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
2021-08-29 11:09:21	ga_ls8c_ard_3-2-0_108078_2021-08-29_final
2021-09-01 10:02:59	ga_ls8c_ard_3-2-0_097082_2021-09-01_final
2021-09-17 10:00:39	ga_ls8c_ard_3-2-0_097076_2021-09-17_final
2021-09-17 11:39:32	ga_ls8c_ard_3-2-0_113076_2021-09-17_final
2021-09-18 10:45:07	ga_ls8c_ard_3-2-0_104079_2021-09-18_final
2021-09-26 11:33:23	ga_ls8c_ard_3-2-0_112076_2021-09-26_final
2021-09-28 09:42:57	ga_ls8c_ard_3-2-0_094078_2021-09-28_final
2021-09-30 11:09:05	ga_ls8c_ard_3-2-0_108077_2021-09-30_final
2021-10-03 10:00:20	ga_ls8c_ard_3-2-0_097075_2021-10-03_final
2021-10-04 10:45:12	ga_ls8c_ard_3-2-0_104079_2021-10-04_final
2021-10-05 09:49:11	ga_ls8c_ard_3-2-0_095078_2021-10-05_final
2021-10-11 10:51:00	ga_ls8c_ard_3-2-0_105078_2021-10-11_final
2021-10-12 11:33:53	ga_ls8c_ard_3-2-0_112077_2021-10-12_final
2021-10-21 09:49:14	ga_ls8c_ard_3-2-0_095078_2021-10-21_final
2021-10-24 11:58:37	ga_ls8c_ard_3-2-0_116077_2021-10-24_final
2021-10-27 10:51:02	ga_ls8c_ard_3-2-0_105078_2021-10-27_final
2021-12-19 11:09:04	ga_ls8c_ard_3-2-1_108077_2021-12-19_final
2021-12-28 11:05:13	ga_ls8c_ard_3-2-1_107083_2021-12-28_final
2022-02-09 10:45:44	ga_ls8c_ard_3-2-1_104081_2022-02-09_final
2022-02-21 11:09:10	ga_ls8c_ard_3-2-1_108078_2022-02-21_final
2022-03-09 11:08:44	ga_ls8c_ard_3-2-1_108077_2022-03-09_final
2022-04-01 09:37:46	ga_ls8c_ard_3-2-1_093082_2022-04-01_final
2022-04-03 11:02:42	ga_ls8c_ard_3-2-1_107078_2022-04-03_final
2022-04-06 09:53:57	ga_ls8c_ard_3-2-1_096076_2022-04-06_final
2022-04-06 11:32:50	ga_ls8c_ard_3-2-1_112076_2022-04-06_final
2022-04-06 11:33:14	ga_ls8c_ard_3-2-1_112077_2022-04-06_final
2022-04-13 09:59:48	ga_ls8c_ard_3-2-1_097075_2022-04-13_final
2022-04-15 09:49:26	ga_ls8c_ard_3-2-1_095080_2022-04-15_final
2022-04-15 11:27:55	ga_ls8c_ard_3-2-1_111079_2022-04-15_final
2022-04-24 11:21:18	ga_ls8c_ard_3-2-1_110078_2022-04-24_final
2022-05-08 11:34:08	ga_ls8c_ard_3-2-1_112079_2022-05-08_final
2022-05-17 09:48:44	ga_ls8c_ard_3-2-1_095078_2022-05-17_final
2022-05-22 10:08:53	ga_ls8c_ard_3-2-1_098082_2022-05-22_final
2022-05-26 09:42:57	ga_ls8c_ard_3-2-1_094079_2022-05-26_final
2022-06-08 10:50:18	ga_ls8c_ard_3-2-1_105077_2022-06-08_final
2022-06-18 09:48:36	ga_ls8c_ard_3-2-1_095077_2022-06-18_final
2022-06-24 10:50:26	ga_ls8c_ard_3-2-1_105077_2022-06-24_final
2022-06-26 10:39:16	ga_ls8c_ard_3-2-1_103080_2022-06-26_final
2022-06-27 11:22:08	ga_ls8c_ard_3-2-1_110079_2022-06-27_final
2022-07-04 09:49:26	ga_ls8c_ard_3-2-1_095079_2022-07-04_final
2022-07-10 10:50:26	ga_ls8c_ard_3-2-1_105077_2022-07-10_final
2022-07-11 11:34:30	ga_ls8c_ard_3-2-1_112079_2022-07-11_final
2022-07-13 11:21:44	ga_ls8c_ard_3-2-1_110078_2022-07-13_final
2022-07-13 11:22:08	ga_ls8c_ard_3-2-1_110079_2022-07-13_final
2022-07-15 11:08:57	ga_ls8c_ard_3-2-1_108077_2022-07-15_final
2022-07-27 11:33:26	ga_ls8c_ard_3-2-1_112076_2022-07-27_final
2022-07-27 11:34:38	ga_ls8c_ard_3-2-1_112079_2022-07-27_final
2022-07-28 10:39:25	ga_ls8c_ard_3-2-1_103080_2022-07-28_final
2022-08-05 11:28:08	ga_ls8c_ard_3-2-1_111078_2022-08-05_final
2022-08-07 11:15:48	ga_ls8c_ard_3-2-1_109078_2022-08-07_final
2022-08-12 11:35:10	ga_ls8c_ard_3-2-1_112080_2022-08-12_final
2022-08-14 11:22:25	ga_ls8c_ard_3-2-1_110079_2022-08-14_final
2022-08-19 10:00:30	ga_ls8c_ard_3-2-1_097075_2022-08-19_final
2022-08-21 09:48:56	ga_ls8c_ard_3-2-1_095077_2022-08-21_final
2022-08-21 11:28:13	ga_ls8c_ard_3-2-1_111078_2022-08-21_final
2022-08-23 11:18:15	ga_ls8c_ard_3-2-1_109084_2022-08-23_final
2022-08-25 11:03:30	ga_ls8c_ard_3-2-1_107078_2022-08-25_final
2022-08-27 10:50:44	ga_ls8c_ard_3-2-1_105077_2022-08-27_final
2022-08-28 11:33:36	ga_ls8c_ard_3-2-1_112076_2022-08-28_final
2022-08-28 11:34:00	ga_ls8c_ard_3-2-1_112077_2022-08-28_final
2022-09-05 10:44:58	ga_ls8c_ard_3-2-1_104078_2022-09-05_final
2022-09-06 09:49:21	ga_ls8c_ard_3-2-1_095078_2022-09-06_final
2022-09-21 10:45:28	ga_ls8c_ard_3-2-1_104079_2022-09-21_final
2022-09-22 09:49:27	ga_ls8c_ard_3-2-1_095078_2022-09-22_final
2022-09-22 11:28:44	ga_ls8c_ard_3-2-1_111079_2022-09-22_final
2022-09-23 10:33:30	ga_ls8c_ard_3-2-1_102080_2022-09-23_final
2022-10-09 10:33:25	ga_ls8c_ard_3-2-1_102080_2022-10-09_final
2022-10-14 10:51:06	ga_ls8c_ard_3-2-1_105078_2022-10-14_final
2022-10-28 11:03:12	ga_ls8c_ard_3-2-1_107077_2022-10-28_final
2022-11-04 11:09:47	ga_ls8c_ard_3-2-1_108078_2022-11-04_final
2022-11-08 10:46:14	ga_ls8c_ard_3-2-1_104081_2022-11-08_final
2022-11-15 10:51:09	ga_ls8c_ard_3-2-1_105078_2022-11-15_final
2022-11-24 10:46:10	ga_ls8c_ard_3-2-1_104081_2022-11-24_final
2022-11-25 09:49:21	ga_ls8c_ard_3-2-1_095078_2022-11-25_final
2022-11-25 09:49:45	ga_ls8c_ard_3-2-1_095079_2022-11-25_final
2022-12-06 11:09:42	ga_ls8c_ard_3-2-1_108078_2022-12-06_final
2022-12-21 10:27:05	ga_ls8c_ard_3-2-1_101080_2022-12-21_final
2022-12-22 11:09:31	ga_ls8c_ard_3-2-1_108078_2022-12-22_final
2023-01-02 10:51:01	ga_ls8c_ard_3-2-1_105078_2023-01-02_final
2023-01-07 11:09:33	ga_ls8c_ard_3-2-1_108078_2023-01-07_final
2023-01-09 10:58:46	ga_ls8c_ard_3-2-1_106082_2023-01-09_final
2023-01-11 10:45:59	ga_ls8c_ard_3-2-1_104081_2023-01-11_final
2023-01-23 11:09:29	ga_ls8c_ard_3-2-1_108078_2023-01-23_final
2023-02-08 11:09:30	ga_ls8c_ard_3-2-1_108078_2023-02-08_final
2023-02-19 10:50:48	ga_ls8c_ard_3-2-1_105078_2023-02-19_final
2023-03-01 09:48:51	ga_ls8c_ard_3-2-1_095078_2023-03-01_final
2023-03-08 11:33:27	ga_ls8c_ard_3-2-1_112077_2023-03-08_final
2023-03-21 11:04:26	ga_ls8c_ard_3-2-1_107082_2023-03-21_final
2023-04-02 09:48:57	ga_ls8c_ard_3-2-1_095079_2023-04-02_final
2023-04-02 11:27:50	ga_ls8c_ard_3-2-1_111079_2023-04-02_final
2023-04-04 09:37:45	ga_ls8c_ard_3-2-1_093082_2023-04-04_final
2023-04-17 10:43:57	ga_ls8c_ard_3-2-1_104078_2023-04-17_final
2023-04-18 09:47:55	ga_ls8c_ard_3-2-1_095077_2023-04-18_final
2023-04-25 09:54:06	ga_ls8c_ard_3-2-1_096077_2023-04-25_final
2023-04-25 11:33:47	ga_ls8c_ard_3-2-1_112079_2023-04-25_final
2023-05-08 11:02:20	ga_ls8c_ard_3-2-1_107078_2023-05-08_final
2023-05-11 09:53:30	ga_ls8c_ard_3-2-1_096076_2023-05-11_final
2023-05-11 11:32:47	ga_ls8c_ard_3-2-1_112077_2023-05-11_final
2023-05-11 11:33:58	ga_ls8c_ard_3-2-1_112080_2023-05-11_final
2023-05-12 10:38:20	ga_ls8c_ard_3-2-1_103080_2023-05-12_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