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
2022-02-16 09:12:35	ga_ls8c_ard_3-2-1_089080_2022-02-15_final
2022-02-27 10:30:29	ga_ls8c_ard_3-2-1_102074_2022-02-27_final
2022-02-28 09:38:03	ga_ls8c_ard_3-2-1_093082_2022-02-28_final
2022-03-07 09:45:48	ga_ls8c_ard_3-2-1_094086_2022-03-07_final
2022-03-27 10:56:10	ga_ls8c_ard_3-2-1_106077_2022-03-27_final
2022-03-29 10:41:22	ga_ls8c_ard_3-2-1_104071_2022-03-29_final
2022-04-03 09:24:13	ga_ls8c_ard_3-2-1_091079_2022-04-02_final
2022-04-06 09:55:57	ga_ls8c_ard_3-2-1_096081_2022-04-06_final
2022-04-10 09:31:40	ga_ls8c_ard_3-2-1_092082_2022-04-10_final
2022-04-13 10:00:59	ga_ls8c_ard_3-2-1_097078_2022-04-13_final
2022-04-15 09:47:50	ga_ls8c_ard_3-2-1_095076_2022-04-15_final
2022-04-17 09:36:16	ga_ls8c_ard_3-2-1_093078_2022-04-17_final
2022-04-21 10:50:49	ga_ls8c_ard_3-2-1_105079_2022-04-21_final
2022-05-01 09:51:23	ga_ls8c_ard_3-2-1_095085_2022-05-01_final
2022-05-01 11:28:40	ga_ls8c_ard_3-2-1_111081_2022-05-01_final
2022-05-05 11:00:24	ga_ls8c_ard_3-2-1_107072_2022-05-05_final
2022-05-25 10:35:23	ga_ls8c_ard_3-2-1_103071_2022-05-25_final
2022-05-29 10:16:15	ga_ls8c_ard_3-2-1_099085_2022-05-29_final
2022-05-30 09:21:03	ga_ls8c_ard_3-2-1_090086_2022-05-29_final
2022-05-31 10:02:20	ga_ls8c_ard_3-2-1_097081_2022-05-31_final
2022-06-01 10:41:13	ga_ls8c_ard_3-2-1_104070_2022-06-01_final
2022-06-15 10:57:21	ga_ls8c_ard_3-2-1_106079_2022-06-15_final
2022-06-24 09:13:08	ga_ls8c_ard_3-2-1_089081_2022-06-23_final
2022-06-24 10:51:38	ga_ls8c_ard_3-2-1_105080_2022-06-24_final
2022-06-29 09:30:30	ga_ls8c_ard_3-2-1_092078_2022-06-29_final
2022-07-06 09:39:05	ga_ls8c_ard_3-2-1_093084_2022-07-06_final
2022-07-07 10:20:44	ga_ls8c_ard_3-2-1_100080_2022-07-07_final
2022-07-07 10:21:08	ga_ls8c_ard_3-2-1_100081_2022-07-07_final
2022-07-13 09:42:03	ga_ls8c_ard_3-2-1_094076_2022-07-13_final
2022-07-14 10:24:54	ga_ls8c_ard_3-2-1_101075_2022-07-14_final
2022-07-20 09:47:29	ga_ls8c_ard_3-2-1_095074_2022-07-20_final
2022-07-20 09:49:29	ga_ls8c_ard_3-2-1_095079_2022-07-20_final
2022-07-25 10:06:29	ga_ls8c_ard_3-2-1_098075_2022-07-25_final
2022-07-27 09:55:45	ga_ls8c_ard_3-2-1_096079_2022-07-27_final
2022-07-29 11:21:54	ga_ls8c_ard_3-2-1_110078_2022-07-29_final
2022-07-31 11:09:57	ga_ls8c_ard_3-2-1_108079_2022-07-31_final
2022-08-04 10:44:28	ga_ls8c_ard_3-2-1_104077_2022-08-04_final
2022-08-05 09:50:51	ga_ls8c_ard_3-2-1_095082_2022-08-05_final
2022-08-10 10:06:38	ga_ls8c_ard_3-2-1_098075_2022-08-10_final
2022-08-11 09:14:13	ga_ls8c_ard_3-2-1_089083_2022-08-10_final
2022-08-26 10:06:41	ga_ls8c_ard_3-2-1_098075_2022-08-26_final
2022-09-01 11:11:16	ga_ls8c_ard_3-2-1_108082_2022-09-01_final
2022-09-15 09:42:27	ga_ls8c_ard_3-2-1_094076_2022-09-15_final
2022-09-17 09:31:18	ga_ls8c_ard_3-2-1_092079_2022-09-17_final
2022-09-17 11:06:11	ga_ls8c_ard_3-2-1_108069_2022-09-17_final
2022-09-18 10:13:22	ga_ls8c_ard_3-2-1_099076_2022-09-18_final
2022-09-26 11:01:37	ga_ls8c_ard_3-2-1_107073_2022-09-26_final
2022-09-29 11:34:06	ga_ls8c_ard_3-2-1_112077_2022-09-29_final
2022-09-30 10:38:29	ga_ls8c_ard_3-2-1_103077_2022-09-30_final
2022-10-03 09:32:53	ga_ls8c_ard_3-2-1_092083_2022-10-03_final
2022-10-03 11:06:58	ga_ls8c_ard_3-2-1_108071_2022-10-03_final
2022-10-07 10:43:25	ga_ls8c_ard_3-2-1_104074_2022-10-07_final
2022-10-14 10:50:42	ga_ls8c_ard_3-2-1_105077_2022-10-14_final
2022-10-15 09:53:29	ga_ls8c_ard_3-2-1_096073_2022-10-15_final
2022-10-30 10:52:02	ga_ls8c_ard_3-2-1_105080_2022-10-30_final
2022-11-04 09:31:18	ga_ls8c_ard_3-2-1_092079_2022-11-04_final
2022-11-05 10:15:45	ga_ls8c_ard_3-2-1_099082_2022-11-05_final
2022-11-05 11:52:39	ga_ls8c_ard_3-2-1_115077_2022-11-05_final
2022-11-11 09:36:14	ga_ls8c_ard_3-2-1_093076_2022-11-11_final
2022-11-14 11:47:35	ga_ls8c_ard_3-2-1_114080_2022-11-14_final
2022-11-16 09:55:07	ga_ls8c_ard_3-2-1_096077_2022-11-16_final
2022-11-17 10:38:22	ga_ls8c_ard_3-2-1_103077_2022-11-17_final
2022-11-25 11:28:14	ga_ls8c_ard_3-2-1_111078_2022-11-25_final
2022-11-30 11:47:11	ga_ls8c_ard_3-2-1_114079_2022-11-30_final
2022-12-03 10:38:48	ga_ls8c_ard_3-2-1_103078_2022-12-03_final
2022-12-04 11:21:40	ga_ls8c_ard_3-2-1_110077_2022-12-04_final
2022-12-11 09:46:32	ga_ls8c_ard_3-2-1_095071_2022-12-11_final
2022-12-22 11:11:55	ga_ls8c_ard_3-2-1_108084_2022-12-22_final
2022-12-23 10:15:05	ga_ls8c_ard_3-2-1_099081_2022-12-23_final
2023-01-01 10:07:21	ga_ls8c_ard_3-2-1_098077_2023-01-01_final
2023-01-02 10:51:49	ga_ls8c_ard_3-2-1_105080_2023-01-02_final
2023-01-05 09:43:50	ga_ls8c_ard_3-2-1_094080_2023-01-05_final
2023-01-07 09:35:27	ga_ls8c_ard_3-2-1_092090_2023-01-07_final
2023-01-14 09:38:46	ga_ls8c_ard_3-2-1_093083_2023-01-14_final
2023-01-18 10:48:53	ga_ls8c_ard_3-2-1_105073_2023-01-18_final
2023-01-22 10:23:01	ga_ls8c_ard_3-2-1_101070_2023-01-22_final
2023-01-26 09:59:32	ga_ls8c_ard_3-2-1_097073_2023-01-26_final
2023-02-07 10:23:51	ga_ls8c_ard_3-2-1_101072_2023-02-07_final
2023-02-08 09:31:01	ga_ls8c_ard_3-2-1_092079_2023-02-08_final
2023-02-08 09:32:13	ga_ls8c_ard_3-2-1_092082_2023-02-08_final
2023-02-10 10:59:06	ga_ls8c_ard_3-2-1_106083_2023-02-10_final
2023-02-13 09:48:17	ga_ls8c_ard_3-2-1_095076_2023-02-13_final
2023-02-20 11:35:38	ga_ls8c_ard_3-2-1_112082_2023-02-20_final
2023-02-23 10:25:11	ga_ls8c_ard_3-2-1_101076_2023-02-23_final
2023-03-13 11:53:10	ga_ls8c_ard_3-2-1_115080_2023-03-13_final
2023-03-14 09:18:16	ga_ls8c_ard_3-2-1_090079_2023-03-13_final
2023-03-29 10:16:07	ga_ls8c_ard_3-2-1_099085_2023-03-29_final
2023-04-14 10:12:17	ga_ls8c_ard_3-2-1_099076_2023-04-14_final
2023-04-21 11:57:18	ga_ls8c_ard_3-2-1_116076_2023-04-21_final
2023-04-27 11:23:48	ga_ls8c_ard_3-2-1_110085_2023-04-27_final
2023-04-29 09:28:57	ga_ls8c_ard_3-2-1_092076_2023-04-28_final
2023-05-03 10:40:17	ga_ls8c_ard_3-2-1_104069_2023-05-03_final
2023-05-04 11:27:07	ga_ls8c_ard_3-2-1_111078_2023-05-04_final
2023-05-05 10:31:05	ga_ls8c_ard_3-2-1_102077_2023-05-05_final
2023-05-06 11:14:20	ga_ls8c_ard_3-2-1_109077_2023-05-06_final
2023-05-06 11:14:44	ga_ls8c_ard_3-2-1_109078_2023-05-06_final
2023-05-08 11:00:20	ga_ls8c_ard_3-2-1_107073_2023-05-08_final
2023-05-11 09:54:41	ga_ls8c_ard_3-2-1_096079_2023-05-11_final
2023-05-21 10:31:45	ga_ls8c_ard_3-2-1_102079_2023-05-21_final
2023-05-22 09:34:32	ga_ls8c_ard_3-2-1_093075_2023-05-22_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