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
2022-11-15 10:51:09	ga_ls8c_ard_3-2-1_105078_2022-11-15_final
2022-11-25 09:49:45	ga_ls8c_ard_3-2-1_095079_2022-11-25_final
2022-12-01 10:51:10	ga_ls8c_ard_3-2-1_105078_2022-12-01_final
2022-12-04 11:22:04	ga_ls8c_ard_3-2-1_110078_2022-12-04_final
2022-12-15 11:03:27	ga_ls8c_ard_3-2-1_107078_2022-12-15_final
2022-12-18 09:54:38	ga_ls8c_ard_3-2-1_096076_2022-12-18_final
2022-12-18 09:55:25	ga_ls8c_ard_3-2-1_096078_2022-12-18_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
2022-12-30 10:20:31	ga_ls8c_ard_3-2-1_100079_2022-12-30_final
2023-01-05 11:22:19	ga_ls8c_ard_3-2-1_110079_2023-01-05_final
2023-01-11 10:45:59	ga_ls8c_ard_3-2-1_104081_2023-01-11_final
2023-01-12 09:50:21	ga_ls8c_ard_3-2-1_095081_2023-01-12_final
2023-01-12 11:28:26	ga_ls8c_ard_3-2-1_111079_2023-01-12_final
2023-01-20 10:38:33	ga_ls8c_ard_3-2-1_103078_2023-01-20_final
2023-01-21 11:21:49	ga_ls8c_ard_3-2-1_110078_2023-01-21_final
2023-02-04 11:34:38	ga_ls8c_ard_3-2-1_112079_2023-02-04_final
2023-02-06 11:22:16	ga_ls8c_ard_3-2-1_110079_2023-02-06_final
2023-02-13 11:27:10	ga_ls8c_ard_3-2-1_111076_2023-02-13_final
2023-02-13 11:28:22	ga_ls8c_ard_3-2-1_111079_2023-02-13_final
2023-02-17 11:03:12	ga_ls8c_ard_3-2-1_107078_2023-02-17_final
2023-02-19 10:50:48	ga_ls8c_ard_3-2-1_105078_2023-02-19_final
2023-02-20 09:53:57	ga_ls8c_ard_3-2-1_096075_2023-02-20_final
2023-02-20 09:55:57	ga_ls8c_ard_3-2-1_096080_2023-02-20_final
2023-02-20 11:32:02	ga_ls8c_ard_3-2-1_112073_2023-02-20_final
2023-02-22 09:42:45	ga_ls8c_ard_3-2-1_094078_2023-02-22_final
2023-02-24 11:09:13	ga_ls8c_ard_3-2-1_108078_2023-02-24_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
2023-03-11 10:22:40	ga_ls8c_ard_3-2-1_101070_2023-03-11_final
2023-03-16 10:45:34	ga_ls8c_ard_3-2-1_104081_2023-03-16_final
2023-03-17 11:27:13	ga_ls8c_ard_3-2-1_111077_2023-03-17_final
2023-03-17 11:27:37	ga_ls8c_ard_3-2-1_111078_2023-03-17_final
2023-03-23 10:50:27	ga_ls8c_ard_3-2-1_105078_2023-03-23_final
2023-03-24 09:54:49	ga_ls8c_ard_3-2-1_096078_2023-03-24_final
2023-03-24 09:55:37	ga_ls8c_ard_3-2-1_096080_2023-03-24_final
2023-03-26 09:42:27	ga_ls8c_ard_3-2-1_094078_2023-03-26_final
2023-04-09 09:54:11	ga_ls8c_ard_3-2-1_096077_2023-04-09_final
2023-04-09 11:34:16	ga_ls8c_ard_3-2-1_112080_2023-04-09_final
2023-04-11 11:21:28	ga_ls8c_ard_3-2-1_110079_2023-04-11_final
2023-04-18 11:28:00	ga_ls8c_ard_3-2-1_111080_2023-04-18_final
2023-04-20 11:15:37	ga_ls8c_ard_3-2-1_109080_2023-04-20_final
2023-04-25 09:54:06	ga_ls8c_ard_3-2-1_096077_2023-04-25_final
2023-04-25 09:54:30	ga_ls8c_ard_3-2-1_096078_2023-04-25_final
2023-04-25 09:55:17	ga_ls8c_ard_3-2-1_096080_2023-04-25_final
2023-04-25 11:33:47	ga_ls8c_ard_3-2-1_112079_2023-04-25_final
2023-04-27 09:42:07	ga_ls8c_ard_3-2-1_094078_2023-04-27_final
2023-04-27 11:21:00	ga_ls8c_ard_3-2-1_110078_2023-04-27_final
2023-04-27 11:21:24	ga_ls8c_ard_3-2-1_110079_2023-04-27_final
2023-05-06 09:36:15	ga_ls8c_ard_3-2-1_093079_2023-05-06_final
2023-05-06 11:15:08	ga_ls8c_ard_3-2-1_109079_2023-05-06_final
2023-05-11 09:53:54	ga_ls8c_ard_3-2-1_096077_2023-05-11_final
2023-05-11 09:54:18	ga_ls8c_ard_3-2-1_096078_2023-05-11_final
2023-05-11 11:33:58	ga_ls8c_ard_3-2-1_112080_2023-05-11_final
2023-05-13 09:41:54	ga_ls8c_ard_3-2-1_094078_2023-05-13_final
2023-05-13 11:20:48	ga_ls8c_ard_3-2-1_110078_2023-05-13_final
2023-05-20 09:48:52	ga_ls8c_ard_3-2-1_095080_2023-05-20_final
2023-05-22 09:36:08	ga_ls8c_ard_3-2-1_093079_2023-05-22_final
2023-05-22 11:15:01	ga_ls8c_ard_3-2-1_109079_2023-05-22_final
2023-05-22 11:15:25	ga_ls8c_ard_3-2-1_109080_2023-05-22_final
2023-05-24 11:02:16	ga_ls8c_ard_3-2-1_107078_2023-05-24_final
2023-05-27 09:54:17	ga_ls8c_ard_3-2-1_096078_2023-05-27_final
2023-05-27 09:55:05	ga_ls8c_ard_3-2-1_096080_2023-05-27_final
2023-05-27 11:32:22	ga_ls8c_ard_3-2-1_112076_2023-05-27_final
2023-05-29 11:20:49	ga_ls8c_ard_3-2-1_110078_2023-05-29_final
2023-06-01 11:50:07	ga_ls8c_ard_3-2-1_115074_2023-06-01_final
2023-06-05 09:47:45	ga_ls8c_ard_3-2-1_095077_2023-06-05_final
2023-06-05 11:27:02	ga_ls8c_ard_3-2-1_111078_2023-06-05_final
2023-06-09 11:02:22	ga_ls8c_ard_3-2-1_107078_2023-06-09_final
2023-06-14 11:20:57	ga_ls8c_ard_3-2-1_110078_2023-06-14_final
2023-06-21 11:27:33	ga_ls8c_ard_3-2-1_111079_2023-06-21_final
2023-06-23 11:15:11	ga_ls8c_ard_3-2-1_109079_2023-06-23_final
2023-06-25 11:02:28	ga_ls8c_ard_3-2-1_107078_2023-06-25_final
2023-06-28 09:54:08	ga_ls8c_ard_3-2-1_096077_2023-06-28_final
2023-06-30 09:42:13	ga_ls8c_ard_3-2-1_094078_2023-06-30_final
2023-07-03 11:50:26	ga_ls8c_ard_3-2-1_115074_2023-07-03_final
2023-07-09 11:15:00	ga_ls8c_ard_3-2-1_109078_2023-07-09_final
2023-07-14 09:53:53	ga_ls8c_ard_3-2-1_096076_2023-07-14_final
2023-07-14 09:54:41	ga_ls8c_ard_3-2-1_096078_2023-07-14_final
2023-07-18 11:09:15	ga_ls8c_ard_3-2-1_108079_2023-07-18_final
2023-07-19 10:16:01	ga_ls8c_ard_3-2-1_099085_2023-07-19_final
2023-07-24 10:31:49	ga_ls8c_ard_3-2-1_102078_2023-07-24_final
2023-07-24 10:33:24	ga_ls8c_ard_3-2-1_102082_2023-07-24_final
2023-07-25 11:15:05	ga_ls8c_ard_3-2-1_109078_2023-07-25_final
2023-07-27 11:02:45	ga_ls8c_ard_3-2-1_107078_2023-07-27_final
2023-07-29 10:50:01	ga_ls8c_ard_3-2-1_105077_2023-07-29_final
2023-07-30 09:54:00	ga_ls8c_ard_3-2-1_096076_2023-07-30_final
2023-07-30 09:54:24	ga_ls8c_ard_3-2-1_096077_2023-07-30_final
2023-07-30 09:54:48	ga_ls8c_ard_3-2-1_096078_2023-07-30_final
2023-07-30 11:32:53	ga_ls8c_ard_3-2-1_112076_2023-07-30_final
2023-07-30 11:34:29	ga_ls8c_ard_3-2-1_112080_2023-07-30_final
2023-08-01 11:20:57	ga_ls8c_ard_3-2-1_110077_2023-08-01_final
2023-08-10 09:36:41	ga_ls8c_ard_3-2-1_093079_2023-08-10_final
2023-08-10 11:15:10	ga_ls8c_ard_3-2-1_109078_2023-08-10_final
2023-08-12 11:02:50	ga_ls8c_ard_3-2-1_107078_2023-08-12_final
2023-08-15 09:54:06	ga_ls8c_ard_3-2-1_096076_2023-08-15_final
2023-08-15 09:54:30	ga_ls8c_ard_3-2-1_096077_2023-08-15_final
2023-09-07 10:03:55	ga_ls8c_ard_3-2-1_097085_2023-09-07_final
2023-09-09 09:49:11	ga_ls8c_ard_3-2-1_095079_2023-09-09_final
2023-09-11 09:36:51	ga_ls8c_ard_3-2-1_093079_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