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
2021-09-05 09:33:53	ga_ls8c_ard_3-2-0_093071_2021-09-05_final
2021-09-16 09:18:59	ga_ls8c_ard_3-2-0_090080_2021-09-15_final
2021-09-19 11:29:10	ga_ls8c_ard_3-2-0_111081_2021-09-19_final
2021-09-21 11:17:13	ga_ls8c_ard_3-2-0_109082_2021-09-21_final
2021-09-26 11:36:11	ga_ls8c_ard_3-2-0_112083_2021-09-26_final
2021-09-27 10:38:10	ga_ls8c_ard_3-2-0_103077_2021-09-27_final
2021-09-30 09:35:24	ga_ls8c_ard_3-2-0_092090_2021-09-30_final
2021-10-03 11:42:24	ga_ls8c_ard_3-2-0_113083_2021-10-03_final
2021-10-09 09:27:16	ga_ls8c_ard_3-2-0_091085_2021-10-08_final
2021-10-09 11:02:58	ga_ls8c_ard_3-2-0_107077_2021-10-09_final
2021-10-20 10:41:16	ga_ls8c_ard_3-2-0_104069_2021-10-20_final
2021-10-23 11:17:45	ga_ls8c_ard_3-2-0_109083_2021-10-23_final
2021-10-27 09:15:21	ga_ls8c_ard_3-2-0_089086_2021-10-26_final
2021-10-28 09:52:37	ga_ls8c_ard_3-2-0_096071_2021-10-28_final
2021-10-30 09:45:26	ga_ls8c_ard_3-2-0_094084_2021-10-30_final
2021-11-30 10:35:24	ga_ls8c_ard_3-2-0_103070_2021-11-30_final
2021-12-09 10:30:01	ga_ls8c_ard_3-2-1_102072_2021-12-09_final
2021-12-26 11:15:12	ga_ls8c_ard_3-2-1_109077_2021-12-26_final
2021-12-31 09:56:01	ga_ls8c_ard_3-2-1_096080_2021-12-31_final
2021-12-31 09:56:25	ga_ls8c_ard_3-2-1_096081_2021-12-31_final
2022-01-09 09:50:14	ga_ls8c_ard_3-2-1_095081_2022-01-09_final
2022-02-04 10:26:49	ga_ls8c_ard_3-2-1_101080_2022-02-04_final
2022-02-22 11:53:14	ga_ls8c_ard_3-2-1_115080_2022-02-22_final
2022-02-23 10:56:48	ga_ls8c_ard_3-2-1_106078_2022-02-23_final
2022-03-10 11:50:47	ga_ls8c_ard_3-2-1_115074_2022-03-10_final
2022-03-11 10:54:45	ga_ls8c_ard_3-2-1_106073_2022-03-11_final
2022-04-01 11:17:03	ga_ls8c_ard_3-2-1_109083_2022-04-01_final
2022-04-24 11:23:18	ga_ls8c_ard_3-2-1_110083_2022-04-24_final
2022-04-29 11:41:00	ga_ls8c_ard_3-2-1_113081_2022-04-29_final
2022-04-30 10:42:12	ga_ls8c_ard_3-2-1_104073_2022-04-30_final
2022-05-01 09:46:59	ga_ls8c_ard_3-2-1_095074_2022-05-01_final
2022-05-05 11:03:12	ga_ls8c_ard_3-2-1_107079_2022-05-05_final
2022-05-20 10:20:26	ga_ls8c_ard_3-2-1_100080_2022-05-20_final
2022-05-27 10:25:00	ga_ls8c_ard_3-2-1_101076_2022-05-27_final
2022-05-28 11:05:28	ga_ls8c_ard_3-2-1_108069_2022-05-28_final
2022-06-08 10:47:06	ga_ls8c_ard_3-2-1_105069_2022-06-08_final
2022-06-12 10:24:01	ga_ls8c_ard_3-2-1_101073_2022-06-12_final
2022-06-16 11:41:49	ga_ls8c_ard_3-2-1_113082_2022-06-16_final
2022-06-20 11:17:32	ga_ls8c_ard_3-2-1_109083_2022-06-20_final
2022-06-22 09:24:42	ga_ls8c_ard_3-2-1_091079_2022-06-21_final
2022-06-26 10:34:53	ga_ls8c_ard_3-2-1_103069_2022-06-26_final
2022-06-29 09:31:42	ga_ls8c_ard_3-2-1_092081_2022-06-29_final
2022-07-18 09:59:25	ga_ls8c_ard_3-2-1_097073_2022-07-18_final
2022-07-24 09:26:24	ga_ls8c_ard_3-2-1_091083_2022-07-23_final
2022-07-25 11:47:22	ga_ls8c_ard_3-2-1_114080_2022-07-25_final
2022-07-28 10:36:38	ga_ls8c_ard_3-2-1_103073_2022-07-28_final
2022-08-04 10:41:41	ga_ls8c_ard_3-2-1_104070_2022-08-04_final
2022-08-17 11:51:20	ga_ls8c_ard_3-2-1_115074_2022-08-17_final
2022-09-07 10:31:50	ga_ls8c_ard_3-2-1_102076_2022-09-07_final
2022-09-12 09:14:43	ga_ls8c_ard_3-2-1_089084_2022-09-11_final
2022-09-21 10:43:04	ga_ls8c_ard_3-2-1_104073_2022-09-21_final
2022-09-22 09:48:39	ga_ls8c_ard_3-2-1_095076_2022-09-22_final
2022-09-24 11:15:34	ga_ls8c_ard_3-2-1_109077_2022-09-24_final
2022-10-01 11:23:44	ga_ls8c_ard_3-2-1_110082_2022-10-01_final
2022-10-08 11:27:28	ga_ls8c_ard_3-2-1_111076_2022-10-08_final
2022-10-22 10:01:21	ga_ls8c_ard_3-2-1_097077_2022-10-22_final
2022-11-03 10:24:08	ga_ls8c_ard_3-2-1_101072_2022-11-03_final
2022-11-26 10:31:01	ga_ls8c_ard_3-2-1_102074_2022-11-26_final
2022-11-30 11:47:35	ga_ls8c_ard_3-2-1_114080_2022-11-30_final
2022-12-16 11:46:42	ga_ls8c_ard_3-2-1_114078_2022-12-16_final
2022-12-16 11:47:30	ga_ls8c_ard_3-2-1_114080_2022-12-16_final
2022-12-22 09:35:02	ga_ls8c_ard_3-2-1_092089_2022-12-22_final
2022-12-27 09:51:36	ga_ls8c_ard_3-2-1_095084_2022-12-27_final
2022-12-27 09:52:48	ga_ls8c_ard_3-2-1_095087_2022-12-27_final
2022-12-29 11:15:20	ga_ls8c_ard_3-2-1_109077_2022-12-29_final
2023-01-06 10:26:17	ga_ls8c_ard_3-2-1_101078_2023-01-06_final
2023-01-12 11:29:38	ga_ls8c_ard_3-2-1_111082_2023-01-12_final
2023-01-14 09:38:22	ga_ls8c_ard_3-2-1_093082_2023-01-14_final
2023-01-26 10:02:43	ga_ls8c_ard_3-2-1_097081_2023-01-26_final
2023-02-03 09:16:53	ga_ls8c_ard_3-2-1_089090_2023-02-02_final
2023-02-05 10:38:37	ga_ls8c_ard_3-2-1_103078_2023-02-05_final
2023-02-08 11:08:42	ga_ls8c_ard_3-2-1_108076_2023-02-08_final
2023-02-09 11:53:33	ga_ls8c_ard_3-2-1_115080_2023-02-09_final
2023-02-10 09:19:50	ga_ls8c_ard_3-2-1_090082_2023-02-09_final
2023-02-20 11:32:02	ga_ls8c_ard_3-2-1_112073_2023-02-20_final
2023-02-21 10:38:47	ga_ls8c_ard_3-2-1_103079_2023-02-21_final
2023-02-24 09:30:44	ga_ls8c_ard_3-2-1_092079_2023-02-24_final
2023-02-25 11:50:52	ga_ls8c_ard_3-2-1_115074_2023-02-25_final
2023-03-19 11:12:27	ga_ls8c_ard_3-2-1_109071_2023-03-19_final
2023-03-23 10:48:27	ga_ls8c_ard_3-2-1_105073_2023-03-23_final
2023-04-02 11:27:02	ga_ls8c_ard_3-2-1_111077_2023-04-02_final
2023-04-08 09:13:45	ga_ls8c_ard_3-2-1_089084_2023-04-07_final
2023-04-27 11:21:00	ga_ls8c_ard_3-2-1_110078_2023-04-27_final
2023-05-20 09:46:29	ga_ls8c_ard_3-2-1_095074_2023-05-20_final
2023-05-28 10:35:57	ga_ls8c_ard_3-2-1_103074_2023-05-28_final
2023-05-29 09:43:08	ga_ls8c_ard_3-2-1_094081_2023-05-29_final
2023-06-02 10:58:05	ga_ls8c_ard_3-2-1_106083_2023-06-02_final
2023-06-08 10:19:54	ga_ls8c_ard_3-2-1_100080_2023-06-08_final
2023-06-10 10:02:22	ga_ls8c_ard_3-2-1_098067_2023-06-10_final
2023-06-10 11:44:27	ga_ls8c_ard_3-2-1_114075_2023-06-10_final
2023-06-16 11:05:49	ga_ls8c_ard_3-2-1_108071_2023-06-16_final
2023-06-20 10:40:42	ga_ls8c_ard_3-2-1_104070_2023-06-20_final
2023-06-23 09:34:19	ga_ls8c_ard_3-2-1_093074_2023-06-23_final
2023-06-23 09:34:43	ga_ls8c_ard_3-2-1_093075_2023-06-23_final
2023-07-10 10:20:11	ga_ls8c_ard_3-2-1_100080_2023-07-10_final
2023-08-11 11:57:38	ga_ls8c_ard_3-2-1_116076_2023-08-11_final
2023-08-25 10:31:39	ga_ls8c_ard_3-2-1_102077_2023-08-25_final
2023-08-27 11:58:35	ga_ls8c_ard_3-2-1_116078_2023-08-27_final
2023-09-09 11:23:41	ga_ls8c_ard_3-2-1_111068_2023-09-09_final
2023-09-11 11:16:32	ga_ls8c_ard_3-2-1_109081_2023-09-11_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

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years