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
2022-06-08 10:50:18	ga_ls8c_ard_3-2-1_105077_2022-06-08_final
2022-06-18 09:49:23	ga_ls8c_ard_3-2-1_095079_2022-06-18_final
2022-06-25 11:33:42	ga_ls8c_ard_3-2-1_112077_2022-06-25_final
2022-06-25 11:34:06	ga_ls8c_ard_3-2-1_112078_2022-06-25_final
2022-06-27 11:21:44	ga_ls8c_ard_3-2-1_110078_2022-06-27_final
2022-07-06 11:15:58	ga_ls8c_ard_3-2-1_109079_2022-07-06_final
2022-07-11 11:33:42	ga_ls8c_ard_3-2-1_112077_2022-07-11_final
2022-07-11 11:34:06	ga_ls8c_ard_3-2-1_112078_2022-07-11_final
2022-07-11 11:34:30	ga_ls8c_ard_3-2-1_112079_2022-07-11_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
2022-07-20 09:48:41	ga_ls8c_ard_3-2-1_095077_2022-07-20_final
2022-07-26 10:50:34	ga_ls8c_ard_3-2-1_105077_2022-07-26_final
2022-07-27 11:33:26	ga_ls8c_ard_3-2-1_112076_2022-07-27_final
2022-07-27 11:33:50	ga_ls8c_ard_3-2-1_112077_2022-07-27_final
2022-07-27 11:34:14	ga_ls8c_ard_3-2-1_112078_2022-07-27_final
2022-07-28 10:37:25	ga_ls8c_ard_3-2-1_103075_2022-07-28_final
2022-07-29 09:43:01	ga_ls8c_ard_3-2-1_094078_2022-07-29_final
2022-08-05 09:48:51	ga_ls8c_ard_3-2-1_095077_2022-08-05_final
2022-08-06 10:31:44	ga_ls8c_ard_3-2-1_102076_2022-08-06_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
2022-08-13 10:37:33	ga_ls8c_ard_3-2-1_103075_2022-08-13_final
2022-08-21 09:49:44	ga_ls8c_ard_3-2-1_095079_2022-08-21_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
2022-08-30 11:22:26	ga_ls8c_ard_3-2-1_110079_2022-08-30_final
2022-09-13 11:34:53	ga_ls8c_ard_3-2-1_112079_2022-09-13_final
2022-09-15 11:22:08	ga_ls8c_ard_3-2-1_110078_2022-09-15_final
2022-09-20 10:01:24	ga_ls8c_ard_3-2-1_097077_2022-09-20_final
2022-09-22 09:49:03	ga_ls8c_ard_3-2-1_095077_2022-09-22_final
2022-09-28 10:51:15	ga_ls8c_ard_3-2-1_105078_2022-09-28_final
2022-10-08 11:28:39	ga_ls8c_ard_3-2-1_111079_2022-10-08_final
2022-10-17 11:22:02	ga_ls8c_ard_3-2-1_110078_2022-10-17_final
2022-10-24 09:49:24	ga_ls8c_ard_3-2-1_095078_2022-10-24_final
2022-11-04 09:35:17	ga_ls8c_ard_3-2-1_092089_2022-11-04_final
2022-11-18 09:43:08	ga_ls8c_ard_3-2-1_094078_2022-11-18_final
2022-11-20 11:09:16	ga_ls8c_ard_3-2-1_108077_2022-11-20_final
2022-11-25 09:49:45	ga_ls8c_ard_3-2-1_095079_2022-11-25_final
2022-12-10 10:46:09	ga_ls8c_ard_3-2-1_104081_2022-12-10_final
2022-12-21 10:27:05	ga_ls8c_ard_3-2-1_101080_2022-12-21_final
2023-01-22 10:27:01	ga_ls8c_ard_3-2-1_101080_2023-01-22_final
2023-02-07 10:27:02	ga_ls8c_ard_3-2-1_101080_2023-02-07_final
2023-02-22 09:42:45	ga_ls8c_ard_3-2-1_094078_2023-02-22_final
2023-03-01 09:48:51	ga_ls8c_ard_3-2-1_095078_2023-03-01_final
2023-03-08 11:34:15	ga_ls8c_ard_3-2-1_112079_2023-03-08_final
2023-03-10 11:21:53	ga_ls8c_ard_3-2-1_110079_2023-03-10_final
2023-03-11 10:22:40	ga_ls8c_ard_3-2-1_101070_2023-03-11_final
2023-03-17 11:28:01	ga_ls8c_ard_3-2-1_111079_2023-03-17_final
2023-03-21 11:04:26	ga_ls8c_ard_3-2-1_107082_2023-03-21_final
2023-03-22 10:08:48	ga_ls8c_ard_3-2-1_098082_2023-03-22_final
2023-03-23 10:50:27	ga_ls8c_ard_3-2-1_105078_2023-03-23_final
2023-03-24 11:32:54	ga_ls8c_ard_3-2-1_112076_2023-03-24_final
2023-03-26 09:42:27	ga_ls8c_ard_3-2-1_094078_2023-03-26_final
2023-04-02 09:48:57	ga_ls8c_ard_3-2-1_095079_2023-04-02_final
2023-04-09 09:54:35	ga_ls8c_ard_3-2-1_096078_2023-04-09_final
2023-04-09 11:32:40	ga_ls8c_ard_3-2-1_112076_2023-04-09_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
2023-04-27 09:42:07	ga_ls8c_ard_3-2-1_094078_2023-04-27_final
2023-05-11 11:32:23	ga_ls8c_ard_3-2-1_112076_2023-05-11_final
2023-05-17 10:58:02	ga_ls8c_ard_3-2-1_106083_2023-05-17_final
2023-05-27 09:54:17	ga_ls8c_ard_3-2-1_096078_2023-05-27_final
2023-05-29 09:41:56	ga_ls8c_ard_3-2-1_094078_2023-05-29_final
2023-05-30 10:25:35	ga_ls8c_ard_3-2-1_101079_2023-05-30_final
2023-06-05 11:27:02	ga_ls8c_ard_3-2-1_111078_2023-06-05_final
2023-06-12 09:53:37	ga_ls8c_ard_3-2-1_096076_2023-06-12_final
2023-06-12 09:54:01	ga_ls8c_ard_3-2-1_096077_2023-06-12_final
2023-06-14 11:20:57	ga_ls8c_ard_3-2-1_110078_2023-06-14_final
2023-06-21 11:27:33	ga_ls8c_ard_3-2-1_111079_2023-06-21_final
2023-06-28 11:33:02	ga_ls8c_ard_3-2-1_112077_2023-06-28_final
2023-06-28 11:33:26	ga_ls8c_ard_3-2-1_112078_2023-06-28_final
2023-06-30 09:42:13	ga_ls8c_ard_3-2-1_094078_2023-06-30_final
2023-06-30 09:42:37	ga_ls8c_ard_3-2-1_094079_2023-06-30_final
2023-07-03 10:14:21	ga_ls8c_ard_3-2-1_099081_2023-07-03_final
2023-07-07 11:26:57	ga_ls8c_ard_3-2-1_111077_2023-07-07_final
2023-07-08 10:32:08	ga_ls8c_ard_3-2-1_102079_2023-07-08_final
2023-07-10 11:57:52	ga_ls8c_ard_3-2-1_116077_2023-07-10_final
2023-07-14 09:53:53	ga_ls8c_ard_3-2-1_096076_2023-07-14_final
2023-07-14 09:54:41	ga_ls8c_ard_3-2-1_096078_2023-07-14_final
2023-07-24 10:31:49	ga_ls8c_ard_3-2-1_102078_2023-07-24_final
2023-07-24 10:32:13	ga_ls8c_ard_3-2-1_102079_2023-07-24_final
2023-07-30 09:54:00	ga_ls8c_ard_3-2-1_096076_2023-07-30_final
2023-07-30 11:33:17	ga_ls8c_ard_3-2-1_112077_2023-07-30_final
2023-08-08 11:27:56	ga_ls8c_ard_3-2-1_111079_2023-08-08_final
2023-08-10 09:36:41	ga_ls8c_ard_3-2-1_093079_2023-08-10_final
2023-08-15 09:54:30	ga_ls8c_ard_3-2-1_096077_2023-08-15_final
2023-08-15 11:33:47	ga_ls8c_ard_3-2-1_112078_2023-08-15_final
2023-08-17 11:21:50	ga_ls8c_ard_3-2-1_110079_2023-08-17_final
2023-08-22 11:39:14	ga_ls8c_ard_3-2-1_113076_2023-08-22_final
2023-08-26 09:36:50	ga_ls8c_ard_3-2-1_093079_2023-08-26_final
2023-08-26 11:15:19	ga_ls8c_ard_3-2-1_109078_2023-08-26_final
2023-08-26 11:15:43	ga_ls8c_ard_3-2-1_109079_2023-08-26_final
2023-08-31 09:54:35	ga_ls8c_ard_3-2-1_096077_2023-08-31_final
2023-08-31 09:54:59	ga_ls8c_ard_3-2-1_096078_2023-08-31_final
2023-09-02 11:21:53	ga_ls8c_ard_3-2-1_110079_2023-09-02_final
2023-09-11 11:15:44	ga_ls8c_ard_3-2-1_109079_2023-09-11_final
2023-09-16 09:54:14	ga_ls8c_ard_3-2-1_096076_2023-09-16_final
2023-09-16 09:54:38	ga_ls8c_ard_3-2-1_096077_2023-09-16_final
2023-09-18 09:43:05	ga_ls8c_ard_3-2-1_094079_2023-09-18_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