LS7_TMAD_NBART_6_-44_20180101.nc

dataset of product ls7_nbart_tmad_annual
Indexed by qcp547 , created
Archived
for 1st January 2018

Fields 🔗

creation_time 2021-03-03 14:43:50 🔍 format NetCDF 🔍 id 1dcb4c09-5beb-4ced-9572-4fdcfa0ae24a 🔍 instrument ETM+ label • 🔍 lat -39.647 to -39.123 🔍 lon 139.398 to 140.048 🔍 platform LANDSAT_7 product_type surface_reflectance_triple_mad time 2018-01-01 00:00:00 to 2018-01-01 00:00:00 🔍

Related Datasets 🔗

LS7_ETM_PQ_3577_6_-44_20180207002358500000_v1522797582.nc
LS7_ETM_PQ_3577_6_-44_20180428002254500000_v1537611829.nc
LS7_ETM_NBART_3577_6_-44_20180802002112500000_v1537611829.nc
LS7_ETM_NBART_3577_6_-44_20180701002147500000_v1538102561.nc
LS7_ETM_NBART_3577_6_-44_20180530002222500000_v1538049321.nc
LS7_ETM_PQ_3577_6_-44_20181224001751500000_v1548211882.nc
LS7_ETM_PQ_3577_6_-44_20180701002147500000_v1538102880.nc
LS7_ETM_PQ_3577_6_-44_20180412002311000000_v1525141431.nc
LS7_ETM_PQ_3577_6_-44_20180530002222500000_v1538048947.nc
LS7_ETM_NBART_3577_6_-44_20180207002358500000_v1520974084.nc
LS7_ETM_NBART_3577_6_-44_20180412002311000000_v1525136509.nc
LS7_ETM_PQ_3577_6_-44_20180802002112500000_v1537611829.nc
LS7_ETM_PQ_3577_6_-44_20180919002013500000_v1539426403.nc
LS7_ETM_NBART_3577_6_-44_20181224001751500000_v1548211882.nc
LS7_ETM_NBART_3577_6_-44_20180919002013500000_v1539426401.nc
LS7_ETM_NBART_3577_6_-44_20180428002254500000_v1537611829.nc
LS7_TMAD_NBART_6_-44_20180101.nc

Location 🔗

file:///g/data/fk4/datacube/002/stats/tmad/annual/ls7_mad/6_-44/LS7_TMAD_NBART_6_-44_20180101.nc

Metadata Document 🔗

RAW As Stac
id: 1dcb4c09-5beb-4ced-9572-4fdcfa0ae24a
product_type: surface_reflectance_triple_mad
creation_dt: 2021-03-03T14:43:50.187031
platform:
code: LANDSAT_7
instrument:
name: ETM+
format:
name: NetCDF
extent:
coord:
ll:
lat: -39.647412479610175
lon: 139.43373954505725
lr:
lat: -39.61782392918792
lon: 140.04757105855165
ul:
lat: -39.15286186097427
lon: 139.39761814587052
ur:
lat: -39.12347886408626
lon: 140.0084820611183
to_dt: 2018-01-01T00:00:00
from_dt: 2018-01-01T00:00:00
center_dt: 2018-01-01T00:00:00
grid_spatial:
projection:
valid_data:
type: Polygon
coordinates: [
[
[
700000.0
-4354215.797279831
]
[
700000.0
-4354311.247133869
]
[
653059.2445989434
-4342413.526817728
]
[
648648.706870264
-4341265.318455414
]
[
648493.8644109853
-4341162.810156525
]
[
647382.7483257235
-4340873.078342413
]
[
646481.5411645934
-4340257.76805733
]
[
648240.0385125478
-4334695.098117262
]
[
655939.3468414719
-4310878.382361345
]
[
659481.030440388
-4300000.0
]
[
700000.0
-4300000.0
]
[
700000.0
-4354215.797279831
]
]
]
geo_ref_points:
ll:
x: 600000.0
y: -4400000.0
lr:
x: 700000.0
y: -4400000.0
ul:
x: 600000.0
y: -4300000.0
ur:
x: 700000.0
y: -4300000.0
spatial_reference: EPSG:3577
image:
bands:
edev:
path:
layer: edev
sdev:
path:
layer: sdev
bcdev:
path:
layer: bcdev
lineage:
algorithm:
name: datacube-stats
version: 1.0.2
repo_url: https://github.com/GeoscienceAustralia/datacube-stats.git
parameters:
configuration_file:
sources: [
masks: [
flags:
cloud_acca: no_cloud
contiguous: True
cloud_fmask: no_cloud
nir_saturated: False
red_saturated: False
blue_saturated: False
green_saturated: False
swir1_saturated: False
swir2_saturated: False
cloud_shadow_acca: no_cloud_shadow
cloud_shadow_fmask: no_cloud_shadow
product: ls7_pq_albers
group_by: solar_day
fuse_func: datacube.helpers.ga_pq_fuser
measurement: pixelquality
]
product: ls7_nbart_albers
group_by: solar_day
measurements: [
blue
green
red
nir
swir1
swir2
]
]
storage:
crs: EPSG:3577
driver: NetCDF CF
chunking:
x: 256
y: 256
time: 1
tile_size:
x: 100000.0
y: 100000.0
resolution:
x: 25
y: -25
dimension_order: [
time
y
x
]
location: /g/data/u46/users/sc0554/annuals/mad_ls7_2018/
computation:
chunking:
x: 1000
y: 200
date_ranges:
end_date: 2019-01-01
step_size: 1y
start_date: 2018-01-01
stats_duration: 1y
input_region:
tiles: [
[
6
-44
]
]
filter_product:
var_attributes:
output_products: [
name: ls7_nbart_tmad_annual
metadata:
format:
name: NetCDF
platform:
code: LANDSAT_7
instrument:
name: ETM+
statistic: external
product_type: surface_reflectance_triple_mad
output_params:
zlib: True
fletcher32: True
statistic_args:
impl: model.TernaryMAD
num_threads: 3
file_path_template: LS7_TMAD_NBART_{x}_{y}_{epoch_start:%Y%m%d}.nc
]
global_attributes:
title: LS7 Surface Reflectance Triple Median Absolute Deviation 2.1.0
cmi_id: SR_TMAD_25_2.1.0
source: datacube-2nd-order-stats
license: CC BY Attribution 4.0 International License
summary: This product provides 'second order' statistical techniques that follow from the geometric median, useful for environmental characterisation and change detection. The Median Absolute Deviation (MAD) is a measure of variance in a dataset through comparison to the median. It is similar in concept to the way that the standard deviation in statistics can be used to understand variance compared to the mean.
keywords: AU/GA,NASA/GSFC/SED/ESD/LANDSAT,TM,EARTH SCIENCE
references: Roberts, D., Dunn, B. and Mueller, N. (2018). Open Data Cube Products Using High-Dimensional Statistics of Time Series. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium.
institution: Commonwealth of Australia (Geoscience Australia)
cdm_data_type: Grid
product_suite: Surface Reflectance Triple Median Absolute Deviation
publisher_url: http://www.ga.gov.au
publisher_name: Section Leader, Operations Section, NEMO, Geoscience Australia
acknowledgments: The high-dimensional statistics algorithms incorporated in this product is the work of Dr Dale Roberts, Australian National University.
product_version: 2.1.0
publisher_email: earth.observation@ga.gov.au
keywords_vocabulary: GCMD
machine:
uname: Linux gadi-cpu-clx-1504.gadi.nci.org.au 4.18.0-240.1.1.el8.nci.x86_64 #1 SMP Tue Dec 15 02:36:21 UTC 2020 x86_64
hostname: gadi-cpu-clx-1504.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: 1.8.3
repo_url: https://github.com/opendatacube/datacube-core.git
source_datasets:
statistics:
step: 1y
period: 1y