LS_TCW_PC_-13_-40_19870101_20181025.nc

dataset of product ga_ls_tcw_percentiles_2
Indexed by dra547 , created
Region -13_-40 for 1st January 1987

Fields 🔗

creation_time 2018-11-27 06:29:41 🔍 format NetCDF 🔍 id d6b98a6b-9bd2-4481-8a7d-264da7b7d4bf 🔍 instrument TM,ETM+,OLI label • 🔍 lat -36.037 to -35.045 🔍 lon 117.56 to 118.777 🔍 platform LANDSAT_5,LANDSAT_7,LANDSAT_8 product_type tcw_percentile time 1987-01-01 00:00:00 to 1987-01-01 00:00:00 🔍

Related Datasets 🔗

LS8_OLI_PQ_3577_-13_-40_2015_v1501891224.nc#part=75
LS8_OLI_NBART_3577_-13_-40_20180208015344500000_v1520974159.nc
LS8_OLI_PQ_3577_-13_-40_20171010020021000000_v1512615633.nc
LS7_ETM_PQ_3577_-13_-40_2000_v1501877138.nc#part=12
LS8_OLI_PQ_3577_-13_-40_20180531015242000000_v1535105519.nc
LS5_TM_PQ_3577_-13_-40_2006_v1501873839.nc#part=19
LS5_TM_NBART_3577_-13_-40_1993_v1493725466.nc#part=0
LS8_OLI_NBART_3577_-13_-40_2015_v1493806523.nc#part=64
LS5_TM_PQ_3577_-13_-40_2009_v1501875574.nc#part=18
LS5_TM_PQ_3577_-13_-40_1990_v1501865521.nc#part=5
LS8_OLI_PQ_3577_-13_-40_20171206015402500000_v1515732337.nc
LS5_TM_NBART_3577_-13_-40_2007_v1493738755.nc#part=8
LS5_TM_PQ_3577_-13_-40_1992_v1501866831.nc#part=20
LS5_TM_PQ_3577_-13_-40_1998_v1501870626.nc#part=29
LS8_OLI_NBART_3577_-13_-40_2015_v1493806523.nc#part=3
LS8_OLI_NBART_3577_-13_-40_20170519015933000000_v1508468655.nc
LS5_TM_NBART_3577_-13_-40_2007_v1493738755.nc#part=16
LS8_OLI_NBART_3577_-13_-40_20180904015352000000_v1537611829.nc
LS5_TM_PQ_3577_-13_-40_1990_v1501865521.nc#part=28
LS8_OLI_PQ_3577_-13_-40_2014_v1501890175.nc#part=76
LS5_TM_PQ_3577_-13_-40_1988_v1501858717.nc#part=16
LS5_TM_PQ_3577_-13_-40_2003_v1501871971.nc#part=13
LS5_TM_PQ_3577_-13_-40_1991_v1501866123.nc#part=12
LS5_TM_PQ_3577_-13_-40_1987_v1501853691.nc#part=2
LS5_TM_PQ_3577_-13_-40_1997_v1501870047.nc#part=14
LS5_TM_NBART_3577_-13_-40_1990_v1493707129.nc#part=23
LS8_OLI_NBART_3577_-13_-40_20160430015940000000.nc
LS5_TM_NBART_3577_-13_-40_1993_v1493725466.nc#part=9
LS5_TM_PQ_3577_-13_-40_1988_v1501858717.nc#part=11
LS8_OLI_NBART_3577_-13_-40_2014_v1493805436.nc#part=52
... 1772 more
LS_TCW_PC_-13_-40_19870101_20181025.nc

Location 🔗

file:///g/data/fk4/datacube/002/TCI/ls_tcw_percentiles/LS_TCW_PC_-13_-40_19870101_20181025.nc

Metadata Document 🔗

RAW As Stac
id: d6b98a6b-9bd2-4481-8a7d-264da7b7d4bf
product_type: tcw_percentile
creation_dt: 2018-11-27T06:29:41.128735
platform:
code: LANDSAT_5,LANDSAT_7,LANDSAT_8
instrument:
name: TM,ETM+,OLI
format:
name: NetCDF
extent:
coord:
ll:
lat: -35.93892563592589
lon: 117.55952750406267
lr:
lat: -36.03671000653697
lon: 118.66194747484346
ul:
lat: -35.04462142683269
lon: 117.68348149202261
ur:
lat: -35.141340045739746
lon: 118.77658043377863
to_dt: 1987-01-01T00:00:00
from_dt: 1987-01-01T00:00:00
center_dt: 1987-01-01T00:00:00
grid_spatial:
projection:
valid_data:
type: Polygon
coordinates: [
[
[
-1300000.0
-3900066.5486291307
]
[
-1300000.0
-3900000.0
]
[
-1200000.0
-3900000.0
]
[
-1200000.0
-4000000.0
]
[
-1300000.0
-4000000.0
]
[
-1300000.0
-3900066.5486291307
]
]
]
geo_ref_points:
ll:
x: -1300000.0
y: -4000000.0
lr:
x: -1200000.0
y: -4000000.0
ul:
x: -1300000.0
y: -3900000.0
ur:
x: -1200000.0
y: -3900000.0
spatial_reference: EPSG:3577
image:
bands:
TCW_PC_10:
path:
layer: TCW_PC_10
TCW_PC_50:
path:
layer: TCW_PC_50
TCW_PC_90:
path:
layer: TCW_PC_90
lineage:
algorithm:
name: datacube-stats
version: 0.9b4
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: ls5_pq_albers
group_by: solar_day
fuse_func: datacube.helpers.ga_pq_fuser
measurement: pixelquality
]
product: ls5_nbart_albers
group_by: solar_day
measurements: [
blue
green
red
nir
swir1
swir2
]
source_filter:
product: ls5_level1_scene
gqa_iterative_mean_xy: [
-1
1
]
time: [
1995-01-01
2003-05-31
]
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
]
source_filter:
product: ls7_level1_scene
gqa_iterative_mean_xy: [
-1
1
]
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
]
source_filter:
product: ls8_level1_scene
gqa_iterative_mean_xy: [
-1
1
]
]
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
y
x
]
location: /g/data/fk4/datacube/002/TCI/ls_tcw_percentiles/
computation:
chunking:
x: 800
y: 800
date_ranges:
end_date: 2018-10-25
start_date: 1987-01-01
input_region:
tile: [
13
-34
]
filter_product:
var_attributes:
TCW_PC_10:
long_name: Tasseled Cap Wetness Index 10th percentile
coverage_content_type: modelResult
TCW_PC_50:
long_name: Tasseled Cap Wetness Index 50th percentile
coverage_content_type: modelResult
TCW_PC_90:
long_name: Tasseled Cap Wetness Index 90th percentile
coverage_content_type: modelResult
output_products: [
name: tcw_percentile
metadata:
format:
name: NetCDF
platform:
code: LANDSAT_5,LANDSAT_7,LANDSAT_8
instrument:
name: TM,ETM+,OLI
statistic: external
product_type: tcw_percentile
output_params:
zlib: True
fletcher32: True
statistic_args:
q: [
10
50
90
]
impl: custom_stats.percentile_stats.TCIpercentile
category: wetness
per_pixel_metadata: [
source
observed_date
]
minimum_valid_observations: 3
file_path_template: LS_TCW_PC_{x}_{y}_{epoch_start:%Y%m%d}_{epoch_end:%Y%m%d}.nc
]
global_attributes:
title: Tasseled Cap Wetness Percentiles 25m 2.0.0
cmi_id: TCW_PERCENTILES_25_2.0.0
source: percentiles of tasseled cap wetness index v2.0.0
license: CC BY Attribution 4.0 International License
summary: The tasseled cap index percentiles provide statistical (10th, 50th and 90th percentile) summaries of the tasseled cap wetness index from 1987 to 2018. They are intended for use as inputs into classification algorithms to identify wetlands and characterise salt flats, clay pans, salt lakes and coastal land forms. The tasseled cap wetness transform translates the six spectral bands of Landsat into a single wetness index. The wetness index can be used to identify areas in the landscape that are potentially wetlands or groundwater dependent ecosystems. The tasseled cap wetness percentiles captures how the wetness index behaves over time. The percentiles are well suited to characterising wetlands, salt flats/salt lakes and coastal ecosystems. However, care should be applied when analysing the wetness index, as soil colour and fire scars can cause misleading results. Crist, E.P., 1985. A TM tasseled cap equivalent transformation for reflectance factor data. Remote Sensing of Environment, 17(3),pp.301-306.
keywords: AU/GA,NASA/GSFC/SED/ESD/LANDSAT,REFLECTANCE,ETM+,TM,OLI,EARTH SCIENCE
platform: LANDSAT-5,LANDSAT-7,LANDSAT-8
instrument: TM,ETM+,OLI
references: - Crist, E.P., 1985. A TM tasseled cap equivalent transformation for reflectance factor data. Remote Sensing of Environment, 17(3), pp.301-306.
description: Tasseled Cap Wetness Percentile 25 metre, 100km tile, Australian Albers Equal Area projection (EPSG:3577)
institution: Commonwealth of Australia (Geoscience Australia)
cdm_data_type: Grid
product_suite: Tasseled Cap Index Stats 25m
publisher_url: http://www.ga.gov.au
acknowledgment: - Landsat data is provided by the United States Geological Survey (USGS) through direct reception of the data at Geoscience Australias satellite reception facility or download.
publisher_name: Section Leader, Operations Section, NEMO, Geoscience Australia
product_version: 2.0.0
publisher_email: earth.observation@ga.gov.au
keywords_vocabulary: GCMD
coverage_content_type: modelResult
machine:
uname: Linux r4511 3.10.0-862.14.4.el6.x86_64 #1 SMP Thu Sep 27 07:25:17 AEST 2018 x86_64
hostname: r4511
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: *
period: *