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
2022-01-25 11:25:51	ga_ls8c_ard_3-2-1_111073_2022-01-25_final
2022-01-29 09:23:01	ga_ls8c_ard_3-2-1_091075_2022-01-28_final
2022-02-03 11:21:14	ga_ls8c_ard_3-2-1_110077_2022-02-03_final
2022-02-08 09:57:17	ga_ls8c_ard_3-2-1_097068_2022-02-08_final
2022-02-08 10:02:04	ga_ls8c_ard_3-2-1_097080_2022-02-08_final
2022-02-23 09:18:43	ga_ls8c_ard_3-2-1_090080_2022-02-22_final
2022-03-04 09:13:43	ga_ls8c_ard_3-2-1_089083_2022-03-03_final
2022-03-15 10:33:11	ga_ls8c_ard_3-2-1_102081_2022-03-15_final
2022-04-15 11:23:32	ga_ls8c_ard_3-2-1_111068_2022-04-15_final
2022-04-19 09:23:54	ga_ls8c_ard_3-2-1_091078_2022-04-18_final
2022-04-27 10:09:42	ga_ls8c_ard_3-2-1_099069_2022-04-27_final
2022-05-01 11:25:52	ga_ls8c_ard_3-2-1_111074_2022-05-01_final
2022-05-03 09:35:27	ga_ls8c_ard_3-2-1_093076_2022-05-03_final
2022-05-04 11:58:25	ga_ls8c_ard_3-2-1_116078_2022-05-04_final
2022-05-13 10:09:27	ga_ls8c_ard_3-2-1_099068_2022-05-13_final
2022-06-07 10:03:26	ga_ls8c_ard_3-2-1_098068_2022-06-07_final
2022-06-12 10:28:01	ga_ls8c_ard_3-2-1_101083_2022-06-12_final
2022-06-20 11:14:44	ga_ls8c_ard_3-2-1_109076_2022-06-20_final
2022-06-23 10:03:58	ga_ls8c_ard_3-2-1_098069_2022-06-23_final
2022-06-29 09:34:29	ga_ls8c_ard_3-2-1_092088_2022-06-29_final
2022-07-05 10:33:30	ga_ls8c_ard_3-2-1_102081_2022-07-05_final
2022-07-08 09:28:43	ga_ls8c_ard_3-2-1_091089_2022-07-07_final
2022-07-10 10:46:27	ga_ls8c_ard_3-2-1_105067_2022-07-10_final
2022-07-15 11:05:46	ga_ls8c_ard_3-2-1_108069_2022-07-15_final
2022-07-20 09:46:17	ga_ls8c_ard_3-2-1_095071_2022-07-20_final
2022-07-20 09:47:05	ga_ls8c_ard_3-2-1_095073_2022-07-20_final
2022-07-31 11:07:57	ga_ls8c_ard_3-2-1_108074_2022-07-31_final
2022-08-02 10:58:49	ga_ls8c_ard_3-2-1_106082_2022-08-02_final
2022-08-03 11:40:05	ga_ls8c_ard_3-2-1_113077_2022-08-03_final
2022-08-03 11:40:53	ga_ls8c_ard_3-2-1_113079_2022-08-03_final
2022-08-14 11:23:37	ga_ls8c_ard_3-2-1_110082_2022-08-14_final
2022-08-17 11:52:56	ga_ls8c_ard_3-2-1_115078_2022-08-17_final
2022-08-18 10:53:19	ga_ls8c_ard_3-2-1_106068_2022-08-18_final
2022-09-01 11:08:04	ga_ls8c_ard_3-2-1_108074_2022-09-01_final
2022-09-17 09:34:05	ga_ls8c_ard_3-2-1_092086_2022-09-17_final
2022-09-25 11:59:14	ga_ls8c_ard_3-2-1_116078_2022-09-25_final
2022-09-26 09:22:20	ga_ls8c_ard_3-2-1_091072_2022-09-25_final
2022-09-27 11:47:16	ga_ls8c_ard_3-2-1_114079_2022-09-27_final
2022-09-29 09:58:01	ga_ls8c_ard_3-2-1_096084_2022-09-29_final
2022-10-04 10:10:09	ga_ls8c_ard_3-2-1_099068_2022-10-04_final
2022-10-07 10:46:12	ga_ls8c_ard_3-2-1_104081_2022-10-07_final
2022-10-13 11:47:07	ga_ls8c_ard_3-2-1_114079_2022-10-13_final
2022-10-21 10:53:22	ga_ls8c_ard_3-2-1_106068_2022-10-21_final
2022-10-23 10:46:13	ga_ls8c_ard_3-2-1_104081_2022-10-23_final
2022-11-02 11:21:45	ga_ls8c_ard_3-2-1_110077_2022-11-02_final
2022-11-05 10:11:22	ga_ls8c_ard_3-2-1_099071_2022-11-05_final
2022-11-06 10:53:26	ga_ls8c_ard_3-2-1_106068_2022-11-06_final
2022-11-11 11:14:19	ga_ls8c_ard_3-2-1_109074_2022-11-11_final
2022-11-12 11:58:46	ga_ls8c_ard_3-2-1_116077_2022-11-12_final
2022-11-13 09:25:27	ga_ls8c_ard_3-2-1_091080_2022-11-12_final
2022-11-29 09:28:38	ga_ls8c_ard_3-2-1_091088_2022-11-28_final
2022-12-07 10:10:05	ga_ls8c_ard_3-2-1_099068_2022-12-07_final
2022-12-12 10:31:47	ga_ls8c_ard_3-2-1_102076_2022-12-12_final
2022-12-15 09:28:09	ga_ls8c_ard_3-2-1_091087_2022-12-14_final
2022-12-15 11:04:15	ga_ls8c_ard_3-2-1_107080_2022-12-15_final
2022-12-20 11:21:55	ga_ls8c_ard_3-2-1_110078_2022-12-20_final
2022-12-23 10:14:17	ga_ls8c_ard_3-2-1_099079_2022-12-23_final
2022-12-26 10:42:49	ga_ls8c_ard_3-2-1_104073_2022-12-26_final
2023-01-05 11:21:07	ga_ls8c_ard_3-2-1_110076_2023-01-05_final
2023-01-07 11:05:57	ga_ls8c_ard_3-2-1_108069_2023-01-07_final
2023-01-11 10:43:12	ga_ls8c_ard_3-2-1_104074_2023-01-11_final
2023-01-11 10:46:23	ga_ls8c_ard_3-2-1_104082_2023-01-11_final
2023-01-14 11:13:40	ga_ls8c_ard_3-2-1_109073_2023-01-14_final
2023-01-17 11:46:54	ga_ls8c_ard_3-2-1_114079_2023-01-17_final
2023-01-19 11:34:09	ga_ls8c_ard_3-2-1_112078_2023-01-19_final
2023-01-23 11:05:54	ga_ls8c_ard_3-2-1_108069_2023-01-23_final
2023-02-01 11:00:09	ga_ls8c_ard_3-2-1_107070_2023-02-01_final
2023-02-02 10:05:20	ga_ls8c_ard_3-2-1_098072_2023-02-02_final
2023-02-04 11:32:39	ga_ls8c_ard_3-2-1_112074_2023-02-04_final
2023-02-09 10:16:39	ga_ls8c_ard_3-2-1_099085_2023-02-09_final
2023-02-12 09:07:26	ga_ls8c_ard_3-2-1_088082_2023-02-11_final
2023-02-15 11:12:24	ga_ls8c_ard_3-2-1_109070_2023-02-15_final
2023-02-15 11:17:59	ga_ls8c_ard_3-2-1_109084_2023-02-15_final
2023-02-20 09:51:58	ga_ls8c_ard_3-2-1_096070_2023-02-20_final
2023-03-04 10:19:20	ga_ls8c_ard_3-2-1_100077_2023-03-04_final
2023-03-14 10:58:45	ga_ls8c_ard_3-2-1_106083_2023-03-14_final
2023-03-19 11:17:14	ga_ls8c_ard_3-2-1_109083_2023-03-19_final
2023-04-06 09:22:10	ga_ls8c_ard_3-2-1_091074_2023-04-05_final
2023-04-06 09:22:34	ga_ls8c_ard_3-2-1_091075_2023-04-05_final
2023-04-15 10:52:44	ga_ls8c_ard_3-2-1_106069_2023-04-15_final
2023-04-19 10:31:58	ga_ls8c_ard_3-2-1_102079_2023-04-19_final
2023-04-21 10:16:25	ga_ls8c_ard_3-2-1_100071_2023-04-21_final
2023-05-03 10:45:28	ga_ls8c_ard_3-2-1_104082_2023-05-03_final
2023-05-07 10:21:05	ga_ls8c_ard_3-2-1_100083_2023-05-07_final
2023-05-08 09:27:27	ga_ls8c_ard_3-2-1_091088_2023-05-07_final
2023-05-12 10:39:08	ga_ls8c_ard_3-2-1_103082_2023-05-12_final
2023-05-14 10:26:46	ga_ls8c_ard_3-2-1_101082_2023-05-14_final
2023-05-18 10:01:13	ga_ls8c_ard_3-2-1_097080_2023-05-18_final
2023-05-25 10:03:03	ga_ls8c_ard_3-2-1_098069_2023-05-25_final
2023-05-26 09:10:38	ga_ls8c_ard_3-2-1_089077_2023-05-25_final
2023-05-31 11:06:51	ga_ls8c_ard_3-2-1_108074_2023-05-31_final
2023-06-08 11:57:59	ga_ls8c_ard_3-2-1_116078_2023-06-08_final
2023-06-25 09:27:11	ga_ls8c_ard_3-2-1_091087_2023-06-24_final
2023-06-29 10:37:25	ga_ls8c_ard_3-2-1_103077_2023-06-29_final
2023-07-03 10:09:10	ga_ls8c_ard_3-2-1_099068_2023-07-03_final
2023-07-16 11:19:37	ga_ls8c_ard_3-2-1_110074_2023-07-16_final
2023-08-02 10:22:32	ga_ls8c_ard_3-2-1_101070_2023-08-02_final
2023-08-06 10:01:49	ga_ls8c_ard_3-2-1_097080_2023-08-06_final
2023-08-13 11:46:30	ga_ls8c_ard_3-2-1_114079_2023-08-13_final
2023-09-11 11:13:45	ga_ls8c_ard_3-2-1_109074_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