Add stacking cfg and processing script

scripts/rbr_processing_script.py

@@ -157,7 +157,7 @@ def rbr_processing(
     # load the post fire data, or the year of interest
     post_ds = load_ard(
         dc=dc,
-        products=['ga_ls8c_ard_3'],
+        products=["ga_ls8c_ard_3"],
         geopolygon=pgon,
         time=("2020-01-01", "2020-12-31"),
         group_by="solar_day",

scripts/stacking_processing_script.py

@@ -0,0 +1,149 @@
+import s3fs
+import re
+import rioxarray
+import xarray as xr
+
+from datacube.utils import geometry
+from datacube.utils.cog import write_cog
+
+from dea_burn_cube import bc_io, helper
+
+# Initialize the S3 filesystem (using anonymous access)
+fs = s3fs.S3FileSystem(anon=True)
+
+logging.getLogger("botocore.credentials").setLevel(logging.WARNING)
+logging.basicConfig(level=logging.INFO, format="%(asctime)s %(message)s")
+logger = logging.getLogger(__name__)
+
+def logging_setup():
+    """Set up logging."""
+    loggers = [
+        logging.getLogger(name)
+        for name in logging.root.manager.loggerDict
+        if not name.startswith("sqlalchemy") and not name.startswith("boto")
+    ]
+
+    stdout_hdlr = logging.StreamHandler(sys.stdout)
+    for logger in loggers:
+        logger.addHandler(stdout_hdlr)
+        logger.propagate = False
+
+
+def process_files(match_products, region_id, output_folder):
+    """
+    Search for corresponding files from the match_products based on region id
+    """
+
+    pair_files = []
+
+    # Collect matching files from each product
+    for match_product in match_products:
+        # Build the target folder path dynamically
+        # Let us assume all NBIC product under the same project folder:
+        # s3://dea-public-data-dev/projects/burn_cube/derivative
+        target_folder = f"{output_folder/match_product['product_name']}/3-0-0/{region_id}/"
+
+        # List files in the specific target folder
+        all_files = fs.glob(target_folder + '**')
+
+        # Filter matching files by extension and store with product weight
+        matching_files = [file for file in all_files if file.endswith(match_product["extension_name"])]
+
+        if matching_files:
+            pair_files.append({"file_path": matching_files[0], "product_weight": match_product["product_weight"]})
+
+    # If no files matched, skip further processing
+    if not pair_files:
+        return None
+
+    # Open and process all matching files
+    da_list = []
+    for pair_file in pair_files:
+        # Open raster data from S3
+        da = rioxarray.open_rasterio(f"s3://{pair_file['file_path']}")
+        # Apply product weight
+        da_list.append(da * pair_file["product_weight"])
+
+    # Concatenate along a new "variable" dimension and sum across it
+    combined = xr.concat(da_list, dim="variable")
+    sum_summary = combined.sum(dim="variable")
+
+    # Add CRS (Coordinate Reference System) to the output
+    sum_summary.attrs["crs"] = geometry.CRS("EPSG:3577")
+
+    return sum_summary
+
+
+@click.command(no_args_is_help=True)
+@click.option(
+    "--task-id",
+    "-t",
+    type=str,
+    default=None,
+    help="REQUIRED. Burn Cube task id, e.g. Dec-21.",
+)
+@click.option(
+    "--region-id",
+    "-r",
+    type=str,
+    default=None,
+    help="REQUIRED. Region id AU-30 Grid.",
+)
+@click.option(
+    "--process-cfg-url",
+    "-p",
+    type=str,
+    default=None,
+    help="REQUIRED. The Path URL to Burn Cube process cfg file as YAML format.",
+)
+@click.option(
+    "--overwrite/--no-overwrite",
+    default=False,
+    help="Rerun scenes that have already been processed.",
+)
+def stacking_processing(
+    region_id,
+    process_cfg_url,
+    overwrite,
+):
+    """
+    Simple program to load all sub-products (e.g., burn cube, DEA RF and DEA RBR) to get
+    Stacking result as GeoTIFF file.
+    """
+
+    logging_setup()
+
+    process_cfg = helper.load_yaml_remote(process_cfg_url)
+
+    match_products = process_cfg["match_products"]
+    output_folder = process_cfg["output_folder"]
+
+    output_product_name = process_cfg["product"]["name"]
+
+    # activate AWS credential from attached service account
+    helper.get_and_set_aws_credentials()
+
+    # Limit processing to the first 4 files for efficiency (or batch processing)
+    result = process_files(match_products, region_id, output_folder)
+
+    if result:
+        sum_summary, pattern = result
+        # Write the result to a COG file
+
+        pred_tif = "dea_nbic_stacking_" + pattern.replace("/", "") + "_2020.tif",
+
+        write_cog(
+            geo_im=sum_summary,
+            fname=pred_tif,
+            overwrite=True,
+            nodata=-999
+        )
+
+        logger.info("Save result as: " + str(pred_tif))
+
+        s3_file_uri = f"{output_folder}/{output_product_name}/3-0-0/{region_id[:3]}/{region_id[3:]}/{pred_tif}"
+
+        bc_io.upload_object_to_s3(pred_tif, s3_file_uri)
+
+if __name__ == "__main__":
+    stacking_processing()