LS5_GM_NBART_11_-19_19910101.nc

dataset of product ls5_nbart_geomedian_annual
Indexed by dra547 , created
Archived
for 1st January 1991

Fields 🔗

creation_time 2018-07-06 05:08:28 format NetCDF id 36cd574e-25f6-4dd0-8028-b5dc0adc9a8b instrument TM label • lat -17.396 to -16.417 🔍 lon 142.272 to 143.283 🔍 platform LANDSAT_5 product_type surface_reflectance_statistical_summary time 1991-01-01 00:00:00 to 1991-01-01 00:00:00 🔍

Related Datasets 🔗

LS5_TM_NBART_3577_11_-19_1991_v1493725462.nc#part=4
LS5_TM_PQ_3577_11_-19_1991_v1501866123.nc#part=4
LS5_TM_PQ_3577_11_-19_1991_v1501866123.nc#part=46
LS5_TM_NBART_3577_11_-19_1991_v1493725462.nc#part=56
LS5_TM_PQ_3577_11_-19_1991_v1501866123.nc#part=36
LS5_TM_NBART_3577_11_-19_1991_v1493725462.nc#part=15
LS5_TM_NBART_3577_11_-19_1991_v1493725462.nc#part=40
LS5_TM_PQ_3577_11_-19_1991_v1501866123.nc#part=24
LS5_TM_PQ_3577_11_-19_1991_v1501866123.nc#part=43
LS5_TM_PQ_3577_11_-19_1991_v1501866123.nc#part=19
LS5_TM_NBART_3577_11_-19_1991_v1493725462.nc#part=35
LS5_TM_PQ_3577_11_-19_1991_v1501866123.nc#part=9
LS5_TM_NBART_3577_11_-19_1991_v1493725462.nc#part=39
LS5_TM_NBART_3577_11_-19_1991_v1493725462.nc#part=33
LS5_TM_PQ_3577_11_-19_1991_v1501866123.nc#part=40
LS5_TM_NBART_3577_11_-19_1991_v1493725462.nc#part=34
LS5_TM_PQ_3577_11_-19_1991_v1501866123.nc#part=58
LS5_TM_PQ_3577_11_-19_1991_v1501866123.nc#part=17
LS5_TM_NBART_3577_11_-19_1991_v1493725462.nc#part=10
LS5_TM_NBART_3577_11_-19_1991_v1493725462.nc#part=22
LS5_TM_PQ_3577_11_-19_1991_v1501866123.nc#part=20
LS5_TM_NBART_3577_11_-19_1991_v1493725462.nc#part=11
LS5_TM_PQ_3577_11_-19_1991_v1501866123.nc#part=39
LS5_TM_NBART_3577_11_-19_1991_v1493725462.nc#part=45
LS5_TM_NBART_3577_11_-19_1991_v1493725462.nc#part=62
LS5_TM_PQ_3577_11_-19_1991_v1501866123.nc#part=30
LS5_TM_PQ_3577_11_-19_1991_v1501866123.nc#part=61
LS5_TM_NBART_3577_11_-19_1991_v1493725462.nc#part=2
LS5_TM_PQ_3577_11_-19_1991_v1501866123.nc#part=5
LS5_TM_PQ_3577_11_-19_1991_v1501866123.nc#part=28
... 98 more
LS5_GM_NBART_11_-19_19910101.nc
ga_ls_landcover_class_cyear_2_1-0-0_au_1991-01-01

Location 🔗

file:///g/data/fk4/datacube/002/stats/geomedian/annual/ls5_gm/11_-19/LS5_GM_NBART_11_-19_19910101.nc

Metadata Document 🔗

RAW As Stac
id: 36cd574e-25f6-4dd0-8028-b5dc0adc9a8b
product_type: surface_reflectance_statistical_summary
creation_dt: 2018-07-06T05:08:28.326289
platform:
code: LANDSAT_5
instrument:
name: TM
format:
name: NetCDF
extent:
coord:
ll:
lat: -17.39636626613463
lon: 142.34698139229576
lr:
lat: -17.319838830068115
lon: 143.28293444791913
ul:
lat: -16.493157200887744
lon: 142.27151870500498
ur:
lat: -16.41698655185549
lon: 143.20071306620082
to_dt: 1991-01-01T00:00:00
from_dt: 1991-01-01T00:00:00
center_dt: 1991-01-01T00:00:00
grid_spatial:
projection:
valid_data:
type: Polygon
coordinates: [
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image:
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repo_url: https://github.com/GeoscienceAustralia/datacube-stats.git
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location: /g/data/u46/users/ia1511/Work/data/geomedian/output
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metadata:
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platform:
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statistic: new_geomedian
product_type: surface_reflectance_statistical_summary
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global_attributes:
title: Surface Reflectance Geometric Median
source: geometric median v2017 of surface reflectance NBAR+T
license: CC BY Attribution 4.0 International License
summary: The surface reflectance geometric median (geomedian) is a pixel composite mosaic of a time series of earth observations. The value of a pixel in a geomedian image is the statistical median of all observations for that pixel from a period of time. For example the 2016 Landsat 8 geomedian image over an area will be the median of Landsat 8 pixels observed for that area in 2016. The geometric median products are available as annual datasets for years since 1987. Each annual composite is created from one calendar year of surface reflectance and for one sensor, i.e. Thematic Mapper (Landsat 5), Enhanced Thematic Mapper (Landsat 7) or Operational Land Imager (Landsat 8). The algorithm considers concurrent spectral measurements as a multi-dimensional set and outputs a multi-dimensional median that maintains the relationships among the measurements. This provides a median of the physical conditions measured by the earth observations used to create it, and provides a good representation of a typical pixel observation devoid of outliers. More information on the algorithm can be found in the article below: - Roberts, D., Mueller, N., & Mcintyre, A. (2017). High-Dimensional Pixel Composites From Earth Observation Time Series. IEEE Transactions on Geoscience and Remote Sensing, 55(11), 6254-6264. https://doi.org/10.1109/tgrs.2017.2723896
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: - Roberts, D., Mueller, N., & Mcintyre, A. (2017). High-Dimensional Pixel Composites From Earth Observation Time Series. IEEE Transactions on Geoscience and Remote Sensing, 55(11), 6254-6264. https://doi.org/10.1109/tgrs.2017.2723896
description: Surface Reflectance Geometric Median 25 metre, 100km tile, Australian Albers Equal Area projection (EPSG:3577)
institution: Commonwealth of Australia (Geoscience Australia)
cdm_data_type: Grid
product_suite: Surface Reflectance Geometric Median 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
publisher_email: earth.observation@ga.gov.au
keywords_vocabulary: GCMD
coverage_content_type: modelResult
machine:
uname: Linux r2434 3.10.0-862.3.3.el6.x86_64 #1 SMP Wed Jun 27 18:22:35 AEST 2018 x86_64
hostname: r2434
software_versions:
python:
version: 3.6.5 | packaged by conda-forge | (default, Apr 6 2018, 13:39:56) [GCC 4.8.2 20140120 (Red Hat 4.8.2-15)]
datacube:
version: 1.6rc2+2.g6aa9d16
repo_url: https://github.com/opendatacube/datacube-core.git
source_datasets:
statistics:
step: 1y
period: 1y