def test_prepare_le07_l2_c2(
tmp_path: Path,
le07_l2_c2_folder: Path,
):
"""Support a functionality baseline for the enhancements to expand landsat
prepare (YAML) logic to support USGS level 2 - PR#159:
LE07 C2 L2."""
assert le07_l2_c2_folder.exists(), "Test data missing(?)"
output_path = tmp_path
expected_metadata_path = (
output_path / "090" / "084" /
"LE07_L2SP_090084_20210331_20210426_02_T1.odc-metadata.yaml")
check_prepare_outputs(
invoke_script=landsat_l1_prepare.main,
run_args=[
"--output-base",
output_path,
"--producer",
"usgs.gov",
le07_l2_c2_folder,
],
expected_doc=expected_le07_l2_c2_folder(),
expected_metadata_path=expected_metadata_path,
)
def test_prepare_l8_l1_tarball_with_source(tmp_path: Path, l1_ls8_folder: Path,
ls8_telemetry_path,
l1_ls8_ga_expected: Dict):
"""Run prepare script with a source telemetry data and unique producer."""
assert l1_ls8_folder.exists(), "Test data missing(?)"
output_path = tmp_path
expected_metadata_path = (
output_path / "090" / "084" /
"LC08_L1TP_090084_20160121_20170405_01_T1.odc-metadata.yaml")
check_prepare_outputs(
invoke_script=landsat_l1_prepare.main,
run_args=[
"--output-base",
output_path,
"--producer",
"ga.gov.au",
"--source",
ls8_telemetry_path,
l1_ls8_folder,
],
expected_doc=l1_ls8_ga_expected,
expected_metadata_path=expected_metadata_path,
)
def test_prepare_l7_l1_usgs_tarball(l1_ls7_tarball: Path,
l1_ls7_tarball_md_expected: Dict):
assert l1_ls7_tarball.exists(), "Test data missing(?)"
expected_metadata_path = (
l1_ls7_tarball.parent /
"LE07_L1TP_104078_20130429_20161124_01_T1.odc-metadata.yaml")
check_prepare_outputs(
invoke_script=landsat_l1_prepare.main,
run_args=[str(l1_ls7_tarball)],
expected_doc=l1_ls7_tarball_md_expected,
expected_metadata_path=expected_metadata_path,
)
def test_prepare_l8_l1_usgs_tarball(l1_ls8_folder, l1_ls8_folder_md_expected):
assert l1_ls8_folder.exists(), "Test data missing(?)"
# No output path defined,so it will default to being a sibling to the input.
expected_metadata_path = (
l1_ls8_folder.parent /
"LC08_L1TP_090084_20160121_20170405_01_T1.odc-metadata.yaml")
assert not expected_metadata_path.exists()
check_prepare_outputs(
invoke_script=landsat_l1_prepare.main,
run_args=[str(l1_ls8_folder)],
expected_doc=l1_ls8_folder_md_expected,
expected_metadata_path=expected_metadata_path,
)
def test_run(tmp_path, expected_dataset_document):
"""
Run prepare on our test input scene, and check the created metadata matches expected.
"""
shutil.copy(DATASET_PATH, tmp_path)
expected_metadata_path = tmp_path / (
"S2B_MSIL1C_20201011T000249_N0209_R030_T55HFA_20201011T011446.odc-metadata.yaml"
)
check_prepare_outputs(
invoke_script=sentinel_l1_prepare.main,
run_args=[
tmp_path / DATASET_PATH.name,
],
expected_doc=expected_dataset_document,
expected_metadata_path=expected_metadata_path,
)
def test_sinergise_sentinel_l1(tmp_path, expected_dataset_document):
"""
Run prepare on our test dataset, and check the out metadata doc matches.
"""
work_dir = tmp_path / DATASET_DIR.name
shutil.copytree(DATASET_DIR, work_dir)
output_yaml_path = (
work_dir /
"S2B_MSIL1C_20201011T000249_N0209_R030_T55HFA_20201011T011446.odc-metadata.yaml"
)
check_prepare_outputs(
invoke_script=sentinel_l1_prepare.main,
run_args=[
work_dir,
],
expected_doc=expected_dataset_document,
expected_metadata_path=output_yaml_path,
)
def test_generate_expected_outputs(
tmp_path: Path, dataset_input_output: Tuple[Path, Dict, Path]
):
"""
Run prepare on our test input scenes, and check the created metadata matches expected.
"""
(
input_dataset_path,
expected_metadata_doc,
expected_metadata_path,
) = dataset_input_output
check_prepare_outputs(
invoke_script=sentinel_l1_prepare.main,
run_args=[
input_dataset_path,
],
expected_doc=expected_metadata_doc,
expected_metadata_path=expected_metadata_path,
)
def test_prepare_l5_l1_usgs_tarball(tmp_path: Path,
l1_ls5_tarball_md_expected: Dict,
l1_ls5_tarball: Path):
assert l1_ls5_tarball.exists(), "Test data missing(?)"
output_path: Path = tmp_path / "out"
output_path.mkdir()
# When specifying an output base path it will create path/row subfolders within it.
expected_metadata_path = (
output_path / "090" / "085" /
"LT05_L1TP_090085_19970406_20161231_01_T1.odc-metadata.yaml")
check_prepare_outputs(
invoke_script=landsat_l1_prepare.main,
run_args=["--output-base",
str(output_path),
str(l1_ls5_tarball)],
expected_doc=l1_ls5_tarball_md_expected,
expected_metadata_path=expected_metadata_path,
)
def test_prepare_l9_l1_c2(tmp_path: Path, l1_ls9_tarball: Path,
l9_expected: Dict):
"""Run prepare script with a source telemetry data and unique producer."""
assert l1_ls9_tarball.exists(), "Test data missing(?)"
output_path = tmp_path
check_prepare_outputs(
invoke_script=landsat_l1_prepare.main,
run_args=[
"--output-base",
output_path,
"--producer",
"usgs.gov",
l1_ls9_tarball,
],
expected_doc=l9_expected,
expected_metadata_path=(
output_path / "112" / "081" /
"LC09_L1TP_112081_20220209_20220209_02_T1.odc-metadata.yaml"),
)
def test_prepare_s2a_l1c_safe(tmpdir):
assert L1_ZIPFILE_PATH.exists(), "Test data missing(?)"
output_path = Path(tmpdir)
# make a folder and extract contents
output_path.mkdir(parents=True, exist_ok=True)
with zipfile.ZipFile(L1_ZIPFILE_PATH, "r") as zipped_data:
zipped_data.extractall(output_path)
expected_metadata_path = (
output_path /
"S2B_OPER_MSI_L1C_TL_EPAE_20180617T013729_A006677_T55JGF_N02.06.yaml")
def path_offset(offset: str):
return "s3://sentinel-s2-l1c/tiles/55/J/GF/2018/6/17/0/" + offset
expected_doc = {
"acquisition": {
"groundstation": {
"code": "EPA_"
}
},
"archiving_time":
"2018-06-17T02:06:21.973943Z",
"creation_dt":
"2018-06-17T01:27:55Z",
"checksum_sha1":
"bfac5eea3ec0c6c70816ddb97592dfd4d8a389e2",
"datastrip_id":
"S2B_OPER_MSI_L1C_DS_EPAE_20180617T013729_S20180617T001107_N02.06",
"datastrip_metadata":
("http://sentinel-s2-l1c.s3-website.eu-central-1.amazonaws.com"
"/#products/2018/6/17/S2B_MSIL1C_20180617T001109_N0206_R073_"
"T55JGF_20180617T013729/datastrip/0"),
"datatake_id": {
"datatakeIdentifier": "GS2B_20180617T001109_006677_N02.06",
"metadataLevel": "Brief",
},
"datatake_sensing_start":
"2018-06-17T00:11:09.024Z",
"datatake_type":
"INS-NOBS",
"downlink_priority":
"NOMINAL",
"extent": {
"center_dt": "2018-06-17T00:11:07.458Z",
"coord": {
"ll": {
"lat": -31.705779763545088,
"lon": 149.11005323208184
},
"lr": {
"lat": -31.681364358256744,
"lon": 150.26738162306842
},
"ul": {
"lat": -30.715729325189965,
"lon": 149.08817422152293
},
"ur": {
"lat": -30.6922425616759,
"lon": 150.23354450086148
},
},
},
"format": {
"name": "JPEG2000"
},
"grid_spatial": {
"projection": {
"geo_ref_points": {
"ll": {
"x": 699960,
"y": 6490240
},
"lr": {
"x": 809760,
"y": 6490240
},
"ul": {
"x": 699960,
"y": 6600040
},
"ur": {
"x": 809760,
"y": 6600040
},
},
"spatial_reference": "EPSG:32755",
"valid_data": {
"coordinates": [[
[781030.5157393045, 6490240.0],
[802194.5431029584, 6568088.898470836],
[807815.3469119765, 6599599.456501017],
[807233.663302242, 6600040.0],
[699960.0, 6600040.0],
[699960.0, 6490240.0],
[781030.5157393045, 6490240.0],
]],
"type":
"Polygon",
},
}
},
"id":
"e6e14ee5-c431-559d-8b07-e387648d06c6",
"image": {
"bands": {
"B01": {
"layer": 1,
"path": path_offset("B01.jp2")
},
"B02": {
"layer": 1,
"path": path_offset("B02.jp2")
},
"B03": {
"layer": 1,
"path": path_offset("B03.jp2")
},
"B04": {
"layer": 1,
"path": path_offset("B04.jp2")
},
"B05": {
"layer": 1,
"path": path_offset("B05.jp2")
},
"B06": {
"layer": 1,
"path": path_offset("B06.jp2")
},
"B07": {
"layer": 1,
"path": path_offset("B07.jp2")
},
"B08": {
"layer": 1,
"path": path_offset("B08.jp2")
},
"B09": {
"layer": 1,
"path": path_offset("B09.jp2")
},
"B10": {
"layer": 1,
"path": path_offset("B10.jp2")
},
"B11": {
"layer": 1,
"path": path_offset("B11.jp2")
},
"B12": {
"layer": 1,
"path": path_offset("B12.jp2")
},
"B8A": {
"layer": 1,
"path": path_offset("B8A.jp2")
},
},
"cloud_cover_percentage":
41.1953,
"degraded_anc_data_percentage":
0.0,
"degraded_msi_data_percentage":
0.0,
"format_quality_flag":
"PASSED",
"general_quality_flag":
"PASSED",
"geometric_quality_flag":
"PASSED",
"radiometric_quality_flag":
"PASSED",
"reflectance_conversion":
"0.969545500936321",
"sensor_quality_flag":
"PASSED",
"solar_irradiance": [],
"sun_azimuth":
28.329529500752,
"sun_elevation":
60.25415978281,
"tile_reference":
"N02.06",
"viewing_angles": [
{
"bandId": "0",
"measurement": {
"azimuth": {
"value": 285.033757307864
},
"zenith": {
"value": 8.48756458553399
},
},
"unit": "degree",
},
{
"bandId": "9",
"measurement": {
"azimuth": {
"value": 285.075607281345
},
"zenith": {
"value": 8.52241368394389
},
},
"unit": "degree",
},
{
"bandId": "10",
"measurement": {
"azimuth": {
"value": 284.793804242023
},
"zenith": {
"value": 8.34345092249542
},
},
"unit": "degree",
},
{
"bandId": "1",
"measurement": {
"azimuth": {
"value": 284.793733737481
},
"zenith": {
"value": 8.29509641932038
},
},
"unit": "degree",
},
{
"bandId": "2",
"measurement": {
"azimuth": {
"value": 284.851677995258
},
"zenith": {
"value": 8.32126064250559
},
},
"unit": "degree",
},
{
"bandId": "3",
"measurement": {
"azimuth": {
"value": 284.909295311577
},
"zenith": {
"value": 8.3544279324201
},
},
"unit": "degree",
},
{
"bandId": "4",
"measurement": {
"azimuth": {
"value": 284.933467772596
},
"zenith": {
"value": 8.37600138776781
},
},
"unit": "degree",
},
{
"bandId": "5",
"measurement": {
"azimuth": {
"value": 284.973394067973
},
"zenith": {
"value": 8.40018017679447
},
},
"unit": "degree",
},
{
"bandId": "6",
"measurement": {
"azimuth": {
"value": 285.002316322296
},
"zenith": {
"value": 8.42684047592471
},
},
"unit": "degree",
},
{
"bandId": "7",
"measurement": {
"azimuth": {
"value": 284.82134822338
},
"zenith": {
"value": 8.30688902336585
},
},
"unit": "degree",
},
{
"bandId": "8",
"measurement": {
"azimuth": {
"value": 285.068419119347
},
"zenith": {
"value": 8.45522377449714
},
},
"unit": "degree",
},
{
"bandId": "11",
"measurement": {
"azimuth": {
"value": 284.889987613982
},
"zenith": {
"value": 8.39599518380445
},
},
"unit": "degree",
},
{
"bandId": "12",
"measurement": {
"azimuth": {
"value": 284.999750610317
},
"zenith": {
"value": 8.46178406516545
},
},
"unit": "degree",
},
],
},
"instrument": {
"name": "MSI"
},
"lineage": {
"source_datasets": {}
},
"orbit":
"73",
"orbit_direction":
"DESCENDING",
"platform": {
"code": "SENTINEL_2B"
},
"processing_level":
"Level-1C",
"product_format": {
"name": "s2_aws_pds"
},
"product_type":
"level1",
"size_bytes":
1292575,
"tile_id":
"S2B_OPER_MSI_L1C_TL_EPAE_20180617T013729_A006677_T55JGF_N02.06",
}
check_prepare_outputs(
invoke_script=s2_l1c_aws_pds_prepare.main,
run_args=[
"--output",
str(output_path),
str(output_path /
"S2B_OPER_MSI_L1C_TL_EPAE_20180617T013729_A006677_T55JGF_N02.06"
),
],
expected_doc=expected_doc,
expected_metadata_path=expected_metadata_path,
)
def test_filter_folder_structure_info(
tmp_path: Path, dataset_input_output: Tuple[Path, Dict, Path]
):
(
input_dataset_path,
expected_metadata_doc,
expected_metadata_path,
) = dataset_input_output
metadata_offset = expected_metadata_path.relative_to(input_dataset_path.parent)
input_folder = tmp_path / "inputs"
subfolders = "2019/2019-01/25S125E-30S130"
# Move input data into subfolder hierarchy.
dataset_folder = input_folder / "L1C" / subfolders
dataset_folder.mkdir(parents=True)
new_input_dataset_path = dataset_folder / input_dataset_path.name
input_dataset_path.rename(new_input_dataset_path)
input_dataset_path = new_input_dataset_path
# Expect metadata files to be stored in an identical hierarchy in a different output folder
output_folder = tmp_path / "output"
output_folder.mkdir(parents=True)
expected_metadata_path = output_folder / subfolders / metadata_offset
# Our output metadata is in a different place than the data, so we expect it to
# embed the true location in the metadata (by default)
if input_dataset_path.is_dir():
expected_metadata_doc[
"location"
] = f"file://{input_dataset_path.as_posix()}/tileInfo.json"
else:
expected_metadata_doc["location"] = f"zip:{input_dataset_path}!/"
# A file with the correct region
regions_file = tmp_path / "our-regions.txt"
regions_file.write_text("\n".join(["55HFA", "55HFB"]))
# A file that doesn't have our region.
non_regions_file = tmp_path / "our-non-regions.txt"
non_regions_file.write_text("\n".join(["55HFB", "55HFC"]))
# Sanity check: no output exists yet.
assert not expected_metadata_path.exists()
# Run with filters that skips this dataset:
# (it should do nothing)
# Whitelist including the correct region
res = run_prepare_cli(
sentinel_l1_prepare.main,
# It contains our region, so it should filter!
"--only-regions-in-file",
regions_file,
# "Put the output in a different location":
"--output-base",
output_folder,
input_dataset_path,
)
assert (
expected_metadata_path.exists()
), f"Expected dataset to be processed (it's within the region file)! {res.output}"
expected_metadata_path.unlink()
# Run with a region list that doesn't include our dataset region.
res = run_prepare_cli(
sentinel_l1_prepare.main,
# It contains our region, so it should filter!
"--only-regions-in-file",
non_regions_file,
# "Put the output in a different location":
"--output-base",
output_folder,
input_dataset_path,
)
assert (
not expected_metadata_path.exists()
), f"Expected dataset to be filtered out! {res.output}"
# Filter the time period
res = run_prepare_cli(
sentinel_l1_prepare.main,
# After our time period, so it should filter!
"--after-month",
"2019-03",
# "Put the output in a different location":
"--output-base",
output_folder,
input_dataset_path,
)
assert (
not expected_metadata_path.exists()
), f"Expected dataset to be filtered out! {res.output}"
# Filter the time period
res = run_prepare_cli(
sentinel_l1_prepare.main,
# Before our time period, so it should filter!
"--before-month",
"2018-03",
# "Put the output in a different location":
"--output-base",
output_folder,
input_dataset_path,
)
assert (
not expected_metadata_path.exists()
), f"Expected dataset to be filtered out! {res.output}"
# Now run for real, expect an output.
check_prepare_outputs(
invoke_script=sentinel_l1_prepare.main,
run_args=[
# Before our time period, so it should be fine!
"--after-month",
"2018-12",
# "Put the output in a different location":
"--output-base",
output_folder,
input_dataset_path,
],
expected_doc=expected_metadata_doc,
expected_metadata_path=expected_metadata_path,
)
# Now run again using a folder input, not an exact zip input.
# (so it has to scan for datasets)
shutil.rmtree(output_folder)
output_folder.mkdir()
# Now run for real, expect an output.
check_prepare_outputs(
invoke_script=sentinel_l1_prepare.main,
run_args=[
# "Put the output in a different location":
"--output-base",
output_folder,
# The base folder, so it has to scan for zip files itself!
input_folder,
],
expected_doc=expected_metadata_doc,
expected_metadata_path=expected_metadata_path,
)
def test_prepare_l8_l1_c2(tmp_path: Path, l1_c2_ls8_folder: Path):
"""Run prepare script with a source telemetry data and unique producer."""
assert l1_c2_ls8_folder.exists(), "Test data missing(?)"
output_path = tmp_path
expected_metadata_path = (
output_path / "089" / "074" /
"LC08_L1GT_089074_20220506_20220512_02_T2.odc-metadata.yaml")
expected_doc = {
"$schema": "https://schemas.opendatacube.org/dataset",
"id": "5e1359de-0f91-5988-a6f0-8a0a840906f4",
"label": "usgs_ls8c_level1_2-0-20220512_089074_2022-05-06",
"product": {
"name": "usgs_ls8c_level1_2",
"href":
"https://collections.dea.ga.gov.au/product/usgs_ls8c_level1_2",
},
"crs": "epsg:32656",
"grids": {
"default": {
"shape": [60, 60],
"transform": [
3860.5,
0.0,
594285.0,
0.0,
-3910.5,
-2121285.0,
0.0,
0.0,
1.0,
],
},
"panchromatic": {
"shape": [60, 60],
"transform": [
3860.2500000000005,
0.0,
594292.5,
0.0,
-3910.25,
-2121292.5,
0.0,
0.0,
1.0,
],
},
},
"geometry": {
"type":
"Polygon",
"coordinates": ((
(635871.100911986, -2328431.8044824763),
(598807.3537167514, -2315758.4765276713),
(594285.0, -2314216.125490317),
(594285.0, -2294479.549612592),
(629132.1230216483, -2128210.3416854665),
(634001.1369104853, -2121285.0),
(671771.6827861228, -2121285.0),
(759108.8670950294, -2143693.8957929504),
(819064.1631236447, -2156587.0374096073),
(824424.9683929395, -2160452.642015061),
(825915.0, -2160834.95297774),
(825915.0, -2197333.359107589),
(818095.1372109791, -2231658.3131009457),
(784506.5705934291, -2355915.0),
(764094.013739199, -2355915.0),
(647454.7800689514, -2332349.7060506954),
(636125.9731110331, -2328486.0106703877),
(635871.100911986, -2328431.8044824763),
), ),
},
"properties": {
"datetime": "2022-05-06T23:39:59.285133",
"eo:cloud_cover": 86.35,
"eo:gsd": 15.0,
"eo:instrument": "OLI_TIRS",
"eo:platform": "landsat-8",
"eo:sun_azimuth": 39.80724521,
"eo:sun_elevation": 43.24426868,
"landsat:collection_category": "T2",
"landsat:collection_number": 2,
"landsat:data_type": "L1GT",
"landsat:landsat_product_id":
"LC08_L1GT_089074_20220506_20220512_02_T2",
"landsat:landsat_scene_id": "LC80890742022126LGN00",
"landsat:processing_software_version": "LPGS_15.6.0",
"landsat:station_id": "LGN",
"landsat:wrs_path": 89,
"landsat:wrs_row": 74,
"odc:dataset_version": "2.0.20220512",
"odc:file_format": "GeoTIFF",
"odc:processing_datetime": "2022-05-12T14:00:17",
"odc:producer": "usgs.gov",
"odc:product_family": "level1",
"odc:region_code": "089074",
},
"measurements": {
"blue": {
"path": "LC08_L1GT_089074_20220506_20220512_02_T2_B2.TIF"
},
"cirrus": {
"path": "LC08_L1GT_089074_20220506_20220512_02_T2_B9.TIF"
},
"coastal_aerosol": {
"path": "LC08_L1GT_089074_20220506_20220512_02_T2_B1.TIF"
},
"green": {
"path": "LC08_L1GT_089074_20220506_20220512_02_T2_B3.TIF"
},
"lwir_1": {
"path": "LC08_L1GT_089074_20220506_20220512_02_T2_B10.TIF"
},
"lwir_2": {
"path": "LC08_L1GT_089074_20220506_20220512_02_T2_B11.TIF"
},
"nir": {
"path": "LC08_L1GT_089074_20220506_20220512_02_T2_B5.TIF"
},
"panchromatic": {
"path": "LC08_L1GT_089074_20220506_20220512_02_T2_B8.TIF",
"grid": "panchromatic",
},
"qa_radsat": {
"path":
"LC08_L1GT_089074_20220506_20220512_02_T2_QA_RADSAT.TIF"
},
"quality": {
"path": "LC08_L1GT_089074_20220506_20220512_02_T2_QA_PIXEL.TIF"
},
"red": {
"path": "LC08_L1GT_089074_20220506_20220512_02_T2_B4.TIF"
},
"solar_azimuth": {
"path": "LC08_L1GT_089074_20220506_20220512_02_T2_SAA.TIF"
},
"solar_zenith": {
"path": "LC08_L1GT_089074_20220506_20220512_02_T2_SZA.TIF"
},
"swir_1": {
"path": "LC08_L1GT_089074_20220506_20220512_02_T2_B6.TIF"
},
"swir_2": {
"path": "LC08_L1GT_089074_20220506_20220512_02_T2_B7.TIF"
},
"view_azimuth": {
"path": "LC08_L1GT_089074_20220506_20220512_02_T2_VAA.TIF"
},
"view_zenith": {
"path": "LC08_L1GT_089074_20220506_20220512_02_T2_VZA.TIF"
},
},
"accessories": {
"metadata:landsat_mtl": {
"path": "LC08_L1GT_089074_20220506_20220512_02_T2_MTL.txt"
}
},
"lineage": {},
}
check_prepare_outputs(
invoke_script=landsat_l1_prepare.main,
run_args=[
"--output-base",
output_path,
"--producer",
"usgs.gov",
l1_c2_ls8_folder,
],
expected_doc=expected_doc,
expected_metadata_path=expected_metadata_path,
)
def test_prepare_s2a_l1c_safe(tmpdir):
assert L1_ZIPFILE_PATH.exists(), "Test data missing(?)"
output_path = Path(tmpdir)
expected_metadata_path = (
output_path
/ "S2A_MSIL1C_20180629T000241_N0206_R030_T56JMM_20180629T012042.zip.yaml"
)
granule_path = (
"/S2A_MSIL1C_20180629T000241_N0206_R030_T56JMM_20180629T012042.SAFE"
"/GRANULE/L1C_T56JMM_A015757_20180629T000241/"
)
def path_offset(offset: str, granule_path=granule_path):
return "zip://" + str(L1_ZIPFILE_PATH.absolute()) + "!" + granule_path + offset
expected_doc = {
"acquisition": {"groundstation": {"code": "EPA_"}},
"archiving_time": "2018-06-29T03:44:20.252114Z",
"checksum_sha1": "908571e2cdd54174fb051272be34fe73f6efb9a5",
"creation_dt": "2018-06-29T01:20:42.000000Z",
"datastrip_id": "S2A_OPER_MSI_L1C_DS_EPAE_20180629T012042_S20180629T000241_N02.06",
"datastrip_metadata": (
"S2A_MSIL1C_20180629T000241_N0206_R030_T56JMM_20180629T012042.SAFE"
"/DATASTRIP/DS_EPAE_20180629T012042_S20180629T000241/MTD_DS.xml"
),
"datatake_id": {"datatakeIdentifier": "GS2A_20180629T000241_015757_N02.06"},
"datatake_sensing_start": "2018-06-29T00:02:41.024Z",
"datatake_type": "INS-NOBS",
"downlink_priority": "NOMINAL",
"extent": {
"center_dt": "2018-06-29T00:02:41.461Z",
"coord": {
"ll": {"lat": -30.81709901611161, "lon": 151.95410707081012},
"lr": {"lat": -30.82128003446065, "lon": 153.10204544208213},
"ul": {"lat": -29.82640952246035, "lon": 151.9645797990478},
"ur": {"lat": -29.83042869279505, "lon": 153.10102341983713},
},
"from_dt": "2018-06-29T00:02:41.024Z",
"to_dt": "2018-06-29T00:02:41.024Z",
},
"format": {"name": "JPEG2000"},
"grid_spatial": {
"projection": {
"geo_ref_points": {
"ll": {"x": 399960, "y": 6590200},
"lr": {"x": 509760, "y": 6590200},
"ul": {"x": 399960, "y": 6700000},
"ur": {"x": 509760, "y": 6700000},
},
"spatial_reference": "EPSG:32756",
"valid_data": {
"coordinates": [
[
[470826.97121060337, 6590200.0],
[475130.9086383948, 6598904.030892345],
[493180.2237068879, 6681630.058289605],
[493214.79452054796, 6700000.0],
[399960.0, 6700000.0],
[399960.0, 6590200.0],
[470826.97121060337, 6590200.0],
]
],
"type": "Polygon",
},
}
},
"id": "d6004c21-171f-5a76-8e4f-2de359af506a",
"image": {
"bands": {
"B01": {
"layer": 1,
"path": path_offset("IMG_DATA/T56JMM_20180629T000241_B01.jp2"),
},
"B02": {
"layer": 1,
"path": path_offset("IMG_DATA/T56JMM_20180629T000241_B02.jp2"),
},
"B03": {
"layer": 1,
"path": path_offset("IMG_DATA/T56JMM_20180629T000241_B03.jp2"),
},
"B04": {
"layer": 1,
"path": path_offset("IMG_DATA/T56JMM_20180629T000241_B04.jp2"),
},
"B05": {
"layer": 1,
"path": path_offset("IMG_DATA/T56JMM_20180629T000241_B05.jp2"),
},
"B06": {
"layer": 1,
"path": path_offset("IMG_DATA/T56JMM_20180629T000241_B06.jp2"),
},
"B07": {
"layer": 1,
"path": path_offset("IMG_DATA/T56JMM_20180629T000241_B07.jp2"),
},
"B08": {
"layer": 1,
"path": path_offset("IMG_DATA/T56JMM_20180629T000241_B08.jp2"),
},
"B09": {
"layer": 1,
"path": path_offset("IMG_DATA/T56JMM_20180629T000241_B09.jp2"),
},
"B10": {
"layer": 1,
"path": path_offset("IMG_DATA/T56JMM_20180629T000241_B10.jp2"),
},
"B11": {
"layer": 1,
"path": path_offset("IMG_DATA/T56JMM_20180629T000241_B11.jp2"),
},
"B12": {
"layer": 1,
"path": path_offset("IMG_DATA/T56JMM_20180629T000241_B12.jp2"),
},
"B8A": {
"layer": 1,
"path": path_offset("IMG_DATA/T56JMM_20180629T000241_B8A.jp2"),
},
"PVI": {
"layer": 1,
"path": path_offset("QI_DATA/T56JMM_20180629T000241_PVI.jp2"),
},
"TCI": {
"layer": 1,
"path": path_offset("IMG_DATA/T56JMM_20180629T000241_TCI.jp2"),
},
},
"cloud_cover_percentage": 0.0,
"degraded_anc_data_percentage": 0.0,
"degraded_msi_data_percentage": 0.0,
"format_quality_flag": "",
"general_quality_flag": "",
"geometric_quality_flag": "",
"null_value": "0",
"radiometric_quality_flag": "",
"reflectance_conversion": "0.967798898595979",
"saturated": "65535",
"sensor_quality_flag": "",
"solar_irradiance": [
{"bandId": "0", "unit": "W/m²/µm", "value": "1884.69"},
{"bandId": "1", "unit": "W/m²/µm", "value": "1959.72"},
{"bandId": "2", "unit": "W/m²/µm", "value": "1823.24"},
{"bandId": "3", "unit": "W/m²/µm", "value": "1512.06"},
{"bandId": "4", "unit": "W/m²/µm", "value": "1424.64"},
{"bandId": "5", "unit": "W/m²/µm", "value": "1287.61"},
{"bandId": "6", "unit": "W/m²/µm", "value": "1162.08"},
{"bandId": "7", "unit": "W/m²/µm", "value": "1041.63"},
{"bandId": "8", "unit": "W/m²/µm", "value": "955.32"},
{"bandId": "9", "unit": "W/m²/µm", "value": "812.92"},
{"bandId": "10", "unit": "W/m²/µm", "value": "367.15"},
{"bandId": "11", "unit": "W/m²/µm", "value": "245.59"},
{"bandId": "12", "unit": "W/m²/µm", "value": "85.25"},
],
"sun_azimuth": 28.9784209875988,
"sun_elevation": 59.5161129280706,
"tile_reference": "N02.06",
"viewing_angles": [
{
"bandId": "0",
"measurement": {
"azimuth": {"value": 287.743300570742},
"zenith": {"value": 8.90682426360539},
},
"unit": "degree",
},
{
"bandId": "9",
"measurement": {
"azimuth": {"value": 287.913358161721},
"zenith": {"value": 8.93763578589198},
},
"unit": "degree",
},
{
"bandId": "10",
"measurement": {
"azimuth": {"value": 286.62269660653},
"zenith": {"value": 8.77437299338626},
},
"unit": "degree",
},
{
"bandId": "1",
"measurement": {
"azimuth": {"value": 286.085976995274},
"zenith": {"value": 8.70023786261715},
},
"unit": "degree",
},
{
"bandId": "2",
"measurement": {
"azimuth": {"value": 286.471239179063},
"zenith": {"value": 8.72476018739389},
},
"unit": "degree",
},
{
"bandId": "3",
"measurement": {
"azimuth": {"value": 286.832768592131},
"zenith": {"value": 8.75574267151839},
},
"unit": "degree",
},
{
"bandId": "4",
"measurement": {
"azimuth": {"value": 287.013584765891},
"zenith": {"value": 8.77685536841587},
},
"unit": "degree",
},
{
"bandId": "5",
"measurement": {
"azimuth": {"value": 287.207324001684},
"zenith": {"value": 8.80050900146543},
},
"unit": "degree",
},
{
"bandId": "6",
"measurement": {
"azimuth": {"value": 287.400419388821},
"zenith": {"value": 8.8344918122903},
},
"unit": "degree",
},
{
"bandId": "7",
"measurement": {
"azimuth": {"value": 286.272771889735},
"zenith": {"value": 8.71220887022109},
},
"unit": "degree",
},
{
"bandId": "8",
"measurement": {
"azimuth": {"value": 287.592709087249},
"zenith": {"value": 8.86277189674952},
},
"unit": "degree",
},
{
"bandId": "11",
"measurement": {
"azimuth": {"value": 287.100489102096},
"zenith": {"value": 8.84204098088515},
},
"unit": "degree",
},
{
"bandId": "12",
"measurement": {
"azimuth": {"value": 287.498739900102},
"zenith": {"value": 8.90079212851159},
},
"unit": "degree",
},
],
},
"instrument": {"name": "MSI"},
"lineage": {"source_datasets": {}},
"orbit": "30",
"orbit_direction": "DESCENDING",
"platform": {"code": "Sentinel-2A"},
"processing_baseline": "02.06",
"processing_level": "Level-1C",
"product_format": {"name": "SAFE_COMPACT"},
"product_type": "S2MSI1C",
"product_uri": "S2A_MSIL1C_20180629T000241_N0206_R030_T56JMM_20180629T012042.SAFE",
"size_bytes": 1837225,
"tile_id": "S2A_OPER_MSI_L1C_TL_EPAE_20180629T012042_A015757_T56JMM_N02.06",
}
check_prepare_outputs(
invoke_script=s2_prepare_cophub_zip.main,
run_args=[
"--newer-than",
"1970-01-01",
"--output",
str(output_path),
str(L1_ZIPFILE_PATH),
],
expected_doc=expected_doc,
expected_metadata_path=expected_metadata_path,
)
