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
2018-08-17 09:54:01	ga_ls8c_ard_3-0-0_096077_2018-08-17_final
2018-08-17 09:54:25	ga_ls8c_ard_3-0-0_096078_2018-08-17_final
2018-08-17 11:32:55	ga_ls8c_ard_3-0-0_112077_2018-08-17_final
2018-08-17 11:33:19	ga_ls8c_ard_3-0-0_112078_2018-08-17_final
2018-08-18 10:37:18	ga_ls8c_ard_3-0-0_103077_2018-08-18_final
2018-08-18 10:37:42	ga_ls8c_ard_3-0-0_103078_2018-08-18_final
2018-08-19 09:41:41	ga_ls8c_ard_3-0-0_094077_2018-08-19_final
2018-08-19 09:42:05	ga_ls8c_ard_3-0-0_094078_2018-08-19_final
2018-08-19 11:20:34	ga_ls8c_ard_3-0-0_110077_2018-08-19_final
2018-08-19 11:20:58	ga_ls8c_ard_3-0-0_110078_2018-08-19_final
2018-08-20 10:24:57	ga_ls8c_ard_3-0-0_101077_2018-08-20_final
2018-08-20 10:25:21	ga_ls8c_ard_3-0-0_101078_2018-08-20_final
2018-09-02 09:54:08	ga_ls8c_ard_3-0-0_096077_2018-09-02_final
2018-09-02 09:54:32	ga_ls8c_ard_3-0-0_096078_2018-09-02_final
2018-09-02 11:33:01	ga_ls8c_ard_3-0-0_112077_2018-09-02_final
2018-09-02 11:33:25	ga_ls8c_ard_3-0-0_112078_2018-09-02_final
2018-09-03 10:37:24	ga_ls8c_ard_3-0-0_103077_2018-09-03_final
2018-09-03 10:37:48	ga_ls8c_ard_3-0-0_103078_2018-09-03_final
2018-09-04 09:41:47	ga_ls8c_ard_3-0-0_094077_2018-09-04_final
2018-09-04 09:42:11	ga_ls8c_ard_3-0-0_094078_2018-09-04_final
2018-09-04 11:20:40	ga_ls8c_ard_3-0-0_110077_2018-09-04_final
2018-09-04 11:21:04	ga_ls8c_ard_3-0-0_110078_2018-09-04_final
2018-09-05 10:25:03	ga_ls8c_ard_3-0-0_101077_2018-09-05_final
2018-09-05 10:25:27	ga_ls8c_ard_3-0-0_101078_2018-09-05_final
2018-09-16 10:06:34	ga_ls8c_ard_3-0-0_098077_2018-09-16_final
2018-09-16 10:06:58	ga_ls8c_ard_3-0-0_098078_2018-09-16_final
2018-09-16 11:45:27	ga_ls8c_ard_3-0-0_114077_2018-09-16_final
2018-09-16 11:45:51	ga_ls8c_ard_3-0-0_114078_2018-09-16_final
2018-09-17 09:10:57	ga_ls8c_ard_3-0-0_089077_2018-09-16_final
2018-09-17 09:11:21	ga_ls8c_ard_3-0-0_089078_2018-09-16_final
2018-09-17 10:49:50	ga_ls8c_ard_3-0-0_105077_2018-09-17_final
2018-09-17 10:50:14	ga_ls8c_ard_3-0-0_105078_2018-09-17_final
2019-01-06 10:06:48	ga_ls8c_ard_3-0-0_098077_2019-01-06_final
2019-01-06 10:07:12	ga_ls8c_ard_3-0-0_098078_2019-01-06_final
2019-01-06 11:45:41	ga_ls8c_ard_3-0-0_114077_2019-01-06_final
2019-01-06 11:46:05	ga_ls8c_ard_3-0-0_114078_2019-01-06_final
2019-01-07 09:11:11	ga_ls8c_ard_3-0-0_089077_2019-01-06_final
2019-01-07 09:11:35	ga_ls8c_ard_3-0-0_089078_2019-01-06_final
2019-01-07 10:50:04	ga_ls8c_ard_3-0-0_105077_2019-01-07_final
2019-01-07 10:50:28	ga_ls8c_ard_3-0-0_105078_2019-01-07_final
2023-03-23 10:50:27	ga_ls8c_ard_3-2-1_105078_2023-03-23_final
2023-03-24 09:54:49	ga_ls8c_ard_3-2-1_096078_2023-03-24_final
2023-03-24 11:33:18	ga_ls8c_ard_3-2-1_112077_2023-03-24_final
2023-03-24 11:33:42	ga_ls8c_ard_3-2-1_112078_2023-03-24_final
2023-03-25 10:38:04	ga_ls8c_ard_3-2-1_103078_2023-03-25_final
2023-03-26 09:42:03	ga_ls8c_ard_3-2-1_094077_2023-03-26_final
2023-03-26 09:42:27	ga_ls8c_ard_3-2-1_094078_2023-03-26_final
2023-03-26 11:21:20	ga_ls8c_ard_3-2-1_110078_2023-03-26_final
2023-03-29 10:12:56	ga_ls8c_ard_3-2-1_099077_2023-03-29_final
2023-03-29 10:13:20	ga_ls8c_ard_3-2-1_099078_2023-03-29_final
2023-03-29 11:51:49	ga_ls8c_ard_3-2-1_115077_2023-03-29_final
2023-03-29 11:52:13	ga_ls8c_ard_3-2-1_115078_2023-03-29_final
2023-03-30 09:17:18	ga_ls8c_ard_3-2-1_090077_2023-03-29_final
2023-03-30 09:17:42	ga_ls8c_ard_3-2-1_090078_2023-03-29_final
2023-03-30 10:56:11	ga_ls8c_ard_3-2-1_106077_2023-03-30_final
2023-03-30 10:56:35	ga_ls8c_ard_3-2-1_106078_2023-03-30_final
2023-03-31 10:00:33	ga_ls8c_ard_3-2-1_097077_2023-03-31_final
2023-03-31 10:00:57	ga_ls8c_ard_3-2-1_097078_2023-03-31_final
2023-03-31 11:39:26	ga_ls8c_ard_3-2-1_113077_2023-03-31_final
2023-03-31 11:39:50	ga_ls8c_ard_3-2-1_113078_2023-03-31_final
2023-04-04 11:14:39	ga_ls8c_ard_3-2-1_109077_2023-04-04_final
2023-04-04 11:15:03	ga_ls8c_ard_3-2-1_109078_2023-04-04_final
2023-04-06 11:02:14	ga_ls8c_ard_3-2-1_107077_2023-04-06_final
2023-04-06 11:02:38	ga_ls8c_ard_3-2-1_107078_2023-04-06_final
2023-04-08 10:50:14	ga_ls8c_ard_3-2-1_105078_2023-04-08_final
2023-04-09 09:54:35	ga_ls8c_ard_3-2-1_096078_2023-04-09_final
2023-04-14 10:13:04	ga_ls8c_ard_3-2-1_099078_2023-04-14_final
2023-04-14 11:51:34	ga_ls8c_ard_3-2-1_115077_2023-04-14_final
2023-04-14 11:51:57	ga_ls8c_ard_3-2-1_115078_2023-04-14_final
2023-04-15 09:17:03	ga_ls8c_ard_3-2-1_090077_2023-04-14_final
2023-04-15 09:17:27	ga_ls8c_ard_3-2-1_090078_2023-04-14_final
2023-04-15 10:55:56	ga_ls8c_ard_3-2-1_106077_2023-04-15_final
2023-04-15 10:56:20	ga_ls8c_ard_3-2-1_106078_2023-04-15_final
2023-04-20 11:14:50	ga_ls8c_ard_3-2-1_109078_2023-04-20_final
2023-04-21 10:19:13	ga_ls8c_ard_3-2-1_100078_2023-04-21_final
2023-04-21 11:58:06	ga_ls8c_ard_3-2-1_116078_2023-04-21_final
2023-04-24 09:10:50	ga_ls8c_ard_3-2-1_089077_2023-04-23_final
2023-04-24 09:11:14	ga_ls8c_ard_3-2-1_089078_2023-04-23_final
2023-04-24 10:50:07	ga_ls8c_ard_3-2-1_105078_2023-04-24_final
2023-04-25 09:54:06	ga_ls8c_ard_3-2-1_096077_2023-04-25_final
2023-04-25 09:54:30	ga_ls8c_ard_3-2-1_096078_2023-04-25_final
2023-04-26 10:37:45	ga_ls8c_ard_3-2-1_103078_2023-04-26_final
2023-04-27 11:20:36	ga_ls8c_ard_3-2-1_110077_2023-04-27_final
2023-04-27 11:21:00	ga_ls8c_ard_3-2-1_110078_2023-04-27_final
2023-04-28 10:24:59	ga_ls8c_ard_3-2-1_101077_2023-04-28_final
2023-04-28 10:25:23	ga_ls8c_ard_3-2-1_101078_2023-04-28_final
2023-05-01 10:56:15	ga_ls8c_ard_3-2-1_106078_2023-05-01_final
2023-05-02 10:00:13	ga_ls8c_ard_3-2-1_097077_2023-05-02_final
2023-05-02 10:00:37	ga_ls8c_ard_3-2-1_097078_2023-05-02_final
2023-05-02 11:39:30	ga_ls8c_ard_3-2-1_113078_2023-05-02_final
2023-05-07 11:57:59	ga_ls8c_ard_3-2-1_116078_2023-05-07_final
2023-05-08 09:23:03	ga_ls8c_ard_3-2-1_091077_2023-05-07_final
2023-05-08 09:23:27	ga_ls8c_ard_3-2-1_091078_2023-05-07_final
2023-07-26 10:19:05	ga_ls8c_ard_3-2-1_100077_2023-07-26_final
2023-07-26 10:19:29	ga_ls8c_ard_3-2-1_100078_2023-07-26_final
2023-07-26 11:57:58	ga_ls8c_ard_3-2-1_116077_2023-07-26_final
2023-07-26 11:58:22	ga_ls8c_ard_3-2-1_116078_2023-07-26_final
2023-07-27 09:23:28	ga_ls8c_ard_3-2-1_091077_2023-07-26_final
2023-07-27 09:23:52	ga_ls8c_ard_3-2-1_091078_2023-07-26_final
2023-07-27 11:02:21	ga_ls8c_ard_3-2-1_107077_2023-07-27_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