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
2018-05-29 09:49:49	ga_ls8c_ard_3-0-0_096068_2018-05-29_final
2018-05-29 11:28:42	ga_ls8c_ard_3-0-0_112068_2018-05-29_final
2018-05-30 10:33:04	ga_ls8c_ard_3-0-0_103068_2018-05-30_final
2018-05-31 11:16:19	ga_ls8c_ard_3-0-0_110068_2018-05-31_final
2018-06-01 10:20:41	ga_ls8c_ard_3-0-0_101068_2018-06-01_final
2018-06-02 09:25:03	ga_ls8c_ard_3-0-0_092068_2018-06-01_final
2018-06-14 09:49:52	ga_ls8c_ard_3-0-0_096068_2018-06-14_final
2018-06-14 09:50:16	ga_ls8c_ard_3-0-0_096069_2018-06-14_final
2018-06-15 10:33:08	ga_ls8c_ard_3-0-0_103068_2018-06-15_final
2018-06-16 11:16:25	ga_ls8c_ard_3-0-0_110068_2018-06-16_final
2018-06-16 11:16:49	ga_ls8c_ard_3-0-0_110069_2018-06-16_final
2018-06-17 10:20:48	ga_ls8c_ard_3-0-0_101068_2018-06-17_final
2018-06-17 10:21:12	ga_ls8c_ard_3-0-0_101069_2018-06-17_final
2018-06-18 09:25:11	ga_ls8c_ard_3-0-0_092068_2018-06-17_final
2018-07-02 11:16:35	ga_ls8c_ard_3-0-0_110068_2018-07-02_final
2018-07-02 11:16:58	ga_ls8c_ard_3-0-0_110069_2018-07-02_final
2018-07-03 10:20:58	ga_ls8c_ard_3-0-0_101068_2018-07-03_final
2018-07-03 10:21:22	ga_ls8c_ard_3-0-0_101069_2018-07-03_final
2018-07-04 09:25:21	ga_ls8c_ard_3-0-0_092068_2018-07-03_final
2018-07-18 11:16:42	ga_ls8c_ard_3-0-0_110068_2018-07-18_final
2018-07-18 11:17:06	ga_ls8c_ard_3-0-0_110069_2018-07-18_final
2018-07-19 10:21:05	ga_ls8c_ard_3-0-0_101068_2018-07-19_final
2018-07-20 09:25:28	ga_ls8c_ard_3-0-0_092068_2018-07-19_final
2018-07-25 11:22:55	ga_ls8c_ard_3-0-0_111068_2018-07-25_final
2018-07-25 11:23:19	ga_ls8c_ard_3-0-0_111069_2018-07-25_final
2018-07-26 10:27:18	ga_ls8c_ard_3-0-0_102068_2018-07-26_final
2018-07-26 10:27:42	ga_ls8c_ard_3-0-0_102069_2018-07-26_final
2018-07-27 09:31:41	ga_ls8c_ard_3-0-0_093068_2018-07-27_final
2018-07-27 11:10:34	ga_ls8c_ard_3-0-0_109068_2018-07-27_final
2018-07-27 11:10:58	ga_ls8c_ard_3-0-0_109069_2018-07-27_final
2018-07-28 10:14:58	ga_ls8c_ard_3-0-0_100068_2018-07-28_final
2018-07-28 10:15:22	ga_ls8c_ard_3-0-0_100069_2018-07-28_final
2018-08-01 09:50:17	ga_ls8c_ard_3-0-0_096068_2018-08-01_final
2018-08-01 09:50:41	ga_ls8c_ard_3-0-0_096069_2018-08-01_final
2018-08-01 11:29:10	ga_ls8c_ard_3-0-0_112068_2018-08-01_final
2018-08-01 11:29:34	ga_ls8c_ard_3-0-0_112069_2018-08-01_final
2018-08-02 10:33:33	ga_ls8c_ard_3-0-0_103068_2018-08-02_final
2018-08-02 10:33:57	ga_ls8c_ard_3-0-0_103069_2018-08-02_final
2018-08-03 11:16:50	ga_ls8c_ard_3-0-0_110068_2018-08-03_final
2018-08-03 11:17:14	ga_ls8c_ard_3-0-0_110069_2018-08-03_final
2018-08-04 10:21:13	ga_ls8c_ard_3-0-0_101068_2018-08-04_final
2018-08-04 10:21:37	ga_ls8c_ard_3-0-0_101069_2018-08-04_final
2018-08-05 09:25:36	ga_ls8c_ard_3-0-0_092068_2018-08-04_final
2018-08-17 09:50:26	ga_ls8c_ard_3-0-0_096068_2018-08-17_final
2018-08-17 09:50:50	ga_ls8c_ard_3-0-0_096069_2018-08-17_final
2018-08-17 11:29:19	ga_ls8c_ard_3-0-0_112068_2018-08-17_final
2018-08-18 10:33:42	ga_ls8c_ard_3-0-0_103068_2018-08-18_final
2018-08-18 10:34:06	ga_ls8c_ard_3-0-0_103069_2018-08-18_final
2018-08-19 11:16:58	ga_ls8c_ard_3-0-0_110068_2018-08-19_final
2018-08-20 10:21:22	ga_ls8c_ard_3-0-0_101068_2018-08-20_final
2018-08-20 10:21:45	ga_ls8c_ard_3-0-0_101069_2018-08-20_final
2018-08-21 09:25:45	ga_ls8c_ard_3-0-0_092068_2018-08-20_final
2018-09-02 09:50:33	ga_ls8c_ard_3-0-0_096068_2018-09-02_final
2018-09-02 11:29:26	ga_ls8c_ard_3-0-0_112068_2018-09-02_final
2018-09-02 11:29:50	ga_ls8c_ard_3-0-0_112069_2018-09-02_final
2018-09-03 10:33:49	ga_ls8c_ard_3-0-0_103068_2018-09-03_final
2018-09-03 10:34:13	ga_ls8c_ard_3-0-0_103069_2018-09-03_final
2018-09-04 11:17:05	ga_ls8c_ard_3-0-0_110068_2018-09-04_final
2018-09-04 11:17:29	ga_ls8c_ard_3-0-0_110069_2018-09-04_final
2018-09-05 10:21:28	ga_ls8c_ard_3-0-0_101068_2018-09-05_final
2018-09-06 09:25:51	ga_ls8c_ard_3-0-0_092068_2018-09-05_final
2018-09-16 10:02:58	ga_ls8c_ard_3-0-0_098068_2018-09-16_final
2018-09-16 10:03:22	ga_ls8c_ard_3-0-0_098069_2018-09-16_final
2018-09-17 10:46:14	ga_ls8c_ard_3-0-0_105068_2018-09-17_final
2018-09-17 10:46:38	ga_ls8c_ard_3-0-0_105069_2018-09-17_final
2018-10-04 09:50:45	ga_ls8c_ard_3-0-0_096068_2018-10-04_final
2018-10-04 09:51:09	ga_ls8c_ard_3-0-0_096069_2018-10-04_final
2018-10-04 11:29:38	ga_ls8c_ard_3-0-0_112068_2018-10-04_final
2018-10-05 10:34:01	ga_ls8c_ard_3-0-0_103068_2018-10-05_final
2018-10-05 10:34:25	ga_ls8c_ard_3-0-0_103069_2018-10-05_final
2018-10-06 11:17:17	ga_ls8c_ard_3-0-0_110068_2018-10-06_final
2018-10-06 11:17:41	ga_ls8c_ard_3-0-0_110069_2018-10-06_final
2018-10-07 10:21:40	ga_ls8c_ard_3-0-0_101068_2018-10-07_final
2018-10-07 10:22:04	ga_ls8c_ard_3-0-0_101069_2018-10-07_final
2018-10-08 09:26:03	ga_ls8c_ard_3-0-0_092068_2018-10-07_final
2018-12-23 09:50:52	ga_ls8c_ard_3-0-0_096068_2018-12-23_final
2018-12-23 09:51:16	ga_ls8c_ard_3-0-0_096069_2018-12-23_final
2018-12-23 11:29:45	ga_ls8c_ard_3-0-0_112068_2018-12-23_final
2018-12-24 10:34:08	ga_ls8c_ard_3-0-0_103068_2018-12-24_final
2018-12-25 11:17:23	ga_ls8c_ard_3-0-0_110068_2018-12-25_final
2018-12-26 10:21:46	ga_ls8c_ard_3-0-0_101068_2018-12-26_final
2018-12-27 09:26:09	ga_ls8c_ard_3-0-0_092068_2018-12-26_final
2019-01-06 10:03:13	ga_ls8c_ard_3-0-0_098068_2019-01-06_final
2019-01-07 10:46:28	ga_ls8c_ard_3-0-0_105068_2019-01-07_final
2019-01-07 10:46:52	ga_ls8c_ard_3-0-0_105069_2019-01-07_final
2023-08-17 11:17:51	ga_ls8c_ard_3-2-1_110069_2023-08-17_final
2023-08-18 10:22:14	ga_ls8c_ard_3-2-1_101069_2023-08-18_final
2023-08-19 11:05:31	ga_ls8c_ard_3-2-1_108069_2023-08-19_final
2023-08-20 10:09:30	ga_ls8c_ard_3-2-1_099068_2023-08-20_final
2023-08-21 10:52:46	ga_ls8c_ard_3-2-1_106068_2023-08-21_final
2023-08-21 10:53:10	ga_ls8c_ard_3-2-1_106069_2023-08-21_final
2023-08-22 09:57:09	ga_ls8c_ard_3-2-1_097068_2023-08-22_final
2023-08-23 10:40:25	ga_ls8c_ard_3-2-1_104068_2023-08-23_final
2023-08-23 10:40:49	ga_ls8c_ard_3-2-1_104069_2023-08-23_final
2023-08-24 11:23:41	ga_ls8c_ard_3-2-1_111068_2023-08-24_final
2023-08-25 10:28:04	ga_ls8c_ard_3-2-1_102068_2023-08-25_final
2023-08-28 10:58:58	ga_ls8c_ard_3-2-1_107068_2023-08-28_final
2023-08-29 10:03:21	ga_ls8c_ard_3-2-1_098068_2023-08-29_final
2023-09-01 10:34:15	ga_ls8c_ard_3-2-1_103068_2023-09-01_final
2023-09-01 10:34:39	ga_ls8c_ard_3-2-1_103069_2023-09-01_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

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years