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
2018-09-16 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
2018-09-20 11:17:09	ga_ls8c_ard_3-0-0_110068_2018-09-20_final
2018-09-20 11:17:33	ga_ls8c_ard_3-0-0_110069_2018-09-20_final
2018-09-21 10:21:32	ga_ls8c_ard_3-0-0_101068_2018-09-21_final
2018-09-22 09:25:55	ga_ls8c_ard_3-0-0_092068_2018-09-21_final
2018-09-27 11:23:24	ga_ls8c_ard_3-0-0_111068_2018-09-27_final
2018-09-28 10:27:47	ga_ls8c_ard_3-0-0_102068_2018-09-28_final
2018-09-29 09:32:10	ga_ls8c_ard_3-0-0_093068_2018-09-29_final
2018-09-29 11:11:03	ga_ls8c_ard_3-0-0_109068_2018-09-29_final
2018-09-29 11:11:27	ga_ls8c_ard_3-0-0_109069_2018-09-29_final
2018-09-30 10:15:26	ga_ls8c_ard_3-0-0_100068_2018-09-30_final
2018-09-30 10:15:50	ga_ls8c_ard_3-0-0_100069_2018-09-30_final
2018-10-29 11:23:36	ga_ls8c_ard_3-0-0_111068_2018-10-29_final
2018-10-29 11:24:00	ga_ls8c_ard_3-0-0_111069_2018-10-29_final
2018-10-30 10:27:59	ga_ls8c_ard_3-0-0_102068_2018-10-30_final
2018-10-31 09:32:21	ga_ls8c_ard_3-0-0_093068_2018-10-31_final
2018-10-31 11:11:15	ga_ls8c_ard_3-0-0_109068_2018-10-31_final
2018-11-01 10:15:37	ga_ls8c_ard_3-0-0_100068_2018-11-01_final
2018-11-21 09:50:55	ga_ls8c_ard_3-0-0_096068_2018-11-21_final
2018-11-21 11:29:48	ga_ls8c_ard_3-0-0_112068_2018-11-21_final
2018-11-22 10:34:11	ga_ls8c_ard_3-0-0_103068_2018-11-22_final
2018-11-22 10:34:35	ga_ls8c_ard_3-0-0_103069_2018-11-22_final
2018-11-23 11:17:27	ga_ls8c_ard_3-0-0_110068_2018-11-23_final
2018-11-23 11:17:51	ga_ls8c_ard_3-0-0_110069_2018-11-23_final
2018-11-24 10:21:49	ga_ls8c_ard_3-0-0_101068_2018-11-24_final
2018-11-24 10:22:13	ga_ls8c_ard_3-0-0_101069_2018-11-24_final
2018-11-25 09:26:12	ga_ls8c_ard_3-0-0_092068_2018-11-24_final
2018-11-30 11:23:37	ga_ls8c_ard_3-0-0_111068_2018-11-30_final
2018-12-01 10:27:59	ga_ls8c_ard_3-0-0_102068_2018-12-01_final
2018-12-02 09:32:22	ga_ls8c_ard_3-0-0_093068_2018-12-02_final
2018-12-02 11:11:15	ga_ls8c_ard_3-0-0_109068_2018-12-02_final
2018-12-02 11:11:39	ga_ls8c_ard_3-0-0_109069_2018-12-02_final
2018-12-03 10:15:37	ga_ls8c_ard_3-0-0_100068_2018-12-03_final
2018-12-07 09:50:53	ga_ls8c_ard_3-0-0_096068_2018-12-07_final
2018-12-07 11:29:46	ga_ls8c_ard_3-0-0_112068_2018-12-07_final
2018-12-08 10:34:08	ga_ls8c_ard_3-0-0_103068_2018-12-08_final
2018-12-09 11:17:24	ga_ls8c_ard_3-0-0_110068_2018-12-09_final
2018-12-10 10:21:46	ga_ls8c_ard_3-0-0_101068_2018-12-10_final
2018-12-11 09:26:09	ga_ls8c_ard_3-0-0_092068_2018-12-10_final
2018-12-16 11:23:34	ga_ls8c_ard_3-0-0_111068_2018-12-16_final
2018-12-16 11:23:58	ga_ls8c_ard_3-0-0_111069_2018-12-16_final
2018-12-17 10:27:56	ga_ls8c_ard_3-0-0_102068_2018-12-17_final
2018-12-18 09:32:19	ga_ls8c_ard_3-0-0_093068_2018-12-18_final
2018-12-18 11:11:12	ga_ls8c_ard_3-0-0_109068_2018-12-18_final
2018-12-19 10:15:35	ga_ls8c_ard_3-0-0_100068_2018-12-19_final
2018-12-19 10:15:59	ga_ls8c_ard_3-0-0_100069_2018-12-19_final
2018-12-23 09:50:52	ga_ls8c_ard_3-0-0_096068_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
2019-01-01 11:23:34	ga_ls8c_ard_3-0-0_111068_2019-01-01_final
2019-01-01 11:23:58	ga_ls8c_ard_3-0-0_111069_2019-01-01_final
2019-01-02 10:27:56	ga_ls8c_ard_3-0-0_102068_2019-01-02_final
2019-01-03 09:32:19	ga_ls8c_ard_3-0-0_093068_2019-01-03_final
2019-01-03 11:11:12	ga_ls8c_ard_3-0-0_109068_2019-01-03_final
2019-01-03 11:11:36	ga_ls8c_ard_3-0-0_109069_2019-01-03_final
2019-01-04 10:15:35	ga_ls8c_ard_3-0-0_100068_2019-01-04_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
2019-01-08 09:50:51	ga_ls8c_ard_3-0-0_096068_2019-01-08_final
2019-01-08 09:51:15	ga_ls8c_ard_3-0-0_096069_2019-01-08_final
2019-01-08 11:29:44	ga_ls8c_ard_3-0-0_112068_2019-01-08_final
2019-01-09 10:34:06	ga_ls8c_ard_3-0-0_103068_2019-01-09_final
2019-01-10 11:17:22	ga_ls8c_ard_3-0-0_110068_2019-01-10_final
2019-01-11 10:21:44	ga_ls8c_ard_3-0-0_101068_2019-01-11_final
2019-01-12 09:26:07	ga_ls8c_ard_3-0-0_092068_2019-01-11_final
2019-01-17 11:23:31	ga_ls8c_ard_3-0-0_111068_2019-01-17_final
2019-01-18 10:27:54	ga_ls8c_ard_3-0-0_102068_2019-01-18_final
2019-01-19 09:32:16	ga_ls8c_ard_3-0-0_093068_2019-01-19_final
2019-01-19 11:11:09	ga_ls8c_ard_3-0-0_109068_2019-01-19_final
2019-01-20 10:15:31	ga_ls8c_ard_3-0-0_100068_2019-01-20_final
2023-07-29 10:46:25	ga_ls8c_ard_3-2-1_105068_2023-07-29_final
2023-07-31 10:34:05	ga_ls8c_ard_3-2-1_103068_2023-07-31_final
2023-07-31 10:34:29	ga_ls8c_ard_3-2-1_103069_2023-07-31_final
2023-08-02 10:22:08	ga_ls8c_ard_3-2-1_101069_2023-08-02_final
2023-08-06 09:57:02	ga_ls8c_ard_3-2-1_097068_2023-08-06_final
2023-08-07 10:40:17	ga_ls8c_ard_3-2-1_104068_2023-08-07_final
2023-08-07 10:40:41	ga_ls8c_ard_3-2-1_104069_2023-08-07_final
2023-08-08 11:23:33	ga_ls8c_ard_3-2-1_111068_2023-08-08_final
2023-08-09 10:27:56	ga_ls8c_ard_3-2-1_102068_2023-08-09_final
2023-08-09 10:28:19	ga_ls8c_ard_3-2-1_102069_2023-08-09_final
2023-08-10 11:11:35	ga_ls8c_ard_3-2-1_109069_2023-08-10_final
2023-08-12 10:58:50	ga_ls8c_ard_3-2-1_107068_2023-08-12_final
2023-08-13 10:03:14	ga_ls8c_ard_3-2-1_098068_2023-08-13_final
2023-08-14 10:46:31	ga_ls8c_ard_3-2-1_105068_2023-08-14_final
2023-08-16 10:34:11	ga_ls8c_ard_3-2-1_103068_2023-08-16_final
2023-08-16 10:34:35	ga_ls8c_ard_3-2-1_103069_2023-08-16_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
2023-08-24 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
2023-08-30 10:46:37	ga_ls8c_ard_3-2-1_105068_2023-08-30_final
2023-09-01 10:34:15	ga_ls8c_ard_3-2-1_103068_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