ITEM_REL_206_152.52

creation_dt 2017-06-26T13:29:43.339207 creation_time 2017-06-26 13:29:43 format NetCDF id a2299ef5-c1d1-48d3-b5eb-e939010f29d8 instrument • label • lat -22.116 to -20.583 lon 151.97 to 153.233 platform • product_type ITEM time 1986-01-01 00:00:00 to 2016-10-31 23:59:59

Locations

Active:

file:///g/data/fk4/datacube/002/ITEM/ITEM_2_0/netcdf/ITEM_REL_206_152.52_-21.62.nc

Archived 3 years ago:

file:///g/data/fk4/datacube/002/ITEM/ITEM_2_0/ITEM_REL_206_152.52_-21.62.nc

Metadata Document

RAW As Stac

id: a2299ef5-c1d1-48d3-b5eb-e939010f29d8

product_type: ITEM

creation_dt: 2017-06-26T13:29:43.339207

format:

extent:

coord:

ll:

lat: -22.115582526527398

lon: 152.20704930366273

lr:

lat: -21.961581661982336

lon: 153.23330394425935

ul:

lat: -20.73515100080516

lon: 151.9698950624794

ur:

lat: -20.582559534280005

lon: 152.98453335979863

to_dt: 2016-10-31T23:59:59

key_dt: 2016-10-31T23:59:59

from_dt: 1986-01-01T00:00:00

center_dt: 1986-01-01T00:00:00

grid_spatial:

projection:

valid_data:

type: Polygon

coordinates: [

[

2108525.0

-2387275.0

]

[

2100700.0

-2397175.0

]

[

2059025.0

-2453141.426858513

]

[

2059025.0

-2453440.306122449

]

[

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]

[

2066950.0

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]

[

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]

[

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]

[

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]

[

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]

[

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]

[

2165500.0

-2406420.8478513355

]

[

2165500.0

-2406366.6228070175

]

[

2108525.0

-2387275.0

]

geo_ref_points:

ll:

x: 2059025.0

y: -2543050.0

lr:

x: 2165500.0

y: -2543050.0

ul:

x: 2059025.0

y: -2387175.0

ur:

x: 2165500.0

y: -2387175.0

spatial_reference: EPSG:3577

image:

bands:

relative:

path:

layer: relative

lineage:

algorithm:

version: 0.4b1

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

parameters:

configuration_file: {'global_attributes': {'title': 'ITEM'}, 'sources': [{'product': 'ls5_nbar_albers', 'name': 'ITEM', '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': 'ITEM', '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': 'ITEM', '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': '1986-01-01', 'end_date': '2017-01-01', 'stats_duration': '31y', 'step_size': '31y', 'type': 'simple'}, 'location': '/g/data/r78/ITEM/OUTPUT_GA', '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': 'med_ndwi', 'statistic': 'medndwi', 'output_params': {'zlib': True, 'fletcher32': True}, 'file_path_template': '{x}_{y}_{epoch_start:%Y%m%d}_{epoch_end:%Y%m%d}_{stat_name}_PER_{percent}.nc', 'product_type': 'ITEM'}], 'tide_class': {'product': 'item', 'range_percent': 10, 'percent': 90, 'ls7_slc_off': False, 'global_epoch_start': '1986-01-01', 'global_epoch_end': '2017-01-01', 'feature_id': [206]}}

machine:

uname: Linux r4514 3.10.0-327.36.3.el6.x86_64 #1 SMP Wed Jan 25 05:38:43 UTC 2017 x86_64

hostname: r4514

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: