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
2019-07-11 10:40:22	ga_ls8c_ard_3-1-0_104068_2019-07-11_final
2019-07-11 10:40:46	ga_ls8c_ard_3-1-0_104069_2019-07-11_final
2019-07-12 11:23:38	ga_ls8c_ard_3-1-0_111068_2019-07-12_final
2019-07-12 11:24:02	ga_ls8c_ard_3-1-0_111069_2019-07-12_final
2019-07-17 10:03:18	ga_ls8c_ard_3-1-0_098068_2019-07-17_final
2019-07-17 10:03:42	ga_ls8c_ard_3-1-0_098069_2019-07-17_final
2019-07-18 10:46:34	ga_ls8c_ard_3-1-0_105068_2019-07-18_final
2019-07-18 10:46:57	ga_ls8c_ard_3-1-0_105069_2019-07-18_final
2019-07-19 09:50:56	ga_ls8c_ard_3-1-0_096068_2019-07-19_final
2019-07-19 09:51:20	ga_ls8c_ard_3-1-0_096069_2019-07-19_final
2019-07-19 11:29:50	ga_ls8c_ard_3-1-0_112068_2019-07-19_final
2019-07-19 11:30:13	ga_ls8c_ard_3-1-0_112069_2019-07-19_final
2019-07-20 10:34:13	ga_ls8c_ard_3-1-0_103068_2019-07-20_final
2019-07-20 10:34:37	ga_ls8c_ard_3-1-0_103069_2019-07-20_final
2019-07-24 10:09:31	ga_ls8c_ard_3-1-0_099068_2019-07-24_final
2019-07-24 10:09:55	ga_ls8c_ard_3-1-0_099069_2019-07-24_final
2019-07-25 10:52:47	ga_ls8c_ard_3-1-0_106068_2019-07-25_final
2019-07-25 10:53:11	ga_ls8c_ard_3-1-0_106069_2019-07-25_final
2019-08-09 10:09:38	ga_ls8c_ard_3-1-0_099068_2019-08-09_final
2019-08-09 10:10:02	ga_ls8c_ard_3-1-0_099069_2019-08-09_final
2019-08-10 10:52:54	ga_ls8c_ard_3-1-0_106068_2019-08-10_final
2019-08-10 10:53:18	ga_ls8c_ard_3-1-0_106069_2019-08-10_final
2019-08-11 09:57:17	ga_ls8c_ard_3-1-0_097068_2019-08-11_final
2019-08-11 09:57:41	ga_ls8c_ard_3-1-0_097069_2019-08-11_final
2019-08-12 10:40:33	ga_ls8c_ard_3-1-0_104068_2019-08-12_final
2019-08-12 10:40:57	ga_ls8c_ard_3-1-0_104069_2019-08-12_final
2019-08-13 11:23:49	ga_ls8c_ard_3-1-0_111068_2019-08-13_final
2019-08-13 11:24:13	ga_ls8c_ard_3-1-0_111069_2019-08-13_final
2019-08-14 10:28:12	ga_ls8c_ard_3-1-0_102068_2019-08-14_final
2019-08-14 10:28:36	ga_ls8c_ard_3-1-0_102069_2019-08-14_final
2019-08-15 09:32:35	ga_ls8c_ard_3-1-0_093068_2019-08-15_final
2019-08-15 11:11:28	ga_ls8c_ard_3-1-0_109068_2019-08-15_final
2019-08-15 11:11:52	ga_ls8c_ard_3-1-0_109069_2019-08-15_final
2019-08-16 10:15:51	ga_ls8c_ard_3-1-0_100068_2019-08-16_final
2019-08-16 10:16:15	ga_ls8c_ard_3-1-0_100069_2019-08-16_final
2019-08-17 09:20:14	ga_ls8c_ard_3-1-0_091068_2019-08-16_final
2019-09-06 10:34:28	ga_ls8c_ard_3-1-0_103068_2019-09-06_final
2019-09-06 10:34:52	ga_ls8c_ard_3-1-0_103069_2019-09-06_final
2019-09-07 11:17:44	ga_ls8c_ard_3-1-0_110068_2019-09-07_final
2019-09-07 11:18:08	ga_ls8c_ard_3-1-0_110069_2019-09-07_final
2019-09-08 10:22:07	ga_ls8c_ard_3-1-0_101068_2019-09-08_final
2019-09-08 10:22:31	ga_ls8c_ard_3-1-0_101069_2019-09-08_final
2019-09-09 09:26:30	ga_ls8c_ard_3-1-0_092068_2019-09-08_final
2019-10-07 09:51:22	ga_ls8c_ard_3-1-0_096068_2019-10-07_final
2019-10-07 09:51:46	ga_ls8c_ard_3-1-0_096069_2019-10-07_final
2019-10-07 11:30:15	ga_ls8c_ard_3-1-0_112068_2019-10-07_final
2019-10-07 11:30:39	ga_ls8c_ard_3-1-0_112069_2019-10-07_final
2019-10-08 10:34:38	ga_ls8c_ard_3-1-0_103068_2019-10-08_final
2019-10-08 10:35:01	ga_ls8c_ard_3-1-0_103069_2019-10-08_final
2019-10-12 10:09:55	ga_ls8c_ard_3-1-0_099068_2019-10-12_final
2019-10-12 10:10:19	ga_ls8c_ard_3-1-0_099069_2019-10-12_final
2019-10-13 10:53:11	ga_ls8c_ard_3-1-0_106068_2019-10-13_final
2019-10-13 10:53:35	ga_ls8c_ard_3-1-0_106069_2019-10-13_final
2019-10-17 10:28:28	ga_ls8c_ard_3-1-0_102068_2019-10-17_final
2019-10-17 10:28:52	ga_ls8c_ard_3-1-0_102069_2019-10-17_final
2019-10-18 09:32:50	ga_ls8c_ard_3-1-0_093068_2019-10-18_final
2019-10-18 11:11:44	ga_ls8c_ard_3-1-0_109068_2019-10-18_final
2019-10-18 11:12:07	ga_ls8c_ard_3-1-0_109069_2019-10-18_final
2019-10-19 10:16:06	ga_ls8c_ard_3-1-0_100068_2019-10-19_final
2019-10-19 10:16:30	ga_ls8c_ard_3-1-0_100069_2019-10-19_final
2019-10-20 09:20:29	ga_ls8c_ard_3-1-0_091068_2019-10-19_final
2019-10-24 10:34:39	ga_ls8c_ard_3-1-0_103068_2019-10-24_final
2019-10-24 10:35:03	ga_ls8c_ard_3-1-0_103069_2019-10-24_final
2019-10-25 11:17:54	ga_ls8c_ard_3-1-0_110068_2019-10-25_final
2019-10-25 11:18:18	ga_ls8c_ard_3-1-0_110069_2019-10-25_final
2019-10-26 10:22:17	ga_ls8c_ard_3-1-0_101068_2019-10-26_final
2019-10-26 10:22:41	ga_ls8c_ard_3-1-0_101069_2019-10-26_final
2019-10-27 09:26:40	ga_ls8c_ard_3-1-0_092068_2019-10-26_final
2019-12-04 10:28:23	ga_ls8c_ard_3-1-0_102068_2019-12-04_final
2019-12-04 10:28:47	ga_ls8c_ard_3-1-0_102069_2019-12-04_final
2019-12-05 09:32:46	ga_ls8c_ard_3-1-0_093068_2019-12-05_final
2019-12-05 11:11:39	ga_ls8c_ard_3-1-0_109068_2019-12-05_final
2019-12-05 11:12:03	ga_ls8c_ard_3-1-0_109069_2019-12-05_final
2019-12-06 10:16:01	ga_ls8c_ard_3-1-0_100068_2019-12-06_final
2019-12-06 10:16:25	ga_ls8c_ard_3-1-0_100069_2019-12-06_final
2019-12-07 09:20:24	ga_ls8c_ard_3-1-0_091068_2019-12-06_final
2022-08-31 10:22:49	ga_ls8c_ard_3-2-1_101069_2022-08-31_final
2022-09-01 11:06:05	ga_ls8c_ard_3-2-1_108069_2022-09-01_final
2022-09-02 10:10:03	ga_ls8c_ard_3-2-1_099068_2022-09-02_final
2022-09-02 10:10:27	ga_ls8c_ard_3-2-1_099069_2022-09-02_final
2022-09-03 10:53:19	ga_ls8c_ard_3-2-1_106068_2022-09-03_final
2022-09-03 10:53:43	ga_ls8c_ard_3-2-1_106069_2022-09-03_final
2022-09-04 09:57:42	ga_ls8c_ard_3-2-1_097068_2022-09-04_final
2022-09-04 09:58:06	ga_ls8c_ard_3-2-1_097069_2022-09-04_final
2022-10-22 09:57:45	ga_ls8c_ard_3-2-1_097068_2022-10-22_final
2022-10-22 09:58:09	ga_ls8c_ard_3-2-1_097069_2022-10-22_final
2022-10-23 10:41:02	ga_ls8c_ard_3-2-1_104068_2022-10-23_final
2022-10-23 10:41:26	ga_ls8c_ard_3-2-1_104069_2022-10-23_final
2022-10-24 11:24:18	ga_ls8c_ard_3-2-1_111068_2022-10-24_final
2022-10-24 11:24:42	ga_ls8c_ard_3-2-1_111069_2022-10-24_final
2022-10-25 10:28:41	ga_ls8c_ard_3-2-1_102068_2022-10-25_final
2022-10-25 10:29:05	ga_ls8c_ard_3-2-1_102069_2022-10-25_final
2022-10-26 11:12:21	ga_ls8c_ard_3-2-1_109069_2022-10-26_final
2022-10-28 10:59:36	ga_ls8c_ard_3-2-1_107068_2022-10-28_final
2022-10-28 11:00:00	ga_ls8c_ard_3-2-1_107069_2022-10-28_final
2022-10-29 10:03:59	ga_ls8c_ard_3-2-1_098068_2022-10-29_final
2022-10-29 10:04:23	ga_ls8c_ard_3-2-1_098069_2022-10-29_final
2023-01-11 10:40:48	ga_ls8c_ard_3-2-1_104068_2023-01-11_final
2023-01-14 11:12:04	ga_ls8c_ard_3-2-1_109069_2023-01-14_final
2023-01-16 10:59:16	ga_ls8c_ard_3-2-1_107068_2023-01-16_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years