgeo import gdal

gdal.UseExceptions()
os.environ['GDAL_NUM_THREADS'] = 'ALL_CPUS'
os.environ['GDAL_DISABLE_READDIR_ON_OPEN'] = 'TRUE'

pols = {
    'DH': ['HHHH', 'HVHV'],
    'SH': ['HHHH'],
    'DV': ['VVVV', 'VHVH'],
    'SV': ['VVVV'],
    'QP': ['HHHH', 'HVHV', 'VVVV', 'VHVH'],
    'NA': [],
}


def process_product(product: Path):
    print(product)
    for frequency in ['A', 'B']:
        if frequency == 'A':
            index = product.stem[36:38]
        else:
            index = product.stem[38:40]
        for pol in pols[index]:
            source = f'NETCDF:"{product}"://science/LSAR/GCOV/grids/frequency{frequency}/{pol}'
            dest = f'{product.parent}/{product.stem}_{frequency}_{pol}.tiff'
            gdal.Translate(
                destName=dest,
                srcDS=source,
                format='COG',
                stats=True,
                creationOptions=['OVERVIEW_RESAMPLING=AVERAGE'],
            )


working_dir = Path('.')
products = working_dir.glob('*.h5')
with ProcessPoolExecutor(max_workers=4) as executor:
    executor.map(process_product, products)