Beginning implementation of sentinel-3 preprocessing

Author: Hneuschmidt

efast/s2_processing_openeo.py

@@ -8,6 +8,7 @@ def connect():
     return openeo.connect("https://openeo.dataspace.copernicus.eu/")
 
 
+# TODO move somewhere else, not specific to sentinel-2
 class TestArea:
     # aoi_wkt = "POINT (-15.432283 15.402828)"
     directions = ["west", "south", "east", "north"]
@@ -19,7 +20,12 @@ def __init__(
         *,
         bbox: Mapping[str, float] = bbox,
         s2_bands: Sequence[str] = ["B02", "B03", "B04", "B8A", "SCL"],
-        s3_bands: Sequence[str] = ["SDR_Oa04", "SDR_Oa06", "SDR_Oa08", "SDR_Oa17"],
+        s3_bands: Sequence[str] = [
+            "Syn_Oa04_reflectance",
+            "Syn_Oa06_reflectance",
+            "Syn_Oa08_reflectance",
+            "Syn_Oa17_reflectance",
+            ],
         temporal_extent: Sequence[str] = ["2022-06-01", "2022-06-30"],
     ) -> None:
         self.bbox = bbox
@@ -35,6 +41,14 @@ def get_s2_cube(self, connection):
             bands=self.s2_bands,
         )
 
+    def get_s3_cube(self, connection):
+        return connection.load_collection(
+            "SENTINEL3_SYN_L2_SYN",
+            spatial_extent=self.bbox,
+            temporal_extent=self.temporal_extent,
+            bands=self.s3_bands,
+        )
+
 
 def extract_cloud_mask(cube: openeo.DataCube):
     scl = cube.filter_bands(["SCL"])

efast/s3_processing_openeo.py

@@ -0,0 +1,7 @@
+import openeo
+
+def binning_s3():
+    pass
+
+
+

tests/test_preprocessing_openeo.py

@@ -33,7 +33,7 @@
 TEST_DATE = "20220618"
 TEST_DATE_DASH = "2022-06-18"
 
-SKIP_LOCAL = True
+SKIP_LOCAL = False
 SMALL_AREA = True
 
 
@@ -181,7 +181,8 @@ def extract_epsg_code_from_rasterio_crs(crs: rasterio.CRS) -> int:
 
 def test_data_acquisition_s3():
     with create_temp_dir_and_copy_files(
-        TEST_DATA_S3, sub="raw/", pattern=f"raw/*SY_2_SYN____{TEST_DATE}*"
+        TEST_DATA_S3, sub="raw/", pattern=f"raw/*SY_2_SYN____2022061*"
+        #TEST_DATA_S3, sub="raw/", pattern=f"raw/*SY_2_SYN____*"
     ) as tmp:
         inner_data_acquisition_s3(tmp)
 
@@ -201,15 +202,18 @@ def inner_data_acquisition_s3(tmpdir):
     }
 
     if SMALL_AREA:
-        dist = 900
+        dist = 3600
         bounds["east"] = bounds["west"] + dist
         bounds["north"] = bounds["south"] + dist
 
     # reference
 
     s3_binning_dir = tmp / "binning"
+    s3_composites_dir = tmp / "composites"
     s3_download_dir = tmp / "raw"
+
     s3_binning_dir.mkdir()
+    s3_composites_dir.mkdir()
     footprint = transform_bounds_to_wkt(
         bounds
     )  # TODO probably needs to be converted to wkt
@@ -229,6 +233,14 @@ def inner_data_acquisition_s3(tmpdir):
             snap_parallelization=1,  # TODO more than 1?
         )
 
+        s3_processing.produce_median_composite(
+            s3_binning_dir,
+            s3_composites_dir,
+            mosaic_days=100,
+            step=2,
+            s3_bands=None,
+        )
+
         shutil.copytree(s3_binning_dir, download_dir, dirs_exist_ok=True)
 
     # openeo
@@ -283,3 +295,14 @@ def transform_bounds_to_wkt(bounds: dict):
         minx=minx_wgs84, miny=miny_wgs84, maxx=maxx_wgs84, maxy=maxy_wgs84
     )
     return wkt.dumps(bbox)
+
+METADATA_UDF = openeo.UDF("""
+import numpy as np
+import xarray as xr
+from openeo.udf import XarrayDataCube
+def apply_datacube(cube: XarrayDataCube, context: dict) -> XarrayDataCube:
+    array = cube.get_array()
+    array = array < {tolerance_percentage}
+    #return XarrayDataCube(xr.DataArray(array, dims=["t", "x", "y", "bands"]))
+    return XarrayDataCube(xr.DataArray(array, dims=["bands", "x", "y"]))
+""")