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
2022-05-02 10:32:15	ga_ls8c_ard_3-2-1_102079_2022-05-02_final
2022-05-06 10:08:23	ga_ls8c_ard_3-2-1_098081_2022-05-06_final
2022-05-08 09:53:39	ga_ls8c_ard_3-2-1_096075_2022-05-08_final
2022-05-08 11:34:32	ga_ls8c_ard_3-2-1_112080_2022-05-08_final
2022-05-10 11:21:47	ga_ls8c_ard_3-2-1_110079_2022-05-10_final
2022-05-13 10:11:50	ga_ls8c_ard_3-2-1_099074_2022-05-13_final
2022-05-13 10:14:38	ga_ls8c_ard_3-2-1_099081_2022-05-13_final
2022-05-15 11:39:58	ga_ls8c_ard_3-2-1_113078_2022-05-15_final
2022-05-26 09:44:32	ga_ls8c_ard_3-2-1_094083_2022-05-26_final
2022-05-29 10:12:16	ga_ls8c_ard_3-2-1_099075_2022-05-29_final
2022-06-08 10:50:18	ga_ls8c_ard_3-2-1_105077_2022-06-08_final
2022-06-09 09:56:41	ga_ls8c_ard_3-2-1_096082_2022-06-09_final
2022-06-23 10:05:34	ga_ls8c_ard_3-2-1_098073_2022-06-23_final
2022-06-23 10:08:46	ga_ls8c_ard_3-2-1_098081_2022-06-23_final
2022-06-25 09:54:01	ga_ls8c_ard_3-2-1_096075_2022-06-25_final
2022-06-25 09:54:25	ga_ls8c_ard_3-2-1_096076_2022-06-25_final
2022-06-25 11:32:54	ga_ls8c_ard_3-2-1_112075_2022-06-25_final
2022-06-26 10:37:17	ga_ls8c_ard_3-2-1_103075_2022-06-26_final
2022-06-26 10:38:52	ga_ls8c_ard_3-2-1_103079_2022-06-26_final
2022-07-02 11:39:05	ga_ls8c_ard_3-2-1_113075_2022-07-02_final
2022-07-06 09:38:17	ga_ls8c_ard_3-2-1_093082_2022-07-06_final
2022-07-06 11:15:58	ga_ls8c_ard_3-2-1_109079_2022-07-06_final
2022-07-09 10:06:47	ga_ls8c_ard_3-2-1_098076_2022-07-09_final
2022-07-10 10:50:50	ga_ls8c_ard_3-2-1_105078_2022-07-10_final
2022-07-11 09:54:25	ga_ls8c_ard_3-2-1_096076_2022-07-11_final
2022-07-11 09:54:49	ga_ls8c_ard_3-2-1_096077_2022-07-11_final
2022-07-13 11:22:08	ga_ls8c_ard_3-2-1_110079_2022-07-13_final
2022-07-14 10:26:54	ga_ls8c_ard_3-2-1_101080_2022-07-14_final
2022-07-16 10:11:44	ga_ls8c_ard_3-2-1_099073_2022-07-16_final
2022-07-18 10:00:13	ga_ls8c_ard_3-2-1_097075_2022-07-18_final
2022-07-19 10:45:05	ga_ls8c_ard_3-2-1_104079_2022-07-19_final
2022-07-25 10:06:53	ga_ls8c_ard_3-2-1_098076_2022-07-25_final
2022-07-26 10:50:58	ga_ls8c_ard_3-2-1_105078_2022-07-26_final
2022-07-27 09:54:33	ga_ls8c_ard_3-2-1_096076_2022-07-27_final
2022-07-28 10:37:25	ga_ls8c_ard_3-2-1_103075_2022-07-28_final
2022-07-29 09:41:49	ga_ls8c_ard_3-2-1_094075_2022-07-29_final
2022-08-04 10:45:16	ga_ls8c_ard_3-2-1_104079_2022-08-04_final
2022-08-07 11:16:12	ga_ls8c_ard_3-2-1_109079_2022-08-07_final
2022-08-09 11:05:03	ga_ls8c_ard_3-2-1_107082_2022-08-09_final
2022-08-10 10:05:50	ga_ls8c_ard_3-2-1_098073_2022-08-10_final
2022-08-11 10:51:06	ga_ls8c_ard_3-2-1_105078_2022-08-11_final
2022-08-18 10:59:18	ga_ls8c_ard_3-2-1_106083_2022-08-18_final
2022-08-26 10:06:17	ga_ls8c_ard_3-2-1_098074_2022-08-26_final
2022-08-28 09:56:43	ga_ls8c_ard_3-2-1_096081_2022-08-28_final
2022-08-30 11:22:26	ga_ls8c_ard_3-2-1_110079_2022-08-30_final
2022-09-05 10:44:58	ga_ls8c_ard_3-2-1_104078_2022-09-05_final
2022-09-05 10:45:22	ga_ls8c_ard_3-2-1_104079_2022-09-05_final
2022-09-06 09:48:33	ga_ls8c_ard_3-2-1_095076_2022-09-06_final
2022-09-11 10:09:08	ga_ls8c_ard_3-2-1_098081_2022-09-11_final
2022-09-14 10:40:28	ga_ls8c_ard_3-2-1_103082_2022-09-14_final
2022-09-15 09:42:03	ga_ls8c_ard_3-2-1_094075_2022-09-15_final
2022-09-15 09:44:27	ga_ls8c_ard_3-2-1_094081_2022-09-15_final
2022-09-20 09:58:13	ga_ls8c_ard_3-2-1_097069_2022-09-20_final
2022-09-21 10:45:04	ga_ls8c_ard_3-2-1_104078_2022-09-21_final
2022-09-22 09:49:27	ga_ls8c_ard_3-2-1_095078_2022-09-22_final
2022-09-27 10:09:35	ga_ls8c_ard_3-2-1_098082_2022-09-27_final
2022-09-28 10:53:14	ga_ls8c_ard_3-2-1_105083_2022-09-28_final
2022-09-29 11:33:42	ga_ls8c_ard_3-2-1_112076_2022-09-29_final
2022-10-10 09:36:11	ga_ls8c_ard_3-2-1_093076_2022-10-10_final
2022-10-14 10:51:06	ga_ls8c_ard_3-2-1_105078_2022-10-14_final
2022-10-15 09:54:41	ga_ls8c_ard_3-2-1_096076_2022-10-15_final
2022-10-17 11:22:26	ga_ls8c_ard_3-2-1_110079_2022-10-17_final
2022-10-20 10:12:53	ga_ls8c_ard_3-2-1_099075_2022-10-20_final
2022-10-22 11:39:50	ga_ls8c_ard_3-2-1_113076_2022-10-22_final
2022-10-22 11:40:38	ga_ls8c_ard_3-2-1_113078_2022-10-22_final
2022-11-01 10:37:41	ga_ls8c_ard_3-2-1_103075_2022-11-01_final
2022-11-08 10:45:27	ga_ls8c_ard_3-2-1_104079_2022-11-08_final
2022-11-09 09:49:25	ga_ls8c_ard_3-2-1_095078_2022-11-09_final
2022-11-09 11:27:54	ga_ls8c_ard_3-2-1_111077_2022-11-09_final
2022-11-11 11:12:44	ga_ls8c_ard_3-2-1_109070_2022-11-11_final
2022-11-23 10:03:18	ga_ls8c_ard_3-2-1_097082_2022-11-23_final
2022-11-24 10:45:22	ga_ls8c_ard_3-2-1_104079_2022-11-24_final
2022-11-25 09:48:33	ga_ls8c_ard_3-2-1_095076_2022-11-25_final
2022-12-02 09:54:21	ga_ls8c_ard_3-2-1_096075_2022-12-02_final
2022-12-03 10:40:24	ga_ls8c_ard_3-2-1_103082_2022-12-03_final
2022-12-11 11:28:36	ga_ls8c_ard_3-2-1_111079_2022-12-11_final
2022-12-16 10:09:01	ga_ls8c_ard_3-2-1_098081_2022-12-16_final
2022-12-21 10:27:05	ga_ls8c_ard_3-2-1_101080_2022-12-21_final
2022-12-25 10:03:09	ga_ls8c_ard_3-2-1_097082_2022-12-25_final
2022-12-26 10:45:13	ga_ls8c_ard_3-2-1_104079_2022-12-26_final
2022-12-27 09:48:00	ga_ls8c_ard_3-2-1_095075_2022-12-27_final
2023-01-03 11:33:29	ga_ls8c_ard_3-2-1_112076_2023-01-03_final
2023-01-06 10:23:06	ga_ls8c_ard_3-2-1_101070_2023-01-06_final
2023-01-08 11:53:36	ga_ls8c_ard_3-2-1_115080_2023-01-08_final
2023-01-10 10:00:21	ga_ls8c_ard_3-2-1_097075_2023-01-10_final
2023-01-20 10:37:21	ga_ls8c_ard_3-2-1_103075_2023-01-20_final
2023-02-06 09:42:59	ga_ls8c_ard_3-2-1_094078_2023-02-06_final
2023-02-06 11:22:16	ga_ls8c_ard_3-2-1_110079_2023-02-06_final
2023-02-11 10:00:17	ga_ls8c_ard_3-2-1_097075_2023-02-11_final
2023-02-11 11:39:34	ga_ls8c_ard_3-2-1_113076_2023-02-11_final
2023-02-18 11:47:38	ga_ls8c_ard_3-2-1_114081_2023-02-18_final
2023-02-20 09:54:21	ga_ls8c_ard_3-2-1_096076_2023-02-20_final
2023-02-22 11:21:38	ga_ls8c_ard_3-2-1_110078_2023-02-22_final
2023-02-27 11:40:06	ga_ls8c_ard_3-2-1_113078_2023-02-27_final
2023-02-28 10:44:29	ga_ls8c_ard_3-2-1_104078_2023-02-28_final
2023-03-01 09:48:03	ga_ls8c_ard_3-2-1_095076_2023-03-01_final
2023-03-02 10:32:07	ga_ls8c_ard_3-2-1_102078_2023-03-02_final
2023-03-02 10:32:31	ga_ls8c_ard_3-2-1_102079_2023-03-02_final
2023-03-05 09:24:30	ga_ls8c_ard_3-2-1_091079_2023-03-04_final
2023-03-06 10:08:57	ga_ls8c_ard_3-2-1_098082_2023-03-06_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