Search ga_ls8c_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2014-02-03 10:43:52	ga_ls8c_ard_3-0-0_104074_2014-02-03_final
2014-02-03 10:45:03	ga_ls8c_ard_3-0-0_104077_2014-02-03_final
2014-02-03 10:46:15	ga_ls8c_ard_3-0-0_104080_2014-02-03_final
2017-09-05 10:52:30	ga_ls8c_ard_3-0-0_106067_2017-09-05_final
2017-09-05 10:52:54	ga_ls8c_ard_3-0-0_106068_2017-09-05_final
2017-09-05 10:53:18	ga_ls8c_ard_3-0-0_106069_2017-09-05_final
2017-09-05 10:53:42	ga_ls8c_ard_3-0-0_106070_2017-09-05_final
2017-09-07 10:42:56	ga_ls8c_ard_3-0-0_104074_2017-09-07_final
2017-09-07 10:43:20	ga_ls8c_ard_3-0-0_104075_2017-09-07_final
2017-09-07 10:43:44	ga_ls8c_ard_3-0-0_104076_2017-09-07_final
2017-09-07 10:44:08	ga_ls8c_ard_3-1-0_104077_2017-09-07_final
2017-09-07 10:44:32	ga_ls8c_ard_3-0-0_104078_2017-09-07_final
2017-09-07 10:44:56	ga_ls8c_ard_3-0-0_104079_2017-09-07_final
2017-09-07 10:45:20	ga_ls8c_ard_3-0-0_104080_2017-09-07_final
2017-09-09 10:33:46	ga_ls8c_ard_3-0-0_102082_2017-09-09_final
2017-09-09 10:34:10	ga_ls8c_ard_3-0-0_102083_2017-09-09_final
2017-09-23 10:43:00	ga_ls8c_ard_3-0-0_104074_2017-09-23_final
2017-09-23 10:43:24	ga_ls8c_ard_3-0-0_104075_2017-09-23_final
2017-09-23 10:43:48	ga_ls8c_ard_3-0-0_104076_2017-09-23_final
2017-09-23 10:44:12	ga_ls8c_ard_3-1-0_104077_2017-09-23_final
2017-09-23 10:44:36	ga_ls8c_ard_3-0-0_104078_2017-09-23_final
2017-09-23 10:45:00	ga_ls8c_ard_3-0-0_104079_2017-09-23_final
2017-09-23 10:45:24	ga_ls8c_ard_3-0-0_104080_2017-09-23_final
2017-10-11 10:33:56	ga_ls8c_ard_3-0-0_102082_2017-10-11_final
2017-10-11 10:34:20	ga_ls8c_ard_3-0-0_102083_2017-10-11_final
2017-10-16 10:47:18	ga_ls8c_ard_3-0-0_105069_2017-10-16_final
2017-10-16 10:47:42	ga_ls8c_ard_3-0-0_105070_2017-10-16_final
2017-10-16 10:48:06	ga_ls8c_ard_3-0-0_105071_2017-10-16_final
2017-10-16 10:48:30	ga_ls8c_ard_3-0-0_105072_2017-10-16_final
2017-10-16 10:48:54	ga_ls8c_ard_3-0-0_105073_2017-10-16_final
2017-10-16 10:49:18	ga_ls8c_ard_3-0-0_105074_2017-10-16_final
2017-10-16 10:49:42	ga_ls8c_ard_3-0-0_105075_2017-10-16_final
2017-12-28 10:43:00	ga_ls8c_ard_3-0-0_104074_2017-12-28_final
2017-12-28 10:43:24	ga_ls8c_ard_3-0-0_104075_2017-12-28_final
2017-12-28 10:43:48	ga_ls8c_ard_3-0-0_104076_2017-12-28_final
2017-12-28 10:44:12	ga_ls8c_ard_3-1-0_104077_2017-12-28_final
2017-12-28 10:44:36	ga_ls8c_ard_3-0-0_104078_2017-12-28_final
2017-12-28 10:45:00	ga_ls8c_ard_3-0-0_104079_2017-12-28_final
2017-12-28 10:45:23	ga_ls8c_ard_3-0-0_104080_2017-12-28_final
2017-12-30 10:33:49	ga_ls8c_ard_3-0-0_102082_2017-12-30_final
2017-12-30 10:34:13	ga_ls8c_ard_3-0-0_102083_2017-12-30_final
2018-03-16 10:51:57	ga_ls8c_ard_3-0-0_106067_2018-03-16_final
2018-03-16 10:52:21	ga_ls8c_ard_3-0-0_106068_2018-03-16_final
2018-03-16 10:52:45	ga_ls8c_ard_3-0-0_106069_2018-03-16_final
2018-03-16 10:53:09	ga_ls8c_ard_3-0-0_106070_2018-03-16_final
2018-05-19 10:51:21	ga_ls8c_ard_3-0-0_106067_2018-05-19_final
2018-05-19 10:51:45	ga_ls8c_ard_3-0-0_106068_2018-05-19_final
2018-05-19 10:52:09	ga_ls8c_ard_3-0-0_106069_2018-05-19_final
2018-05-19 10:52:33	ga_ls8c_ard_3-0-0_106070_2018-05-19_final
2018-05-21 10:41:46	ga_ls8c_ard_3-0-0_104074_2018-05-21_final
2018-05-21 10:42:10	ga_ls8c_ard_3-0-0_104075_2018-05-21_final
2018-05-21 10:42:34	ga_ls8c_ard_3-0-0_104076_2018-05-21_final
2018-05-21 10:42:58	ga_ls8c_ard_3-1-0_104077_2018-05-21_final
2018-05-21 10:43:21	ga_ls8c_ard_3-0-0_104078_2018-05-21_final
2018-05-21 10:43:45	ga_ls8c_ard_3-0-0_104079_2018-05-21_final
2018-05-21 10:44:09	ga_ls8c_ard_3-0-0_104080_2018-05-21_final
2018-06-04 10:51:10	ga_ls8c_ard_3-0-0_106067_2018-06-04_final
2018-06-04 10:51:34	ga_ls8c_ard_3-0-0_106068_2018-06-04_final
2018-06-04 10:51:58	ga_ls8c_ard_3-0-0_106069_2018-06-04_final
2018-06-04 10:52:22	ga_ls8c_ard_3-0-0_106070_2018-06-04_final
2018-07-06 10:51:29	ga_ls8c_ard_3-0-0_106067_2018-07-06_final
2018-07-06 10:51:53	ga_ls8c_ard_3-0-0_106068_2018-07-06_final
2018-07-06 10:52:17	ga_ls8c_ard_3-0-0_106069_2018-07-06_final
2018-07-06 10:52:41	ga_ls8c_ard_3-0-0_106070_2018-07-06_final
2018-07-22 10:51:36	ga_ls8c_ard_3-0-0_106067_2018-07-22_final
2018-07-22 10:52:00	ga_ls8c_ard_3-0-0_106068_2018-07-22_final
2018-07-22 10:52:24	ga_ls8c_ard_3-0-0_106069_2018-07-22_final
2018-07-22 10:52:48	ga_ls8c_ard_3-0-0_106070_2018-07-22_final
2018-07-24 10:42:03	ga_ls8c_ard_3-0-0_104074_2018-07-24_final
2018-07-24 10:42:27	ga_ls8c_ard_3-0-0_104075_2018-07-24_final
2018-07-24 10:42:51	ga_ls8c_ard_3-0-0_104076_2018-07-24_final
2018-07-24 10:43:15	ga_ls8c_ard_3-1-0_104077_2018-07-24_final
2018-07-24 10:43:39	ga_ls8c_ard_3-0-0_104078_2018-07-24_final
2018-07-24 10:44:03	ga_ls8c_ard_3-0-0_104079_2018-07-24_final
2018-07-24 10:44:26	ga_ls8c_ard_3-0-0_104080_2018-07-24_final
2018-07-31 10:46:42	ga_ls8c_ard_3-0-0_105070_2018-07-31_final
2018-07-31 10:47:06	ga_ls8c_ard_3-0-0_105071_2018-07-31_final
2018-07-31 10:47:29	ga_ls8c_ard_3-0-0_105072_2018-07-31_final
2018-07-31 10:47:53	ga_ls8c_ard_3-0-0_105073_2018-07-31_final
2018-07-31 10:48:17	ga_ls8c_ard_3-0-0_105074_2018-07-31_final
2018-07-31 10:48:41	ga_ls8c_ard_3-0-0_105075_2018-07-31_final
2018-08-23 10:51:53	ga_ls8c_ard_3-0-0_106067_2018-08-23_final
2018-08-23 10:52:17	ga_ls8c_ard_3-0-0_106068_2018-08-23_final
2018-08-23 10:52:41	ga_ls8c_ard_3-0-0_106069_2018-08-23_final
2018-08-23 10:53:05	ga_ls8c_ard_3-0-0_106070_2018-08-23_final
2018-09-08 10:51:59	ga_ls8c_ard_3-0-0_106067_2018-09-08_final
2018-09-08 10:52:23	ga_ls8c_ard_3-0-0_106068_2018-09-08_final
2018-09-08 10:52:47	ga_ls8c_ard_3-0-0_106069_2018-09-08_final
2018-09-08 10:53:11	ga_ls8c_ard_3-0-0_106070_2018-09-08_final
2019-03-05 10:42:29	ga_ls8c_ard_3-0-0_104074_2019-03-05_final
2019-03-05 10:42:53	ga_ls8c_ard_3-0-0_104075_2019-03-05_final
2019-03-05 10:43:17	ga_ls8c_ard_3-0-0_104076_2019-03-05_final
2019-03-05 10:43:41	ga_ls8c_ard_3-0-0_104077_2019-03-05_final
2019-03-05 10:44:05	ga_ls8c_ard_3-0-0_104078_2019-03-05_final
2019-03-05 10:44:29	ga_ls8c_ard_3-0-0_104079_2019-03-05_final
2019-03-05 10:44:53	ga_ls8c_ard_3-0-0_104080_2019-03-05_final
2019-03-07 10:33:42	ga_ls8c_ard_3-1-0_102083_2019-03-07_final
2019-05-10 10:33:10	ga_ls8c_ard_3-0-0_102082_2019-05-10_final
2019-05-10 10:33:34	ga_ls8c_ard_3-0-0_102083_2019-05-10_final
2019-06-11 10:33:27	ga_ls8c_ard_3-0-0_102082_2019-06-11_final

Return to ga_ls8c_ard_3 whole collection overview

ga_ls8c_ard_3: Geoscience Australia Landsat 8 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

GA Collection 3

USGS Products

Collection 2 NBAR

Collection 2 NBAR Tiled

Pixel Quality

Collection 2 Level1

Tidal

Water Observations

Fractional Cover

Sentinel 2

Ingested Pixel Quality

Geomedians

TMAD

Telemetry data

Summary

Other Products

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