LS8_TMAD_NBART_8_-31_20160101.nc

dataset of product ls8_nbart_tmad_annual
Indexed by dra547 , created
Archived
for 1st January 2016

Fields 🔗

creation_time 2019-06-01 11:34:44 🔍 format NetCDF 🔍 id 70edcadf-4501-458e-a0f3-9b5ba25e8797 🔍 instrument OLI label • 🔍 lat -28.313 to -27.363 🔍 lon 140.197 to 141.292 🔍 platform LANDSAT_8 product_type surface_reflectance_triple_mad time 2016-01-01 00:00:00 to 2016-01-01 00:00:00 🔍

Related Datasets 🔗

LS8_OLI_NBART_3577_8_-31_20160919003147500000.nc
LS8_OLI_PQ_3577_8_-31_20160107003201000000.nc
LS8_OLI_NBART_3577_8_-31_20160116002551500000.nc
LS8_OLI_NBART_3577_8_-31_20161217002602000000_v1508467955.nc
LS8_OLI_PQ_3577_8_-31_20160615003139000000.nc
LS8_OLI_NBART_3577_8_-31_20160114003749000000.nc
LS8_OLI_NBART_3577_8_-31_20160507002522000000.nc
LS8_OLI_NBART_3577_8_-31_20160304002540000000.nc
LS8_OLI_NBART_3577_8_-31_20160320002534000000.nc
LS8_OLI_PQ_3577_8_-31_20160912002600000000.nc
LS8_OLI_NBART_3577_8_-31_20160912002600000000.nc
LS8_OLI_NBART_3577_8_-31_20160208003134000000.nc
LS8_OLI_PQ_3577_8_-31_20161113003804000000_v1508475122.nc
LS8_OLI_PQ_3577_8_-31_20161028003805000000_v1508475122.nc
LS8_OLI_NBART_3577_8_-31_20161231003758000000_v1508467955.nc
LS8_OLI_NBART_3577_8_-31_20160724003744000000.nc
LS8_OLI_NBART_3577_8_-31_20160825003753000000.nc
LS8_OLI_PQ_3577_8_-31_20160302003738000000.nc
LS8_OLI_NBART_3577_8_-31_20160311003125000000.nc
LS8_OLI_NBART_3577_8_-31_20160215003740000000.nc
LS8_OLI_PQ_3577_8_-31_20160403003723000000.nc
LS8_OLI_NBART_3577_8_-31_20161224003211500000_v1508467955.nc
LS8_OLI_NBART_3577_8_-31_20160201002550000000.nc
LS8_OLI_NBART_3577_8_-31_20160107003137000000.nc
LS8_OLI_PQ_3577_8_-31_20161012003803000000_v1508475122.nc
LS8_OLI_NBART_3577_8_-31_20161208003152000000_v1508467955.nc
LS8_OLI_PQ_3577_8_-31_20160514003106000000.nc
LS8_OLI_NBART_3577_8_-31_20160615003115000000.nc
LS8_OLI_PQ_3577_8_-31_20160123003138000000.nc
LS8_OLI_PQ_3577_8_-31_20161122003154000000_v1508475122.nc
... 144 more
LS8_TMAD_NBART_8_-31_20160101.nc
ga_ls_landcover_class_cyear_2_1-0-0_au_2016-01-01

Location 🔗

file:///g/data/fk4/datacube/002/stats/tmad/annual/ls8_mad/8_-31/LS8_TMAD_NBART_8_-31_20160101.nc

Metadata Document 🔗

RAW As Stac
id: 70edcadf-4501-458e-a0f3-9b5ba25e8797
product_type: surface_reflectance_triple_mad
creation_dt: 2019-06-01T11:34:44.993856
platform:
code: LANDSAT_8
instrument:
name: OLI
format:
name: NetCDF
extent:
coord:
ll:
lat: -28.313019312415847
lon: 140.2626903844939
lr:
lat: -28.25182419011771
lon: 141.292089115204
ul:
lat: -27.423490614002514
lon: 140.19651757600374
ur:
lat: -27.36278459874263
lon: 141.21772655620754
to_dt: 2016-01-01T00:00:00
from_dt: 2016-01-01T00:00:00
center_dt: 2016-01-01T00:00:00
grid_spatial:
projection:
valid_data:
type: Polygon
coordinates: [
[
[
800000.0
-3038302.168010464
]
[
800000.0
-3000000.0
]
[
900000.0
-3000000.0
]
[
900000.0
-3100000.0
]
[
800000.0
-3100000.0
]
[
800000.0
-3038302.168010464
]
]
]
geo_ref_points:
ll:
x: 800000.0
y: -3100000.0
lr:
x: 900000.0
y: -3100000.0
ul:
x: 800000.0
y: -3000000.0
ur:
x: 900000.0
y: -3000000.0
spatial_reference: EPSG:3577
image:
bands:
edev:
path:
layer: edev
sdev:
path:
layer: sdev
bcdev:
path:
layer: bcdev
lineage:
algorithm:
name: datacube-stats
version: 0.9b5
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: ls8_pq_albers
group_by: solar_day
fuse_func: datacube.helpers.ga_pq_fuser
measurement: pixelquality
]
product: ls8_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/bt2744/work/data/mad-annual/prod/ls8/
computation:
chunking:
x: 1000
y: 200
date_ranges:
end_date: 2017-01-01
step_size: 1y
start_date: 2016-01-01
stats_duration: 1y
input_region:
tiles: [
[
8
-31
]
]
filter_product:
var_attributes:
output_products: [
name: ls8_nbart_tmad_annual
metadata:
format:
name: NetCDF
platform:
code: LANDSAT_8
instrument:
name: OLI
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: ls8_ternary_mad-{epoch_start:%Y%m%d}-{epoch_end:%Y%m%d}_{x}_{y}.nc
]
global_attributes:
title: LS8 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 r3057 3.10.0-862.14.4.el6.x86_64 #1 SMP Thu Sep 27 07:25:17 AEST 2018 x86_64
hostname: r3057
software_versions:
python:
version: 3.6.7 | packaged by conda-forge | (default, Feb 20 2019, 02:51:38) [GCC 7.3.0]
datacube:
version: 1.6.2+398.g0e94625d
repo_url: https://github.com/opendatacube/datacube-core.git
source_datasets:
statistics:
step: 1y
period: 1y