LS5_GM_NBART_-5_-17_19900101.nc
dataset of product ls5_nbart_geomedian_annual
Indexed by dra547
,
created
Archived
for
1st January 1990
Fields 🔗
creation_time
2018-07-05 22:09:56 🔍
format
NetCDF 🔍
id
1d98100d-301e-4a6c-973b-2c13e63aedda 🔍
instrument
TM
label
• 🔍
lat
-15.934 to -14.995 🔍
lon
127.357 to 128.312 🔍
platform
LANDSAT_5
product_type
surface_reflectance_statistical_summary
time
1990-01-01 00:00:00 to 1990-01-01 00:00:00 🔍
Location 🔗
Metadata Document 🔗
id:
1d98100d-301e-4a6c-973b-2c13e63aedda
product_type:
surface_reflectance_statistical_summary
creation_dt:
2018-07-05T22:09:56.612378
platform:
code:
LANDSAT_5
instrument:
name:
TM
format:
name:
NetCDF
extent:
coord:
ll:
lat:
-15.904270329179141
lon:
127.35711029057273
lr:
lat:
-15.933997405893452
lon:
128.28509954545945
ul:
lat:
-14.994532473342183
lon:
127.39059854795472
ur:
lat:
-15.024132478938641
lon:
128.31190279813484
to_dt:
1990-01-01T00:00:00
from_dt:
1990-01-01T00:00:00
center_dt:
1990-01-01T00:00:00
grid_spatial:
projection:
valid_data:
type:
Polygon
coordinates:
[
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red:
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green:
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swir2:
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swir2
lineage:
algorithm:
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repo_url:
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parameters:
configuration_file:
sources:
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masks:
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flags:
cloud_acca:
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contiguous:
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cloud_fmask:
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nir_saturated:
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red_saturated:
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blue_saturated:
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swir1_saturated:
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swir2_saturated:
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cloud_shadow_acca:
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red
nir
swir1
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driver:
NetCDF CF
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tile_size:
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resolution:
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y:
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dimension_order:
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y
x
]
location:
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computation:
chunking:
x:
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y:
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date_ranges:
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step_size:
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stats_duration:
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name:
ls5_nbart_geomedian_annual
metadata:
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name:
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platform:
code:
LANDSAT_5
instrument:
name:
TM
statistic:
new_geomedian
product_type:
surface_reflectance_statistical_summary
output_params:
zlib:
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file_path_template:
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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
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uname:
Linux r2440 3.10.0-862.3.3.el6.x86_64 #1 SMP Wed Jun 27 18:22:35 AEST 2018 x86_64
hostname:
r2440
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:
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repo_url:
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source_datasets:
statistics:
step:
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period:
1y