# Upload processed data file to GEE
asset_name = f'projects/resource-watch-gee/{dataset_name}'
# name bands according to variable names in original netcdf
vars = ['b0']
bands = [{
'id': var,
'tileset_band_index': vars.index(var),
'pyramiding_policy': pyramiding_policy,
'missing_data': {
'values': [nodata_value]
}
} for var in vars]
# create manifest for asset upload
manifest = util_cloud.gee_manifest_complete(asset_name, gcs_uris[0], bands)
# upload processed data file to GEE
task_id = util_cloud.gee_ingest(manifest, public=True)
# remove files from Google Cloud Storage
util_cloud.gcs_remove(gcs_uris, gcs_bucket=gcsBucket)
print('Files deleted from Google Cloud Storage.')
'''
Upload original data and processed data to Amazon S3 storage
'''
# initialize AWS variables
aws_bucket = 'wri-projects'
s3_prefix = 'resourcewatch/raster/'
logger.info('Uploading original data to S3.')
# Upload raw data file to S3
band_ids = ['b1']
task_id = []
# Upload processed data files to GEE
for uri in gcs_uris:
# generate an asset name for the current file by using the filename (minus the file type extension)
asset_name = f'projects/resource-watch-gee/{dataset_name}/{os.path.basename(uri)[:-4]}'
# create the band manifest for this asset
mf_bands = [{
'id': band_id,
'tileset_band_index': band_ids.index(band_id),
'tileset_id': os.path.basename(uri)[:-4],
'pyramidingPolicy': pyramiding_policy
} for band_id in band_ids]
# create complete manifest for asset upload
manifest = util_cloud.gee_manifest_complete(asset_name, uri, mf_bands)
# upload the file from GCS to GEE
task = util_cloud.gee_ingest(manifest)
print(asset_name + ' uploaded to GEE')
task_id.append(task)
# remove files from Google Cloud Storage
util_cloud.gcs_remove(gcs_uris, gcs_bucket=gcsBucket)
logger.info('Files deleted from Google Cloud Storage.')
'''
Upload original data and processed data to Amazon S3 storage
'''
# initialize AWS variables
aws_bucket = 'wri-projects'
s3_prefix = 'resourcewatch/raster/'
