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
2022-05-26 11:24:13	ga_ls8c_ard_3-2-1_110085_2022-05-26_final
2022-06-04 11:16:09	ga_ls8c_ard_3-2-1_109080_2022-06-04_final
2022-06-09 11:33:34	ga_ls8c_ard_3-2-1_112077_2022-06-09_final
2022-06-22 11:03:11	ga_ls8c_ard_3-2-1_107078_2022-06-22_final
2022-06-27 11:22:08	ga_ls8c_ard_3-2-1_110079_2022-06-27_final
2022-06-27 11:22:32	ga_ls8c_ard_3-2-1_110080_2022-06-27_final
2022-07-04 11:28:20	ga_ls8c_ard_3-2-1_111079_2022-07-04_final
2022-07-05 10:32:42	ga_ls8c_ard_3-2-1_102079_2022-07-05_final
2022-07-08 11:03:12	ga_ls8c_ard_3-2-1_107078_2022-07-08_final
2022-07-14 10:26:30	ga_ls8c_ard_3-2-1_101079_2022-07-14_final
2022-07-16 10:14:56	ga_ls8c_ard_3-2-1_099081_2022-07-16_final
2022-07-19 10:43:05	ga_ls8c_ard_3-2-1_104074_2022-07-19_final
2022-07-20 09:49:05	ga_ls8c_ard_3-2-1_095078_2022-07-20_final
2022-07-31 11:09:33	ga_ls8c_ard_3-2-1_108078_2022-07-31_final
2022-08-01 10:15:08	ga_ls8c_ard_3-2-1_099081_2022-08-01_final
2022-08-03 10:03:12	ga_ls8c_ard_3-2-1_097082_2022-08-03_final
2022-08-06 10:32:32	ga_ls8c_ard_3-2-1_102078_2022-08-06_final
2022-08-06 10:32:56	ga_ls8c_ard_3-2-1_102079_2022-08-06_final
2022-08-10 10:07:02	ga_ls8c_ard_3-2-1_098076_2022-08-10_final
2022-08-12 11:33:34	ga_ls8c_ard_3-2-1_112076_2022-08-12_final
2022-08-12 11:35:10	ga_ls8c_ard_3-2-1_112080_2022-08-12_final
2022-08-14 09:41:56	ga_ls8c_ard_3-2-1_094075_2022-08-14_final
2022-08-16 11:09:40	ga_ls8c_ard_3-2-1_108078_2022-08-16_final
2022-08-18 10:57:43	ga_ls8c_ard_3-2-1_106079_2022-08-18_final
2022-08-19 10:00:54	ga_ls8c_ard_3-2-1_097076_2022-08-19_final
2022-08-19 10:03:17	ga_ls8c_ard_3-2-1_097082_2022-08-19_final
2022-08-21 09:48:56	ga_ls8c_ard_3-2-1_095077_2022-08-21_final
2022-08-21 09:49:20	ga_ls8c_ard_3-2-1_095078_2022-08-21_final
2022-08-21 11:28:37	ga_ls8c_ard_3-2-1_111079_2022-08-21_final
2022-08-22 10:31:48	ga_ls8c_ard_3-2-1_102076_2022-08-22_final
2022-08-22 10:32:36	ga_ls8c_ard_3-2-1_102078_2022-08-22_final
2022-08-22 10:33:00	ga_ls8c_ard_3-2-1_102079_2022-08-22_final
2022-08-23 11:12:40	ga_ls8c_ard_3-2-1_109070_2022-08-23_final
2022-08-28 09:54:43	ga_ls8c_ard_3-2-1_096076_2022-08-28_final
2022-08-28 09:55:07	ga_ls8c_ard_3-2-1_096077_2022-08-28_final
2022-08-29 10:37:58	ga_ls8c_ard_3-2-1_103076_2022-08-29_final
2022-09-01 11:09:16	ga_ls8c_ard_3-2-1_108077_2022-09-01_final
2022-09-01 11:09:40	ga_ls8c_ard_3-2-1_108078_2022-09-01_final
2022-09-04 10:03:17	ga_ls8c_ard_3-2-1_097082_2022-09-04_final
2022-09-07 10:32:38	ga_ls8c_ard_3-2-1_102078_2022-09-07_final
2022-09-17 11:09:47	ga_ls8c_ard_3-2-1_108078_2022-09-17_final
2022-09-23 10:31:55	ga_ls8c_ard_3-2-1_102076_2022-09-23_final
2022-09-23 10:33:30	ga_ls8c_ard_3-2-1_102080_2022-09-23_final
2022-10-05 09:19:42	ga_ls8c_ard_3-2-1_090081_2022-10-04_final
2022-10-06 10:00:34	ga_ls8c_ard_3-2-1_097075_2022-10-06_final
2022-10-06 10:03:21	ga_ls8c_ard_3-2-1_097082_2022-10-06_final
2022-10-09 10:33:25	ga_ls8c_ard_3-2-1_102080_2022-10-09_final
2022-10-18 10:27:13	ga_ls8c_ard_3-2-1_101080_2022-10-18_final
2022-10-22 10:00:33	ga_ls8c_ard_3-2-1_097075_2022-10-22_final
2022-10-23 10:46:13	ga_ls8c_ard_3-2-1_104081_2022-10-23_final
2022-11-03 10:27:19	ga_ls8c_ard_3-2-1_101080_2022-11-03_final
2022-11-18 11:18:25	ga_ls8c_ard_3-2-1_110069_2022-11-18_final
2022-11-20 09:29:59	ga_ls8c_ard_3-2-1_092076_2022-11-19_final
2022-12-18 09:54:38	ga_ls8c_ard_3-2-1_096076_2022-12-18_final
2022-12-21 10:27:05	ga_ls8c_ard_3-2-1_101080_2022-12-21_final
2022-12-22 11:09:31	ga_ls8c_ard_3-2-1_108078_2022-12-22_final
2022-12-28 10:31:16	ga_ls8c_ard_3-2-1_102075_2022-12-28_final
2022-12-29 09:38:27	ga_ls8c_ard_3-2-1_093082_2022-12-29_final
2023-01-06 10:27:05	ga_ls8c_ard_3-2-1_101080_2023-01-06_final
2023-01-10 11:40:49	ga_ls8c_ard_3-2-1_113079_2023-01-10_final
2023-02-11 11:40:46	ga_ls8c_ard_3-2-1_113079_2023-02-11_final
2023-02-15 09:38:18	ga_ls8c_ard_3-2-1_093082_2023-02-15_final
2023-02-19 10:50:48	ga_ls8c_ard_3-2-1_105078_2023-02-19_final
2023-02-24 11:09:13	ga_ls8c_ard_3-2-1_108078_2023-02-24_final
2023-02-26 10:54:26	ga_ls8c_ard_3-2-1_106072_2023-02-26_final
2023-02-27 11:39:42	ga_ls8c_ard_3-2-1_113077_2023-02-27_final
2023-03-02 10:32:54	ga_ls8c_ard_3-2-1_102080_2023-03-02_final
2023-03-07 10:50:36	ga_ls8c_ard_3-2-1_105078_2023-03-07_final
2023-03-09 10:38:37	ga_ls8c_ard_3-2-1_103079_2023-03-09_final
2023-03-10 09:44:35	ga_ls8c_ard_3-2-1_094083_2023-03-10_final
2023-03-15 10:02:43	ga_ls8c_ard_3-2-1_097082_2023-03-15_final
2023-03-16 10:44:46	ga_ls8c_ard_3-2-1_104079_2023-03-16_final
2023-03-17 09:48:44	ga_ls8c_ard_3-2-1_095078_2023-03-17_final
2023-03-23 10:51:38	ga_ls8c_ard_3-2-1_105081_2023-03-23_final
2023-03-24 11:32:54	ga_ls8c_ard_3-2-1_112076_2023-03-24_final
2023-04-02 09:48:33	ga_ls8c_ard_3-2-1_095078_2023-04-02_final
2023-04-09 09:54:11	ga_ls8c_ard_3-2-1_096077_2023-04-09_final
2023-04-09 11:32:40	ga_ls8c_ard_3-2-1_112076_2023-04-09_final
2023-04-16 11:38:47	ga_ls8c_ard_3-2-1_113076_2023-04-16_final
2023-04-18 11:27:36	ga_ls8c_ard_3-2-1_111079_2023-04-18_final
2023-04-19 10:30:46	ga_ls8c_ard_3-2-1_102076_2023-04-19_final
2023-04-25 09:53:42	ga_ls8c_ard_3-2-1_096076_2023-04-25_final
2023-04-25 09:54:06	ga_ls8c_ard_3-2-1_096077_2023-04-25_final
2023-04-28 10:25:47	ga_ls8c_ard_3-2-1_101079_2023-04-28_final
2023-04-29 11:08:14	ga_ls8c_ard_3-2-1_108077_2023-04-29_final
2023-04-29 11:08:38	ga_ls8c_ard_3-2-1_108078_2023-04-29_final
2023-05-02 09:59:49	ga_ls8c_ard_3-2-1_097076_2023-05-02_final
2023-05-04 11:27:31	ga_ls8c_ard_3-2-1_111079_2023-05-04_final
2023-05-05 10:31:29	ga_ls8c_ard_3-2-1_102078_2023-05-05_final
2023-05-05 10:31:53	ga_ls8c_ard_3-2-1_102079_2023-05-05_final
2023-05-11 09:53:30	ga_ls8c_ard_3-2-1_096076_2023-05-11_final
2023-05-11 09:53:54	ga_ls8c_ard_3-2-1_096077_2023-05-11_final
2023-05-11 11:33:11	ga_ls8c_ard_3-2-1_112078_2023-05-11_final
2023-05-11 11:33:58	ga_ls8c_ard_3-2-1_112080_2023-05-11_final
2023-05-13 09:40:43	ga_ls8c_ard_3-2-1_094075_2023-05-13_final
2023-05-14 10:25:34	ga_ls8c_ard_3-2-1_101079_2023-05-14_final
2023-05-15 11:08:25	ga_ls8c_ard_3-2-1_108078_2023-05-15_final
2023-05-16 10:13:59	ga_ls8c_ard_3-2-1_099081_2023-05-16_final
2023-05-17 10:56:02	ga_ls8c_ard_3-2-1_106078_2023-05-17_final
2023-05-20 11:27:21	ga_ls8c_ard_3-2-1_111079_2023-05-20_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