Merge pull request #66 from GeoscienceAustralia/update_mask_funcs

Update ancillary data loading functions

.github/workflows/dea-intertidal-image.yml

@@ -32,7 +32,7 @@ on:
       - 'codecov.yaml'
 
   release:
-    types: [created, edited, published]
+    types: [edited, published]
 
 permissions:
   id-token: write  # Required for requesting Json web token
@@ -107,13 +107,10 @@ jobs:
           cp ./artifacts/validation.csv ./tests/validation.csv
           cp ./artifacts/README.md ./tests/README.md
 
-      # - name: Setup upterm session
-      #   uses: lhotari/action-upterm@v1
-
       # Commit validation results produced by integration tests back into repo
       - name: Commit validation results into repository
         uses: stefanzweifel/git-auto-commit-action@v4
-        if: github.event_name != 'release'
+        if: github.event_name == 'pull_request'
         with:
           commit_message: Automatically update integration test validation results
           file_pattern: 'tests/validation.jpg tests/validation.csv tests/README.md'

intertidal/elevation.py

@@ -20,8 +20,8 @@
 
 from intertidal.io import (
     load_data,
-    load_aclum,
-    load_topobathy,
+    load_topobathy_mask,
+    load_aclum_mask,
     prepare_for_export,
     tidal_metadata,
     export_dataset_metadata,
@@ -1103,14 +1103,11 @@ def intertidal_cli(
         )
         satellite_ds.load()
 
-        # Load data from GA's AusBathyTopo 250m 2023 Grid
-        topobathy_ds = load_topobathy(
-            dc, satellite_ds, product="ga_ausbathytopo250m_2023", resampling="bilinear"
-        )
-        valid_mask = topobathy_ds.height_depth > -15
+        # Load topobathy mask from GA's AusBathyTopo 250m 2023 Grid
+        topobathy_mask = load_topobathy_mask(dc, satellite_ds.odc.geobox.compat)
 
-        # Load and reclassify for intensive urban land use class only the ABARES ACLUM ds
-        reclassified_aclum = load_aclum(dc, satellite_ds)
+        # Load urban land use class mask from ABARES CLUM
+        reclassified_aclum = load_aclum_mask(dc, satellite_ds.odc.geobox.compat)
 
         # Also load ancillary dataset IDs to use in metadata
         # (both layers are continental continental products with only
@@ -1123,7 +1120,7 @@ def intertidal_cli(
         log.info(f"{run_id}: Calculating Intertidal Elevation")
         ds, tide_m = elevation(
             satellite_ds,
-            valid_mask=valid_mask,
+            valid_mask=topobathy_mask,
             ndwi_thresh=ndwi_thresh,
             min_freq=min_freq,
             max_freq=max_freq,
@@ -1187,7 +1184,7 @@ def intertidal_cli(
         # Prepare data for export
         ds["qa_ndwi_freq"] *= 100  # Convert frequency to %
         ds_prepared = prepare_for_export(ds)  # sets correct dtypes and nodata
-        
+
         # Calculate additional tile-level tidal metadata attributes
         metadata_dict = tidal_metadata(ds)
 

intertidal/io.py

@@ -460,12 +460,15 @@ def load_data(
     return satellite_ds, dss_s2, dss_ls
 
 
-def load_topobathy(
+def load_topobathy_mask(
     dc,
-    satellite_ds,
+    geobox,
     product="ga_ausbathytopo250m_2023",
+    elevation_band="height_depth",
     resampling="bilinear",
     mask_invalid=True,
+    min_threshold=-15,
+    mask_filters=[("dilation", 25)],
 ):
     """
     Loads a topo-bathymetric DEM for the extents of the loaded satellite
@@ -476,38 +479,58 @@ def load_topobathy(
     ----------
     dc : Datacube
         A Datacube instance for loading data.
-    satellite_ds : ndarray
-        The loaded satellite data, used to obtain the spatial extents
-        of the data.
+    geobox : ndarray
+        The GeoBox of the loaded satellite data, used to ensure the data
+        is loaded into the same pixel grid (e.g. resolution, extents, CRS).
     product : str, optional
         The name of the topo-bathymetric DEM product to load from the
         datacube. Defaults to "ga_ausbathytopo250m_2023".
+    elevation_band : str, optional
+        The name of the band containing elevation data. Defaults to 
+        "height_depth".
     resampling : str, optional
         The resampling method to use, by default "bilinear".
     mask_invalid : bool, optional
         Whether to mask invalid/nodata values in the array by setting
         them to NaN, by default True.
+    min_threshold : int or float, optional
+        The elevation value used to create the mask; all pixels with
+        elevations above this value will be given a value of True.
+    mask_filters : list of tuples, optional
+        An optional list of morphological processing steps to pass to 
+        the `mask_cleanup` function. The default is `[("dilation", 25)]`,
+        which will dilate True pixels by a radius of 25 pixels (~250 m).
 
     Returns
     -------
-    topobathy_ds : xarray.Dataset
-        The loaded topo-bathymetric DEM.
+    topobathy_ds : xarray.DataArray
+        An output boolean mask, where True represent pixels to use in the
+        following analysis.
     """
-    topobathy_ds = dc.load(
-        product=product, like=satellite_ds.odc.geobox.compat, resampling=resampling
-    ).squeeze("time")
+    # Load from datacube, reprojecting to GeoBox of input satellite data
+    topobathy_ds = dc.load(product=product, like=geobox, resampling=resampling).squeeze(
+        "time"
+    )
 
     # Mask invalid data
     if mask_invalid:
         topobathy_ds = mask_invalid_data(topobathy_ds)
 
-    return topobathy_ds
+    # Threshold to minumum elevation
+    topobathy_mask = topobathy_ds[elevation_band] > min_threshold
+
+    # If requested, apply cleanup
+    if mask_filters is not None:
+        topobathy_mask = mask_cleanup(topobathy_mask, mask_filters=mask_filters)
+
+    return topobathy_mask
 
 
-def load_aclum(
+def load_aclum_mask(
     dc,
-    satellite_ds,
+    geobox,
     product="abares_clum_2020",
+    class_band="alum_class",
     resampling="nearest",
     mask_invalid=True,
 ):
@@ -521,12 +544,15 @@ def load_aclum(
     ----------
     dc : Datacube
         A Datacube instance for loading data.
-    satellite_ds : ndarray
-        The loaded satellite data, used to obtain the spatial extents
-        of the data.
+    geobox : ndarray
+        The GeoBox of the loaded satellite data, used to ensure the data
+        is loaded into the same pixel grid (e.g. resolution, extents, CRS).
     product : str, optional
         The name of the ABARES land use dataset product to load from the
         datacube. Defaults to "abares_clum_2020".
+    class_band : str, optional
+        The name of the band containing land use class data. Defaults to
+        "alum_class".
     resampling : str, optional
         The resampling method to use, by default "nearest".
     mask_invalid : bool, optional
@@ -535,22 +561,23 @@ def load_aclum(
 
     Returns
     -------
-    reclassified_aclum : xarray.Dataset
-        The ABARES land use mask, summarised to include only two land
-        use classes: 'intensive urban' and 'other'.
+    reclassified_aclum : xarray.DataArray
+        An output boolean mask, where True equals intensive urban and 
+        False equals all other classes.
     """
+    # Load from datacube, reprojecting to GeoBox of input satellite data
     aclum_ds = dc.load(
-        product=product, like=satellite_ds.odc.geobox.compat, resampling=resampling
+        product=product, like=geobox, resampling=resampling
     ).squeeze("time")
 
     # Mask invalid data
     if mask_invalid:
         aclum_ds = mask_invalid_data(aclum_ds)
 
     # Manually isolate the 'intensive urban' land use summary class, set
-    # all other pixels to false. For class definitions, refer to
+    # all other pixels to False. For class definitions, refer to
     # gdata1/data/land_use/ABARES_CLUM/geotiff_clum_50m1220m/Land use, 18-class summary.qml)
-    reclassified_aclum = aclum_ds.alum_class.isin(
+    reclassified_aclum = aclum_ds[class_band].isin(
         [
             500,
             530,
@@ -926,7 +953,7 @@ def export_dataset_metadata(
         Dataset maturity to use for the output dataset. Default is
         "final", can also be "interim".
     additional_metadata : dict, optional
-        An option dictionary containing additional metadata fields to 
+        An option dictionary containing additional metadata fields to
         add to the dataset metadata properties.
     debug : bool, optional
         When true, this will write S3 outputs locally so they can be