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
2022-07-25 10:06:05	ga_ls8c_ard_3-2-1_098074_2022-07-25_final
2022-07-26 10:51:45	ga_ls8c_ard_3-2-1_105080_2022-07-26_final
2022-07-29 09:42:13	ga_ls8c_ard_3-2-1_094076_2022-07-29_final
2022-08-09 11:05:03	ga_ls8c_ard_3-2-1_107082_2022-08-09_final
2022-08-12 11:33:34	ga_ls8c_ard_3-2-1_112076_2022-08-12_final
2022-08-21 09:50:08	ga_ls8c_ard_3-2-1_095080_2022-08-21_final
2022-08-24 11:58:43	ga_ls8c_ard_3-2-1_116077_2022-08-24_final
2022-08-28 09:57:07	ga_ls8c_ard_3-2-1_096082_2022-08-28_final
2022-08-29 10:39:34	ga_ls8c_ard_3-2-1_103080_2022-08-29_final
2022-09-03 10:57:42	ga_ls8c_ard_3-2-1_106079_2022-09-03_final
2022-09-04 10:03:41	ga_ls8c_ard_3-2-1_097083_2022-09-04_final
2022-09-05 10:42:34	ga_ls8c_ard_3-2-1_104072_2022-09-05_final
2022-09-12 10:51:13	ga_ls8c_ard_3-2-1_105078_2022-09-12_final
2022-09-13 09:54:24	ga_ls8c_ard_3-2-1_096075_2022-09-13_final
2022-09-21 10:44:40	ga_ls8c_ard_3-2-1_104077_2022-09-21_final
2022-09-26 11:03:37	ga_ls8c_ard_3-2-1_107078_2022-09-26_final
2022-09-30 10:37:17	ga_ls8c_ard_3-2-1_103074_2022-09-30_final
2022-10-01 09:42:03	ga_ls8c_ard_3-2-1_094075_2022-10-01_final
2022-10-08 11:28:15	ga_ls8c_ard_3-2-1_111078_2022-10-08_final
2022-10-15 09:54:17	ga_ls8c_ard_3-2-1_096075_2022-10-15_final
2022-10-18 10:25:38	ga_ls8c_ard_3-2-1_101076_2022-10-18_final
2022-10-24 09:49:00	ga_ls8c_ard_3-2-1_095077_2022-10-24_final
2022-10-24 11:28:41	ga_ls8c_ard_3-2-1_111079_2022-10-24_final
2022-10-26 09:38:39	ga_ls8c_ard_3-2-1_093082_2022-10-26_final
2022-11-07 11:40:40	ga_ls8c_ard_3-2-1_113078_2022-11-07_final
2022-11-07 11:41:04	ga_ls8c_ard_3-2-1_113079_2022-11-07_final
2022-11-09 09:49:01	ga_ls8c_ard_3-2-1_095077_2022-11-09_final
2022-11-12 11:58:46	ga_ls8c_ard_3-2-1_116077_2022-11-12_final
2022-11-18 11:22:01	ga_ls8c_ard_3-2-1_110078_2022-11-18_final
2022-11-25 09:48:33	ga_ls8c_ard_3-2-1_095076_2022-11-25_final
2022-11-26 10:33:25	ga_ls8c_ard_3-2-1_102080_2022-11-26_final
2022-11-28 10:19:04	ga_ls8c_ard_3-2-1_100075_2022-11-28_final
2022-12-01 10:53:09	ga_ls8c_ard_3-2-1_105083_2022-12-01_final
2022-12-02 09:54:21	ga_ls8c_ard_3-2-1_096075_2022-12-02_final
2022-12-03 10:39:12	ga_ls8c_ard_3-2-1_103079_2022-12-03_final
2022-12-10 10:42:10	ga_ls8c_ard_3-2-1_104071_2022-12-10_final
2022-12-10 10:42:34	ga_ls8c_ard_3-2-1_104072_2022-12-10_final
2022-12-11 09:48:55	ga_ls8c_ard_3-2-1_095077_2022-12-11_final
2022-12-11 09:50:07	ga_ls8c_ard_3-2-1_095080_2022-12-11_final
2022-12-11 11:28:36	ga_ls8c_ard_3-2-1_111079_2022-12-11_final
2022-12-12 10:33:22	ga_ls8c_ard_3-2-1_102080_2022-12-12_final
2022-12-13 09:38:32	ga_ls8c_ard_3-2-1_093082_2022-12-13_final
2022-12-18 09:55:25	ga_ls8c_ard_3-2-1_096078_2022-12-18_final
2022-12-19 10:37:28	ga_ls8c_ard_3-2-1_103075_2022-12-19_final
2022-12-25 11:40:50	ga_ls8c_ard_3-2-1_113079_2022-12-25_final
2022-12-27 09:48:24	ga_ls8c_ard_3-2-1_095076_2022-12-27_final
2022-12-30 11:58:36	ga_ls8c_ard_3-2-1_116077_2022-12-30_final
2023-01-03 09:56:12	ga_ls8c_ard_3-2-1_096080_2023-01-03_final
2023-01-03 09:56:59	ga_ls8c_ard_3-2-1_096082_2023-01-03_final
2023-01-05 11:21:55	ga_ls8c_ard_3-2-1_110078_2023-01-05_final
2023-01-06 10:23:06	ga_ls8c_ard_3-2-1_101070_2023-01-06_final
2023-01-12 09:49:33	ga_ls8c_ard_3-2-1_095079_2023-01-12_final
2023-01-12 11:28:26	ga_ls8c_ard_3-2-1_111079_2023-01-12_final
2023-01-19 09:54:28	ga_ls8c_ard_3-2-1_096076_2023-01-19_final
2023-01-20 10:37:21	ga_ls8c_ard_3-2-1_103075_2023-01-20_final
2023-01-26 10:02:43	ga_ls8c_ard_3-2-1_097081_2023-01-26_final
2023-01-31 11:58:58	ga_ls8c_ard_3-2-1_116078_2023-01-31_final
2023-02-11 10:03:04	ga_ls8c_ard_3-2-1_097082_2023-02-11_final
2023-02-13 09:48:41	ga_ls8c_ard_3-2-1_095077_2023-02-13_final
2023-02-14 10:32:20	ga_ls8c_ard_3-2-1_102078_2023-02-14_final
2023-02-19 10:51:12	ga_ls8c_ard_3-2-1_105079_2023-02-19_final
2023-02-20 09:54:21	ga_ls8c_ard_3-2-1_096076_2023-02-20_final
2023-02-22 09:44:44	ga_ls8c_ard_3-2-1_094083_2023-02-22_final
2023-02-22 11:21:38	ga_ls8c_ard_3-2-1_110078_2023-02-22_final
2023-03-06 10:08:33	ga_ls8c_ard_3-2-1_098081_2023-03-06_final
2023-03-06 10:08:57	ga_ls8c_ard_3-2-1_098082_2023-03-06_final
2023-03-08 09:55:45	ga_ls8c_ard_3-2-1_096080_2023-03-08_final
2023-03-08 09:56:09	ga_ls8c_ard_3-2-1_096081_2023-03-08_final
2023-03-08 11:34:15	ga_ls8c_ard_3-2-1_112079_2023-03-08_final
2023-03-08 11:34:38	ga_ls8c_ard_3-2-1_112080_2023-03-08_final
2023-03-10 11:21:53	ga_ls8c_ard_3-2-1_110079_2023-03-10_final
2023-03-12 09:30:14	ga_ls8c_ard_3-2-1_092078_2023-03-12_final
2023-03-15 10:03:07	ga_ls8c_ard_3-2-1_097083_2023-03-15_final
2023-03-16 10:43:34	ga_ls8c_ard_3-2-1_104076_2023-03-16_final
2023-03-16 10:45:34	ga_ls8c_ard_3-2-1_104081_2023-03-16_final
2023-03-17 11:27:37	ga_ls8c_ard_3-2-1_111078_2023-03-17_final
2023-03-24 09:54:25	ga_ls8c_ard_3-2-1_096077_2023-03-24_final
2023-03-24 09:55:37	ga_ls8c_ard_3-2-1_096080_2023-03-24_final
2023-03-26 09:42:03	ga_ls8c_ard_3-2-1_094077_2023-03-26_final
2023-04-02 11:27:50	ga_ls8c_ard_3-2-1_111079_2023-04-02_final
2023-04-04 09:36:34	ga_ls8c_ard_3-2-1_093079_2023-04-04_final
2023-04-11 11:21:52	ga_ls8c_ard_3-2-1_110080_2023-04-11_final
2023-04-15 09:19:27	ga_ls8c_ard_3-2-1_090083_2023-04-14_final
2023-04-20 09:36:20	ga_ls8c_ard_3-2-1_093079_2023-04-20_final
2023-04-24 10:49:43	ga_ls8c_ard_3-2-1_105077_2023-04-24_final
2023-04-24 10:50:55	ga_ls8c_ard_3-2-1_105080_2023-04-24_final
2023-04-25 09:54:54	ga_ls8c_ard_3-2-1_096079_2023-04-25_final
2023-04-25 09:55:17	ga_ls8c_ard_3-2-1_096080_2023-04-25_final
2023-04-27 11:21:48	ga_ls8c_ard_3-2-1_110080_2023-04-27_final
2023-04-29 09:29:45	ga_ls8c_ard_3-2-1_092078_2023-04-28_final
2023-04-30 10:15:48	ga_ls8c_ard_3-2-1_099085_2023-04-30_final
2023-05-03 10:45:04	ga_ls8c_ard_3-2-1_104081_2023-05-03_final
2023-05-04 09:49:26	ga_ls8c_ard_3-2-1_095081_2023-05-04_final
2023-05-08 09:23:27	ga_ls8c_ard_3-2-1_091078_2023-05-07_final
2023-05-09 10:08:18	ga_ls8c_ard_3-2-1_098082_2023-05-09_final
2023-05-11 11:31:11	ga_ls8c_ard_3-2-1_112073_2023-05-11_final
2023-05-13 09:41:54	ga_ls8c_ard_3-2-1_094078_2023-05-13_final
2023-05-17 10:58:02	ga_ls8c_ard_3-2-1_106083_2023-05-17_final
2023-05-19 10:43:41	ga_ls8c_ard_3-2-1_104078_2023-05-19_final
2023-05-20 09:48:52	ga_ls8c_ard_3-2-1_095080_2023-05-20_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