COUNT_LOW_39_149.65_-21.55_20050101_20170101_PER

creation_dt 2017-06-14T02:25:32.317081 creation_time 2017-06-14 02:25:32 format NetCDF id 2d3b79ad-df94-4c17-9d2a-4c07fda8d30b instrument • label • lat -22.017 to -21.37 lon 148.757 to 149.931 platform • product_type tidal_composite time 2000-01-01 00:00:00 to 2016-10-31 00:00:00

Location 🔗

file:///g/data/fk4/datacube/002/HLTC/HLTC_2_0/netcdf/COUNT_LOW_39_149.65_-21.55_20050101_20170101_PER_20.nc

Archived 4 years ago:

file:///g/data/fk4/datacube/002/HLTC/HLTC_2_0/COUNT_LOW_39_149.65_-21.55_20050101_20170101_PER_20.nc

Metadata Document 🔗

RAW As Stac

id: 2d3b79ad-df94-4c17-9d2a-4c07fda8d30b

product_type: tidal_composite

creation_dt: 2017-06-14T02:25:32.317081

format:

extent:

coord:

ll:

lat: -22.017016452562988

lon: 148.8296919505088

lr:

lat: -21.878661060858917

lon: 149.9307383908445

ul:

lat: -21.508191856692456

lon: 148.75654660738215

ur:

lat: -21.370312906610735

lon: 149.8529292175694

to_dt: 2016-10-31T00:00:00

key_dt: 2016-10-31T00:00:00

from_dt: 2000-01-01T00:00:00

center_dt: 2005-01-01T00:00:00

grid_spatial:

projection:

valid_data:

type: Polygon

coordinates: [

[

1718525.0

-2424950.0

]

[

1832400.0

-2424950.0

]

[

1832400.0

-2482225.0

]

[

1718525.0

-2482225.0

]

[

1718525.0

-2424950.0

]

geo_ref_points:

ll:

x: 1718525.0

y: -2482225.0

lr:

x: 1832400.0

y: -2482225.0

ul:

x: 1718525.0

y: -2424950.0

ur:

x: 1832400.0

y: -2424950.0

spatial_reference: EPSG:3577

image:

bands:

count_observations:

path:

layer: count_observations

lineage:

algorithm:

version: 0.4b1

repo_url: https://github.com/GeoscienceAustralia/agdc_statistics.git

parameters:

configuration_file: {'global_attributes': {'title': 'LOW composite'}, 'sources': [{'product': 'ls5_nbar_albers', 'name': 'intertidal_low', 'measurements': ['blue', 'green', 'red', 'nir', 'swir1', 'swir2'], 'group_by': 'solar_day', 'masks': [{'product': 'ls5_pq_albers', 'measurement': 'pixelquality', 'group_by': 'solar_day', 'fuse_func': 'datacube.helpers.ga_pq_fuser', 'flags': {'contiguous': True, 'cloud_acca': 'no_cloud', 'cloud_fmask': 'no_cloud', 'cloud_shadow_acca': 'no_cloud_shadow', 'cloud_shadow_fmask': 'no_cloud_shadow', 'blue_saturated': False, 'green_saturated': False, 'red_saturated': False, 'nir_saturated': False, 'swir1_saturated': False, 'swir2_saturated': False}}]}, {'product': 'ls7_nbar_albers', 'name': 'intertidal_low', 'measurements': ['blue', 'green', 'red', 'nir', 'swir1', 'swir2'], 'group_by': 'solar_day', 'masks': [{'product': 'ls7_pq_albers', 'measurement': 'pixelquality', 'group_by': 'solar_day', 'fuse_func': 'datacube.helpers.ga_pq_fuser', 'flags': {'contiguous': True, 'cloud_acca': 'no_cloud', 'cloud_fmask': 'no_cloud', 'cloud_shadow_acca': 'no_cloud_shadow', 'cloud_shadow_fmask': 'no_cloud_shadow', 'blue_saturated': False, 'green_saturated': False, 'red_saturated': False, 'nir_saturated': False, 'swir1_saturated': False, 'swir2_saturated': False}}]}, {'product': 'ls8_nbar_albers', 'name': 'intertidal_low', 'measurements': ['blue', 'green', 'red', 'nir', 'swir1', 'swir2'], 'group_by': 'solar_day', 'masks': [{'product': 'ls8_pq_albers', 'measurement': 'pixelquality', 'group_by': 'solar_day', 'fuse_func': 'datacube.helpers.ga_pq_fuser', 'flags': {'contiguous': True, 'cloud_acca': 'no_cloud', 'cloud_fmask': 'no_cloud', 'cloud_shadow_acca': 'no_cloud_shadow', 'cloud_shadow_fmask': 'no_cloud_shadow', 'blue_saturated': False, 'green_saturated': False, 'red_saturated': False, 'nir_saturated': False, 'swir1_saturated': False, 'swir2_saturated': False}}]}], 'date_ranges': {'start_date': '2005-01-01', 'end_date': '2017-01-01', 'stats_duration': '12y', 'step_size': '12y', 'type': 'simple'}, 'location': '/g/data/r78/intertidal/PRODUCT_LOW', 'input_region': {'from_file': '/g/data/r78/ITEM/TM_compute.shp'}, 'storage': {'driver': 'NetCDFCF', 'crs': 'EPSG:3577', 'tile_size': {'x': 100000.0, 'y': 100000.0}, 'resolution': {'x': 25, 'y': -25}, 'chunking': {'x': 200, 'y': 200, 'time': 1}, 'dimension_order': ['time', 'y', 'x']}, 'computation': {'chunking': {'x': 800, 'y': 800}}, 'output_products': [{'name': 'tidal_low', 'statistic': 'precisegeomedian', 'output_params': {'zlib': True, 'fletcher32': True}, 'file_path_template': 'COMPOSITE_{x}_{y}_{epoch_start:%Y%m%d}_{epoch_end:%Y%m%d}_PER_{percent}.nc', 'product_type': 'COMPOSITE LOW'}, {'name': 'tidal_count', 'statistic': 'clearcount', 'output_params': {'zlib': True, 'fletcher32': True}, 'file_path_template': 'COUNT_{x}_{y}_{epoch_start:%Y%m%d}_{epoch_end:%Y%m%d}_PER_{percent}.nc', 'product_type': 'COMPOSITE LOW'}], 'tide_class': {'product': 'low', 'percent': 20, 'global_epoch_start': '2005-01-01', 'global_epoch_end': '2017-01-01', 'feature_id': [39]}}

machine:

uname: Linux r4513 3.10.0-327.36.3.el6.x86_64 #1 SMP Wed Jan 25 05:38:43 UTC 2017 x86_64

hostname: r4513

software_versions:

python:

version: 3.6.1 | packaged by conda-forge | (default, Mar 23 2017, 21:05:12) [GCC 4.8.2 20140120 (Red Hat 4.8.2-15)]

datacube:

version: 1.3.2

repo_url: https://github.com/opendatacube/datacube-core.git

source_datasets:

statistic:

source: pq

tidal_range:

max: 20

min: 0