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
2022-08-21 11:27:49	ga_ls8c_ard_3-2-1_111077_2022-08-21_final
2022-09-12 10:50:49	ga_ls8c_ard_3-2-1_105077_2022-09-12_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
2022-09-13 09:54:48	ga_ls8c_ard_3-2-1_096076_2022-09-13_final
2022-09-13 09:55:12	ga_ls8c_ard_3-2-1_096077_2022-09-13_final
2022-09-13 09:55:36	ga_ls8c_ard_3-2-1_096078_2022-09-13_final
2022-09-13 09:56:24	ga_ls8c_ard_3-2-1_096080_2022-09-13_final
2022-09-13 11:33:41	ga_ls8c_ard_3-2-1_112076_2022-09-13_final
2022-09-15 09:44:27	ga_ls8c_ard_3-2-1_094081_2022-09-15_final
2022-09-15 11:22:08	ga_ls8c_ard_3-2-1_110078_2022-09-15_final
2022-09-16 10:27:19	ga_ls8c_ard_3-2-1_101080_2022-09-16_final
2022-09-20 10:00:36	ga_ls8c_ard_3-2-1_097075_2022-09-20_final
2022-09-20 10:03:24	ga_ls8c_ard_3-2-1_097082_2022-09-20_final
2022-09-21 10:45:04	ga_ls8c_ard_3-2-1_104078_2022-09-21_final
2022-09-28 10:50:51	ga_ls8c_ard_3-2-1_105077_2022-09-28_final
2022-09-28 10:51:39	ga_ls8c_ard_3-2-1_105079_2022-09-28_final
2022-09-29 09:54:49	ga_ls8c_ard_3-2-1_096076_2022-09-29_final
2022-09-29 09:55:13	ga_ls8c_ard_3-2-1_096077_2022-09-29_final
2022-09-29 09:55:37	ga_ls8c_ard_3-2-1_096078_2022-09-29_final
2022-09-30 10:37:17	ga_ls8c_ard_3-2-1_103074_2022-09-30_final
2022-09-30 10:37:41	ga_ls8c_ard_3-2-1_103075_2022-09-30_final
2022-10-02 10:23:19	ga_ls8c_ard_3-2-1_101070_2022-10-02_final
2022-10-03 09:32:05	ga_ls8c_ard_3-2-1_092081_2022-10-03_final
2022-10-05 10:56:59	ga_ls8c_ard_3-2-1_106077_2022-10-05_final
2022-10-07 10:45:24	ga_ls8c_ard_3-2-1_104079_2022-10-07_final
2022-10-10 11:16:40	ga_ls8c_ard_3-2-1_109080_2022-10-10_final
2022-10-12 11:05:04	ga_ls8c_ard_3-2-1_107082_2022-10-12_final
2022-10-14 10:51:29	ga_ls8c_ard_3-2-1_105079_2022-10-14_final
2022-10-15 11:35:10	ga_ls8c_ard_3-2-1_112080_2022-10-15_final
2022-10-16 10:40:21	ga_ls8c_ard_3-2-1_103082_2022-10-16_final
2022-10-17 09:43:09	ga_ls8c_ard_3-2-1_094078_2022-10-17_final
2022-10-17 11:22:02	ga_ls8c_ard_3-2-1_110078_2022-10-17_final
2022-10-30 10:51:38	ga_ls8c_ard_3-2-1_105079_2022-10-30_final
2022-10-31 09:54:25	ga_ls8c_ard_3-2-1_096075_2022-10-31_final
2022-10-31 11:35:18	ga_ls8c_ard_3-2-1_112080_2022-10-31_final
2022-11-02 11:22:09	ga_ls8c_ard_3-2-1_110078_2022-11-02_final
2022-11-03 10:27:19	ga_ls8c_ard_3-2-1_101080_2022-11-03_final
2022-11-04 09:35:17	ga_ls8c_ard_3-2-1_092089_2022-11-04_final
2022-11-09 09:49:49	ga_ls8c_ard_3-2-1_095079_2022-11-09_final
2022-11-09 09:50:13	ga_ls8c_ard_3-2-1_095080_2022-11-09_final
2022-11-10 10:31:28	ga_ls8c_ard_3-2-1_102075_2022-11-10_final
2022-11-10 10:33:28	ga_ls8c_ard_3-2-1_102080_2022-11-10_final
2022-11-11 11:16:43	ga_ls8c_ard_3-2-1_109080_2022-11-11_final
2022-11-15 10:51:57	ga_ls8c_ard_3-2-1_105080_2022-11-15_final
2022-11-25 09:50:09	ga_ls8c_ard_3-2-1_095080_2022-11-25_final
2022-11-25 11:28:38	ga_ls8c_ard_3-2-1_111079_2022-11-25_final
2022-11-26 10:33:25	ga_ls8c_ard_3-2-1_102080_2022-11-26_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
2022-12-04 09:43:11	ga_ls8c_ard_3-2-1_094078_2022-12-04_final
2022-12-04 11:22:04	ga_ls8c_ard_3-2-1_110078_2022-12-04_final
2022-12-06 11:09:42	ga_ls8c_ard_3-2-1_108078_2022-12-06_final
2022-12-11 09:49:43	ga_ls8c_ard_3-2-1_095079_2022-12-11_final
2022-12-11 09:50:07	ga_ls8c_ard_3-2-1_095080_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 09:54:14	ga_ls8c_ard_3-2-1_096075_2022-12-18_final
2022-12-18 09:55:49	ga_ls8c_ard_3-2-1_096079_2022-12-18_final
2022-12-20 09:44:14	ga_ls8c_ard_3-2-1_094081_2022-12-20_final
2022-12-21 10:27:05	ga_ls8c_ard_3-2-1_101080_2022-12-21_final
2022-12-22 11:09:07	ga_ls8c_ard_3-2-1_108077_2022-12-22_final
2022-12-22 11:09:31	ga_ls8c_ard_3-2-1_108078_2022-12-22_final
2022-12-29 11:16:32	ga_ls8c_ard_3-2-1_109080_2022-12-29_final
2022-12-31 11:02:11	ga_ls8c_ard_3-2-1_107075_2022-12-31_final
2023-01-03 09:55:00	ga_ls8c_ard_3-2-1_096077_2023-01-03_final
2023-01-03 09:55:24	ga_ls8c_ard_3-2-1_096078_2023-01-03_final
2023-01-03 09:56:12	ga_ls8c_ard_3-2-1_096080_2023-01-03_final
2023-01-05 09:46:37	ga_ls8c_ard_3-2-1_094087_2023-01-05_final
2023-01-05 11:21:55	ga_ls8c_ard_3-2-1_110078_2023-01-05_final
2023-01-07 09:35:27	ga_ls8c_ard_3-2-1_092090_2023-01-07_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
2023-01-14 11:16:27	ga_ls8c_ard_3-2-1_109080_2023-01-14_final
2023-01-15 10:20:49	ga_ls8c_ard_3-2-1_100080_2023-01-15_final
2023-01-19 09:54:04	ga_ls8c_ard_3-2-1_096075_2023-01-19_final
2023-01-30 11:16:30	ga_ls8c_ard_3-2-1_109080_2023-01-30_final
2023-02-06 11:21:52	ga_ls8c_ard_3-2-1_110078_2023-02-06_final
2023-02-08 11:09:30	ga_ls8c_ard_3-2-1_108078_2023-02-08_final
2023-02-13 09:49:29	ga_ls8c_ard_3-2-1_095079_2023-02-13_final
2023-02-13 11:28:22	ga_ls8c_ard_3-2-1_111079_2023-02-13_final
2023-02-15 09:38:18	ga_ls8c_ard_3-2-1_093082_2023-02-15_final
2023-02-15 11:16:23	ga_ls8c_ard_3-2-1_109080_2023-02-15_final
2023-02-15 11:17:35	ga_ls8c_ard_3-2-1_109083_2023-02-15_final
2023-02-16 10:20:45	ga_ls8c_ard_3-2-1_100080_2023-02-16_final
2023-02-16 10:21:09	ga_ls8c_ard_3-2-1_100081_2023-02-16_final
2023-02-17 11:03:12	ga_ls8c_ard_3-2-1_107078_2023-02-17_final
2023-02-20 09:55:09	ga_ls8c_ard_3-2-1_096078_2023-02-20_final
2023-02-20 09:55:33	ga_ls8c_ard_3-2-1_096079_2023-02-20_final
2023-02-20 09:55:57	ga_ls8c_ard_3-2-1_096080_2023-02-20_final
2023-02-20 09:56:45	ga_ls8c_ard_3-2-1_096082_2023-02-20_final
2023-02-22 09:42:45	ga_ls8c_ard_3-2-1_094078_2023-02-22_final
2023-03-01 09:49:39	ga_ls8c_ard_3-2-1_095080_2023-03-01_final
2023-03-02 10:32:54	ga_ls8c_ard_3-2-1_102080_2023-03-02_final
2023-03-03 09:37:17	ga_ls8c_ard_3-2-1_093080_2023-03-03_final
2023-03-03 11:16:10	ga_ls8c_ard_3-2-1_109080_2023-03-03_final
2023-03-08 09:55:22	ga_ls8c_ard_3-2-1_096079_2023-03-08_final
2023-03-08 09:56:33	ga_ls8c_ard_3-2-1_096082_2023-03-08_final
2023-03-08 11:33:03	ga_ls8c_ard_3-2-1_112076_2023-03-08_final
2023-03-08 11:34:15	ga_ls8c_ard_3-2-1_112079_2023-03-08_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