WOFS_3577_6_-39_2014-04_2014-10_summary.nc

dataset of product wofs_apr_oct_summary
Indexed by adh547 , created
Archived
for 1st April 2014
LS_WATER_3577_6_-39_20140424002433500000_v1526762166.nc
LS_WATER_3577_6_-39_20140618003120500000_v1526762166.nc
LS_WATER_3577_6_-39_20141016003347000000_v1526762166.nc
LS_WATER_3577_6_-39_20140502002729000000_v1526762166.nc
LS_WATER_3577_6_-39_20140813003336500000_v1526762166.nc
LS_WATER_3577_6_-39_20140922003141000000_v1526762166.nc
LS_WATER_3577_6_-39_20140906003136000000_v1526762166.nc
LS_WATER_3577_6_-39_20140914003406000000_v1526762166.nc
LS_WATER_3577_6_-39_20140930003342000000_v1526762166.nc
LS_WATER_3577_6_-39_20140923002752000000_v1526762166.nc
LS_WATER_3577_6_-39_20140525003304000000_v1526762166.nc
LS_WATER_3577_6_-39_20141017002522500000_v1526762166.nc
LS_WATER_3577_6_-39_20140602003056500000_v1526762166.nc
LS_WATER_3577_6_-39_20141009002734000000_v1526762166.nc
LS_WATER_3577_6_-39_20140721002715000000_v1526762166.nc
LS_WATER_3577_6_-39_20140907002754000000_v1526762166.nc
LS_WATER_3577_6_-39_20140626003340000000_v1526762166.nc
LS_WATER_3577_6_-39_20141008003129500000_v1526762166.nc
LS_WATER_3577_6_-39_20140806002747000000_v1526762166.nc
LS_WATER_3577_6_-39_20140618003056500000_v1526762166.nc
LS_WATER_3577_6_-39_20140728003352000000_v1526762166.nc
LS_WATER_3577_6_-39_20140914003342000000_v1526762166.nc
LS_WATER_3577_6_-39_20140830002459500000_v1526762166.nc
LS_WATER_3577_6_-39_20140517003053000000_v1526762166.nc
LS_WATER_3577_6_-39_20140611002510500000_v1526762166.nc
LS_WATER_3577_6_-39_20140712003349000000_v1526762166.nc
LS_WATER_3577_6_-39_20140806002723000000_v1526762166.nc
LS_WATER_3577_6_-39_20140830002523500000_v1526762166.nc
LS_WATER_3577_6_-39_20140704003104000000_v1526762166.nc
LS_WATER_3577_6_-39_20140423003325500000_v1526762166.nc
... 56 more
WOFS_3577_6_-39_2014-04_2014-10_summary.nc

Fields 🔗

creation_dt 2018-11-23T02:45:39.077481 creation_time 2018-11-23 02:45:39 format NetCDF id 1332cb30-b776-4f81-9bd4-8d6c37e01b5e instrument TM,ETM,OLI label • lat -35.56 to -34.613 lon 138.573 to 139.732 platform LANDSAT_5,LANDSAT_7,LANDSAT_8 product_type wofs_apr_oct_summary time 2014-04-01 00:00:00 to 2014-04-01 00:00:00

Location 🔗

file:///g/data/fk4/datacube/002/WOfS/WOfS_Stats_Apr_Oct_25_2_1/netcdf/6_-39/WOFS_3577_6_-39_2014-04_2014-10_summary.nc

Metadata Document 🔗

RAW As Stac
id: 1332cb30-b776-4f81-9bd4-8d6c37e01b5e
product_type: wofs_apr_oct_summary
creation_dt: 2018-11-23T02:45:39.077481
platform:
code: LANDSAT_5,LANDSAT_7,LANDSAT_8
instrument:
name: TM,ETM,OLI
format:
name: NetCDF
extent:
coord:
ll:
lat: -35.56047153483147
lon: 138.62946574546683
lr:
lat: -35.50990706229933
lon: 139.73187258988253
ul:
lat: -34.66254609001261
lon: 138.5726717800677
ur:
lat: -34.61252517416586
lon: 139.66567672461315
to_dt: 2014-04-01T00:00:00
from_dt: 2014-04-01T00:00:00
center_dt: 2014-04-01T00:00:00
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spatial_reference: EPSG:3577
image:
bands:
count_wet:
path:
layer: count_wet
frequency:
path:
layer: frequency
count_clear:
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lineage:
algorithm:
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version: 0.9b4
repo_url: https://github.com/GeoscienceAustralia/datacube-stats.git
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group_by: solar_day
fuse_func: digitalearthau.utils.wofs_fuser
mask_nodata: False
measurements: [
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dimension_order: [
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location: /g/data/u46/users/bt2744/work/data/wofs/output/prod/seasonal_stats/dry
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y: 2000
date_ranges:
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stats_duration: 7m
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filter_product:
var_attributes:
output_products: [
name: wofs_apr_oct_summary
metadata:
format:
name: NetCDF
platform:
code: LANDSAT_5,LANDSAT_7,LANDSAT_8
instrument:
name: TM,ETM,OLI
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 r3445 3.10.0-862.14.4.el6.x86_64 #1 SMP Thu Sep 27 07:25:17 AEST 2018 x86_64
hostname: r3445
software_versions:
python:
version: 3.6.6 | packaged by conda-forge | (default, Oct 12 2018, 14:08:43) [GCC 4.8.2 20140120 (Red Hat 4.8.2-15)]
datacube:
version: 1.6.1+72.gdfc6b47a
repo_url: https://github.com/opendatacube/datacube-core.git
source_datasets:
statistics:
step: 1y
period: 7m