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
2022-03-22 10:38:05	ga_ls8c_ard_3-2-1_103078_2022-03-22_final
2022-04-10 09:30:52	ga_ls8c_ard_3-2-1_092080_2022-04-10_final
2022-04-24 09:45:36	ga_ls8c_ard_3-2-1_094086_2022-04-24_final
2022-04-24 11:18:30	ga_ls8c_ard_3-2-1_110071_2022-04-24_final
2022-04-26 11:10:55	ga_ls8c_ard_3-2-1_108083_2022-04-26_final
2022-04-27 10:14:53	ga_ls8c_ard_3-2-1_099082_2022-04-27_final
2022-05-02 10:29:28	ga_ls8c_ard_3-2-1_102072_2022-05-02_final
2022-05-03 11:17:08	ga_ls8c_ard_3-2-1_109083_2022-05-03_final
2022-05-16 09:07:28	ga_ls8c_ard_3-2-1_088083_2022-05-15_final
2022-05-31 09:56:45	ga_ls8c_ard_3-2-1_097067_2022-05-31_final
2022-05-31 09:59:08	ga_ls8c_ard_3-2-1_097073_2022-05-31_final
2022-06-03 10:29:17	ga_ls8c_ard_3-2-1_102071_2022-06-03_final
2022-06-08 09:14:12	ga_ls8c_ard_3-2-1_089084_2022-06-07_final
2022-06-16 10:04:08	ga_ls8c_ard_3-2-1_097085_2022-06-16_final
2022-06-16 11:41:25	ga_ls8c_ard_3-2-1_113081_2022-06-16_final
2022-06-24 09:15:08	ga_ls8c_ard_3-2-1_089086_2022-06-23_final
2022-07-13 09:45:38	ga_ls8c_ard_3-2-1_094085_2022-07-13_final
2022-07-16 10:09:21	ga_ls8c_ard_3-2-1_099067_2022-07-16_final
2022-07-17 09:21:19	ga_ls8c_ard_3-2-1_090086_2022-07-16_final
2022-07-18 10:02:12	ga_ls8c_ard_3-2-1_097080_2022-07-18_final
2022-07-24 09:26:24	ga_ls8c_ard_3-2-1_091083_2022-07-23_final
2022-08-02 09:21:55	ga_ls8c_ard_3-2-1_090087_2022-08-01_final
2022-08-03 10:01:36	ga_ls8c_ard_3-2-1_097078_2022-08-03_final
2022-08-14 11:23:13	ga_ls8c_ard_3-2-1_110081_2022-08-14_final
2022-09-03 10:55:43	ga_ls8c_ard_3-2-1_106074_2022-09-03_final
2022-09-15 11:22:56	ga_ls8c_ard_3-2-1_110080_2022-09-15_final
2022-10-01 11:18:33	ga_ls8c_ard_3-2-1_110069_2022-10-01_final
2022-10-03 11:12:10	ga_ls8c_ard_3-2-1_108084_2022-10-03_final
2022-10-08 09:48:35	ga_ls8c_ard_3-2-1_095076_2022-10-08_final
2022-10-10 09:38:59	ga_ls8c_ard_3-2-1_093083_2022-10-10_final
2022-10-23 10:43:49	ga_ls8c_ard_3-2-1_104075_2022-10-23_final
2022-11-08 10:41:27	ga_ls8c_ard_3-2-1_104069_2022-11-08_final
2022-11-08 10:41:51	ga_ls8c_ard_3-2-1_104070_2022-11-08_final
2022-11-09 11:27:30	ga_ls8c_ard_3-2-1_111076_2022-11-09_final
2022-11-23 10:02:30	ga_ls8c_ard_3-2-1_097080_2022-11-23_final
2022-11-25 11:27:50	ga_ls8c_ard_3-2-1_111077_2022-11-25_final
2022-11-27 09:35:48	ga_ls8c_ard_3-2-1_093075_2022-11-27_final
2022-12-06 11:08:54	ga_ls8c_ard_3-2-1_108076_2022-12-06_final
2022-12-09 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-12-09_final
2022-12-29 11:15:20	ga_ls8c_ard_3-2-1_109077_2022-12-29_final
2023-01-03 09:54:12	ga_ls8c_ard_3-2-1_096075_2023-01-03_final
2023-01-05 11:23:31	ga_ls8c_ard_3-2-1_110082_2023-01-05_final
2023-01-08 10:16:19	ga_ls8c_ard_3-2-1_099084_2023-01-08_final
2023-01-23 09:31:24	ga_ls8c_ard_3-2-1_092080_2023-01-23_final
2023-02-01 11:04:08	ga_ls8c_ard_3-2-1_107080_2023-02-01_final
2023-02-04 11:33:03	ga_ls8c_ard_3-2-1_112075_2023-02-04_final
2023-02-05 10:39:25	ga_ls8c_ard_3-2-1_103080_2023-02-05_final
2023-02-07 10:28:14	ga_ls8c_ard_3-2-1_101083_2023-02-07_final
2023-02-08 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-02-08_final
2023-02-17 11:05:35	ga_ls8c_ard_3-2-1_107084_2023-02-17_final
2023-02-24 09:33:31	ga_ls8c_ard_3-2-1_092086_2023-02-24_final
2023-02-25 11:53:15	ga_ls8c_ard_3-2-1_115080_2023-02-25_final
2023-03-06 10:10:09	ga_ls8c_ard_3-2-1_098085_2023-03-06_final
2023-03-12 09:33:26	ga_ls8c_ard_3-2-1_092086_2023-03-12_final
2023-03-12 11:05:56	ga_ls8c_ard_3-2-1_108070_2023-03-12_final
2023-03-18 10:31:35	ga_ls8c_ard_3-2-1_102077_2023-03-18_final
2023-03-19 11:12:03	ga_ls8c_ard_3-2-1_109070_2023-03-19_final
2023-03-21 11:02:03	ga_ls8c_ard_3-2-1_107076_2023-03-21_final
2023-04-06 10:59:51	ga_ls8c_ard_3-2-1_107071_2023-04-06_final
2023-04-08 09:13:45	ga_ls8c_ard_3-2-1_089084_2023-04-07_final
2023-04-10 10:37:25	ga_ls8c_ard_3-2-1_103077_2023-04-10_final
2023-04-13 09:33:01	ga_ls8c_ard_3-2-1_092086_2023-04-13_final
2023-04-19 10:29:59	ga_ls8c_ard_3-2-1_102074_2023-04-19_final
2023-04-27 09:45:19	ga_ls8c_ard_3-2-1_094086_2023-04-27_final
2023-04-28 10:24:11	ga_ls8c_ard_3-2-1_101075_2023-04-28_final
2023-05-02 09:59:02	ga_ls8c_ard_3-2-1_097074_2023-05-02_final
2023-05-03 10:43:04	ga_ls8c_ard_3-2-1_104076_2023-05-03_final
2023-05-13 09:44:42	ga_ls8c_ard_3-2-1_094085_2023-05-13_final
2023-05-26 09:12:13	ga_ls8c_ard_3-2-1_089081_2023-05-25_final
2023-05-29 09:45:07	ga_ls8c_ard_3-2-1_094086_2023-05-29_final
2023-06-07 11:14:42	ga_ls8c_ard_3-2-1_109078_2023-06-07_final
2023-06-26 10:03:17	ga_ls8c_ard_3-2-1_098069_2023-06-26_final
2023-06-27 10:47:21	ga_ls8c_ard_3-2-1_105071_2023-06-27_final
2023-06-28 11:35:25	ga_ls8c_ard_3-2-1_112083_2023-06-28_final
2023-07-06 10:45:41	ga_ls8c_ard_3-2-1_104082_2023-07-06_final
2023-07-11 11:03:27	ga_ls8c_ard_3-2-1_107080_2023-07-11_final
2023-07-13 10:49:06	ga_ls8c_ard_3-2-1_105075_2023-07-13_final
2023-07-21 09:58:28	ga_ls8c_ard_3-2-1_097072_2023-07-21_final
2023-07-27 11:03:57	ga_ls8c_ard_3-2-1_107081_2023-07-27_final
2023-08-06 10:00:37	ga_ls8c_ard_3-2-1_097077_2023-08-06_final
2023-08-08 09:47:04	ga_ls8c_ard_3-2-1_095074_2023-08-08_final
2023-08-10 11:13:11	ga_ls8c_ard_3-2-1_109073_2023-08-10_final
2023-08-15 11:34:58	ga_ls8c_ard_3-2-1_112081_2023-08-15_final
2023-08-16 10:34:58	ga_ls8c_ard_3-2-1_103070_2023-08-16_final
2023-08-19 11:05:31	ga_ls8c_ard_3-2-1_108069_2023-08-19_final
2023-08-28 11:00:34	ga_ls8c_ard_3-2-1_107072_2023-08-28_final
2023-08-31 09:51:47	ga_ls8c_ard_3-2-1_096070_2023-08-31_final
2023-09-08 10:41:12	ga_ls8c_ard_3-2-1_104070_2023-09-08_final
2023-09-23 09:58:50	ga_ls8c_ard_3-2-1_097072_2023-09-23_final
2023-10-13 11:13:06	ga_ls8c_ard_3-2-1_109072_2023-10-13_final
2023-10-14 11:58:45	ga_ls8c_ard_3-2-1_116078_2023-10-14_final
2023-10-16 11:45:11	ga_ls8c_ard_3-2-1_114075_2023-10-16_final
2023-10-23 11:52:59	ga_ls8c_ard_3-2-1_115079_2023-10-23_final
2023-10-29 09:40:15	ga_ls8c_ard_3-2-1_093087_2023-10-29_final
2023-11-03 09:54:47	ga_ls8c_ard_3-2-1_096077_2023-11-03_final
2023-11-04 10:34:51	ga_ls8c_ard_3-2-1_103069_2023-11-04_final
2023-11-17 10:03:34	ga_ls8c_ard_3-2-1_098068_2023-11-17_final
2023-11-18 10:50:49	ga_ls8c_ard_3-2-1_105078_2023-11-18_final
2023-11-21 11:22:32	ga_ls8c_ard_3-2-1_110080_2023-11-21_final
2023-11-22 10:25:20	ga_ls8c_ard_3-2-1_101076_2023-11-22_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