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
2021-10-27 10:51:02	ga_ls8c_ard_3-2-0_105078_2021-10-27_final
2022-01-10 10:33:54	ga_ls8c_ard_3-2-1_102082_2022-01-10_final
2022-01-18 09:42:49	ga_ls8c_ard_3-2-1_094078_2022-01-18_final
2022-02-03 09:42:45	ga_ls8c_ard_3-2-1_094078_2022-02-03_final
2022-02-10 09:48:30	ga_ls8c_ard_3-2-1_095077_2022-02-10_final
2022-02-12 09:38:08	ga_ls8c_ard_3-2-1_093082_2022-02-12_final
2022-02-17 09:54:14	ga_ls8c_ard_3-2-1_096076_2022-02-17_final
2022-02-25 10:42:03	ga_ls8c_ard_3-2-1_104072_2022-02-25_final
2022-02-25 10:44:51	ga_ls8c_ard_3-2-1_104079_2022-02-25_final
2022-02-26 11:28:06	ga_ls8c_ard_3-2-1_111079_2022-02-26_final
2022-03-07 09:41:25	ga_ls8c_ard_3-2-1_094075_2022-03-07_final
2022-03-14 09:48:21	ga_ls8c_ard_3-2-1_095077_2022-03-14_final
2022-03-19 10:08:26	ga_ls8c_ard_3-2-1_098081_2022-03-19_final
2022-03-19 10:08:49	ga_ls8c_ard_3-2-1_098082_2022-03-19_final
2022-03-21 11:34:08	ga_ls8c_ard_3-2-1_112079_2022-03-21_final
2022-03-23 11:21:20	ga_ls8c_ard_3-2-1_110078_2022-03-23_final
2022-03-31 10:31:48	ga_ls8c_ard_3-2-1_102078_2022-03-31_final
2022-04-04 10:05:53	ga_ls8c_ard_3-2-1_098075_2022-04-04_final
2022-04-04 10:08:41	ga_ls8c_ard_3-2-1_098082_2022-04-04_final
2022-04-07 10:38:25	ga_ls8c_ard_3-2-1_103079_2022-04-07_final
2022-04-17 09:37:52	ga_ls8c_ard_3-2-1_093082_2022-04-17_final
2022-04-22 09:53:59	ga_ls8c_ard_3-2-1_096076_2022-04-22_final
2022-04-22 09:54:23	ga_ls8c_ard_3-2-1_096077_2022-04-22_final
2022-04-24 11:24:05	ga_ls8c_ard_3-2-1_110085_2022-04-24_final
2022-04-28 10:58:32	ga_ls8c_ard_3-2-1_106083_2022-04-28_final
2022-05-07 10:50:04	ga_ls8c_ard_3-2-1_105077_2022-05-07_final
2022-05-22 10:08:53	ga_ls8c_ard_3-2-1_098082_2022-05-22_final
2022-06-13 11:09:17	ga_ls8c_ard_3-2-1_108078_2022-06-13_final
2022-06-21 11:58:24	ga_ls8c_ard_3-2-1_116077_2022-06-21_final
2022-06-25 11:34:06	ga_ls8c_ard_3-2-1_112078_2022-06-25_final
2022-06-27 11:22:32	ga_ls8c_ard_3-2-1_110080_2022-06-27_final
2022-07-05 10:32:18	ga_ls8c_ard_3-2-1_102078_2022-07-05_final
2022-07-11 11:34:06	ga_ls8c_ard_3-2-1_112078_2022-07-11_final
2022-07-13 09:42:51	ga_ls8c_ard_3-2-1_094078_2022-07-13_final
2022-07-25 10:08:53	ga_ls8c_ard_3-2-1_098081_2022-07-25_final
2022-08-03 10:00:24	ga_ls8c_ard_3-2-1_097075_2022-08-03_final
2022-08-06 10:32:56	ga_ls8c_ard_3-2-1_102079_2022-08-06_final
2022-08-17 10:12:51	ga_ls8c_ard_3-2-1_099075_2022-08-17_final
2022-08-22 10:31:48	ga_ls8c_ard_3-2-1_102076_2022-08-22_final
2022-08-29 10:39:10	ga_ls8c_ard_3-2-1_103079_2022-08-29_final
2022-09-03 10:57:18	ga_ls8c_ard_3-2-1_106078_2022-09-03_final
2022-09-07 10:32:38	ga_ls8c_ard_3-2-1_102078_2022-09-07_final
2022-09-07 10:33:02	ga_ls8c_ard_3-2-1_102079_2022-09-07_final
2022-09-15 11:22:08	ga_ls8c_ard_3-2-1_110078_2022-09-15_final
2022-09-18 10:12:58	ga_ls8c_ard_3-2-1_099075_2022-09-18_final
2022-09-28 10:51:15	ga_ls8c_ard_3-2-1_105078_2022-09-28_final
2022-10-09 10:31:49	ga_ls8c_ard_3-2-1_102076_2022-10-09_final
2022-10-14 10:51:06	ga_ls8c_ard_3-2-1_105078_2022-10-14_final
2022-10-17 09:43:09	ga_ls8c_ard_3-2-1_094078_2022-10-17_final
2022-10-27 11:58:49	ga_ls8c_ard_3-2-1_116077_2022-10-27_final
2022-10-31 11:34:06	ga_ls8c_ard_3-2-1_112077_2022-10-31_final
2022-11-23 11:40:59	ga_ls8c_ard_3-2-1_113079_2022-11-23_final
2022-11-25 09:48:57	ga_ls8c_ard_3-2-1_095077_2022-11-25_final
2022-12-02 09:54:45	ga_ls8c_ard_3-2-1_096076_2022-12-02_final
2022-12-09 10:00:30	ga_ls8c_ard_3-2-1_097075_2022-12-09_final
2022-12-11 09:48:32	ga_ls8c_ard_3-2-1_095076_2022-12-11_final
2023-02-07 10:23:03	ga_ls8c_ard_3-2-1_101070_2023-02-07_final
2023-02-18 10:08:45	ga_ls8c_ard_3-2-1_098081_2023-02-18_final
2023-02-24 11:08:25	ga_ls8c_ard_3-2-1_108076_2023-02-24_final
2023-03-01 09:48:27	ga_ls8c_ard_3-2-1_095077_2023-03-01_final
2023-03-04 11:58:13	ga_ls8c_ard_3-2-1_116077_2023-03-04_final
2023-03-08 11:33:03	ga_ls8c_ard_3-2-1_112076_2023-03-08_final
2023-03-17 11:28:01	ga_ls8c_ard_3-2-1_111079_2023-03-17_final
2023-03-22 10:08:24	ga_ls8c_ard_3-2-1_098081_2023-03-22_final
2023-03-26 09:42:51	ga_ls8c_ard_3-2-1_094079_2023-03-26_final
2023-04-04 09:37:45	ga_ls8c_ard_3-2-1_093082_2023-04-04_final
2023-04-10 10:38:13	ga_ls8c_ard_3-2-1_103079_2023-04-10_final
2023-04-28 10:26:11	ga_ls8c_ard_3-2-1_101080_2023-04-28_final
2023-04-30 10:14:12	ga_ls8c_ard_3-2-1_099081_2023-04-30_final
2023-05-04 09:47:26	ga_ls8c_ard_3-2-1_095076_2023-05-04_final
2023-05-04 11:27:31	ga_ls8c_ard_3-2-1_111079_2023-05-04_final
2023-05-09 10:07:54	ga_ls8c_ard_3-2-1_098081_2023-05-09_final
2023-05-11 09:53:54	ga_ls8c_ard_3-2-1_096077_2023-05-11_final
2023-05-29 09:41:32	ga_ls8c_ard_3-2-1_094077_2023-05-29_final
2023-05-29 09:41:56	ga_ls8c_ard_3-2-1_094078_2023-05-29_final
2023-05-30 10:25:59	ga_ls8c_ard_3-2-1_101080_2023-05-30_final
2023-06-03 11:38:34	ga_ls8c_ard_3-2-1_113076_2023-06-03_final
2023-06-07 09:35:25	ga_ls8c_ard_3-2-1_093077_2023-06-07_final
2023-06-13 10:36:53	ga_ls8c_ard_3-2-1_103076_2023-06-13_final
2023-06-14 09:42:04	ga_ls8c_ard_3-2-1_094078_2023-06-14_final
2023-06-19 10:02:13	ga_ls8c_ard_3-2-1_097082_2023-06-19_final
2023-06-21 11:27:33	ga_ls8c_ard_3-2-1_111079_2023-06-21_final
2023-07-05 11:38:54	ga_ls8c_ard_3-2-1_113076_2023-07-05_final
2023-07-10 11:57:52	ga_ls8c_ard_3-2-1_116077_2023-07-10_final
2023-07-14 09:56:41	ga_ls8c_ard_3-2-1_096083_2023-07-14_final
2023-07-16 11:21:36	ga_ls8c_ard_3-2-1_110079_2023-07-16_final
2023-07-21 10:02:27	ga_ls8c_ard_3-2-1_097082_2023-07-21_final
2023-07-30 09:53:36	ga_ls8c_ard_3-2-1_096075_2023-07-30_final
2023-08-06 09:59:49	ga_ls8c_ard_3-2-1_097075_2023-08-06_final
2023-08-10 09:36:41	ga_ls8c_ard_3-2-1_093079_2023-08-10_final
2023-08-17 09:42:33	ga_ls8c_ard_3-2-1_094078_2023-08-17_final
2023-08-22 09:59:57	ga_ls8c_ard_3-2-1_097075_2023-08-22_final
2023-08-22 11:40:02	ga_ls8c_ard_3-2-1_113078_2023-08-22_final
2023-08-23 10:43:37	ga_ls8c_ard_3-2-1_104076_2023-08-23_final
2023-08-25 10:32:27	ga_ls8c_ard_3-2-1_102079_2023-08-25_final
2023-08-31 09:54:35	ga_ls8c_ard_3-2-1_096077_2023-08-31_final
2023-09-03 10:26:40	ga_ls8c_ard_3-2-1_101080_2023-09-03_final
2023-09-05 10:14:41	ga_ls8c_ard_3-2-1_099081_2023-09-05_final
2023-09-07 10:02:43	ga_ls8c_ard_3-2-1_097082_2023-09-07_final
2023-09-08 10:43:36	ga_ls8c_ard_3-2-1_104076_2023-09-08_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