<del>WOFS_3577_10_-49_2019-04_2019-10

WOFS_3577_10_-49_2019-04_2019-10_summary.nc

dataset of product wofs_apr_oct_summary

Indexed by dra547 3 years ago, created 3 years ago

Archived 2 years ago

for 1st April 2019

Fields 🔗

creation_time 2020-07-03 11:36:38 🔍 format NetCDF id 347ec1ee-6bf9-42f9-98ae-8d92900c39e6 🔍 instrument TM,ETM,OLI label • 🔍 lat -44.093 to -43.406 🔍 lon 143.958 to 145.225 🔍 platform LANDSAT_5,LANDSAT_7,LANDSAT_8 product_type wofs_apr_oct_summary time 2019-04-01 00:00:00 to 2019-04-01 00:00:00 🔍

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~~WOFS_3577_10_-49_2019-04_2019-10_summary.nc~~

Location 🔗

file:///g/data/fk4/datacube/002/WOfS/WOfS_Stats_Apr_Oct_25_2_1/netcdf/10_-49/WOFS_3577_10_-49_2019-04_2019-10_summary.nc

Metadata Document 🔗

RAW As Stac

id: 347ec1ee-6bf9-42f9-98ae-8d92900c39e6

product_type: wofs_apr_oct_summary

creation_dt: 2020-07-03T11:36:38.766923

platform:

code: LANDSAT_5,LANDSAT_7,LANDSAT_8

instrument:

format:

extent:

coord:

ll:

lat: -44.09296572648391

lon: 144.03023925498098

lr:

lat: -44.00067092788738

lon: 145.2250729037058

ul:

lat: -43.49787733881087

lon: 143.95836727265126

ur:

lat: -43.40648223618046

lon: 145.1461593644987

to_dt: 2019-04-01T00:00:00

from_dt: 2019-04-01T00:00:00

center_dt: 2019-04-01T00:00:00

grid_spatial:

projection:

valid_data:

type: Polygon

coordinates: [

[

1000000.0

-4841482.227036813

]

[

1000000.0

-4800000.0

]

[

1100000.0

-4800000.0

]

[

1100000.0

-4864013.321476883

]

[

1090080.2436473612

-4862961.188940421

]

[

1089406.296225338

-4862893.832526992

]

[

1089389.4566386128

-4862887.921063486

]

[

1083724.118411802

-4862287.030631645

]

[

1083710.2879159916

-4862324.555639742

]

[

1051410.875334616

-4859096.451315501

]

[

1008128.6381496013

-4854848.071795101

]

[

1000000.0

-4854098.35550374

]

[

1000000.0

-4841482.227036813

]

geo_ref_points:

ll:

x: 1000000.0

y: -4900000.0

lr:

x: 1100000.0

y: -4900000.0

ul:

x: 1000000.0

y: -4800000.0

ur:

x: 1100000.0

y: -4800000.0

spatial_reference: EPSG:3577

image:

bands:

count_wet:

path:

layer: count_wet

frequency:

path:

layer: frequency

count_clear:

path:

layer: count_clear

lineage:

algorithm:

version: 1.0.2

repo_url: https://github.com/GeoscienceAustralia/datacube-stats.git

parameters:

configuration_file:

sources: [

product: wofs_albers

group_by: solar_day

fuse_func: digitalearthau.utils.wofs_fuser

mask_nodata: False

measurements: [

water

]

storage:

crs: EPSG:3577

driver: NetCDF CF

chunking:

x: 200

y: 200

time: 1

tile_size:

x: 100000.0

y: 100000.0

resolution:

x: 25

y: -25

dimension_order: [

time

]

location: /g/data/u46/users/bt2744/work/data/prod/wofs/seasonal_apr_oct

computation:

chunking:

x: 2000

y: 2000

date_ranges:

end_date: 2019-11-01

step_size: 1y

start_date: 2019-04-01

stats_duration: 7m

input_region:

tiles: [

[

-49

]

filter_product:

var_attributes:

output_products: [

metadata:

format:

platform:

code: LANDSAT_5,LANDSAT_7,LANDSAT_8

instrument:

statistic: wofs_summary

product_type: wofs_apr_oct_summary

output_params:

zlib: True

fletcher32: True

file_path_template: WOFS_3577_{x}_{y}_{epoch_start:%Y-%m}_{epoch_end:%Y-%m}_summary.nc

]

global_attributes:

title: Water Observations from Space April to October Statistics

cmi_id: WO-STATS_25_2.1.5

source: Water Observations from Space Detection Algorithm v1.5

license: CC BY Attribution 4.0 International License

summary: WOfS-STATS (WO_STATS_2.1.5) is a set of statistical summaries of the water observations contained in WOfS (WO_2.1.5). The layers available are: the count of clear observations; the count of wet observations; the percentage of wet observations over time.

keywords: AU/GA,NASA/GSFC/SED/ESD/LANDSAT,ETM+,TM,OLI,EARTH SCIENCE,SURFACE WATER,FLOOD

references: N. Mueller, A. Lewis, D. Roberts, S. Ring, R. Melrose, J. Sixsmith, L. Lymburner, A. McIntyre, P. Tan, S. Curnow, A. Ip, Water observations from space: Mapping surface water from 25 years of Landsat imagery across Australia, Remote Sensing of Environment, Volume 174, 1 March 2016, Pages 341-352, ISSN 0034-4257, http://dx.doi.org/10.1016/j.rse.2015.11.003. (http://www.sciencedirect.com/science/article/pii/S0034425715301929)

institution: Commonwealth of Australia (Geoscience Australia)

cdm_data_type: Grid

product_suite: Water Observations from Space Statistics 25m

publisher_url: http://www.ga.gov.au

publisher_name: Section Leader, Operations Section, NEMO, Geoscience Australia

product_version: 2.1.5

publisher_email: earth.observation@ga.gov.au

keywords_vocabulary: GCMD

machine:

uname: Linux gadi-cpu-clx-2123.gadi.nci.org.au 4.18.0-193.6.3.el8.nci.x86_64 #1 SMP Tue Jun 23 04:50:57 UTC 2020 x86_64

hostname: gadi-cpu-clx-2123.gadi.nci.org.au

software_versions:

python:

version: 3.6.10 | packaged by conda-forge | (default, Apr 24 2020, 16:44:11) [GCC 7.3.0]

datacube:

version: 1.8.1.dev38+ga202f9c4

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

source_datasets:

statistics:

step: 1y

period: 7m