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 09:53:38	ga_ls8c_ard_3-0-0_096076_2018-08-17_final
2018-08-17 09:54:01	ga_ls8c_ard_3-0-0_096077_2018-08-17_final
2018-08-17 11:32:31	ga_ls8c_ard_3-0-0_112076_2018-08-17_final
2018-08-17 11:32:55	ga_ls8c_ard_3-0-0_112077_2018-08-17_final
2018-08-18 10:36:54	ga_ls8c_ard_3-0-0_103076_2018-08-18_final
2018-08-18 10:37:18	ga_ls8c_ard_3-0-0_103077_2018-08-18_final
2018-08-19 09:41:17	ga_ls8c_ard_3-0-0_094076_2018-08-19_final
2018-08-19 09:41:41	ga_ls8c_ard_3-0-0_094077_2018-08-19_final
2018-08-19 11:20:10	ga_ls8c_ard_3-0-0_110076_2018-08-19_final
2018-08-19 11:20:34	ga_ls8c_ard_3-0-0_110077_2018-08-19_final
2018-08-20 10:24:33	ga_ls8c_ard_3-0-0_101076_2018-08-20_final
2018-08-20 10:24:57	ga_ls8c_ard_3-0-0_101077_2018-08-20_final
2018-09-02 09:53:44	ga_ls8c_ard_3-0-0_096076_2018-09-02_final
2018-09-02 09:54:08	ga_ls8c_ard_3-0-0_096077_2018-09-02_final
2018-09-02 11:32:37	ga_ls8c_ard_3-0-0_112076_2018-09-02_final
2018-09-02 11:33:01	ga_ls8c_ard_3-0-0_112077_2018-09-02_final
2018-09-03 10:37:24	ga_ls8c_ard_3-0-0_103077_2018-09-03_final
2018-09-04 09:41:23	ga_ls8c_ard_3-0-0_094076_2018-09-04_final
2018-09-04 09:41:47	ga_ls8c_ard_3-0-0_094077_2018-09-04_final
2018-09-04 11:20:16	ga_ls8c_ard_3-0-0_110076_2018-09-04_final
2018-09-04 11:20:40	ga_ls8c_ard_3-0-0_110077_2018-09-04_final
2018-09-05 10:24:39	ga_ls8c_ard_3-0-0_101076_2018-09-05_final
2018-09-05 10:25:03	ga_ls8c_ard_3-0-0_101077_2018-09-05_final
2018-09-16 10:06:10	ga_ls8c_ard_3-0-0_098076_2018-09-16_final
2018-09-16 10:06:34	ga_ls8c_ard_3-0-0_098077_2018-09-16_final
2018-09-16 11:45:03	ga_ls8c_ard_3-0-0_114076_2018-09-16_final
2018-09-16 11:45:27	ga_ls8c_ard_3-0-0_114077_2018-09-16_final
2018-09-17 09:10:33	ga_ls8c_ard_3-0-0_089076_2018-09-16_final
2018-09-17 09:10:57	ga_ls8c_ard_3-0-0_089077_2018-09-16_final
2018-09-17 10:49:26	ga_ls8c_ard_3-0-0_105076_2018-09-17_final
2018-09-17 10:49:50	ga_ls8c_ard_3-0-0_105077_2018-09-17_final
2019-01-06 10:06:24	ga_ls8c_ard_3-0-0_098076_2019-01-06_final
2019-01-06 10:06:48	ga_ls8c_ard_3-0-0_098077_2019-01-06_final
2019-01-06 11:45:41	ga_ls8c_ard_3-0-0_114077_2019-01-06_final
2019-01-07 09:10:47	ga_ls8c_ard_3-0-0_089076_2019-01-06_final
2019-01-07 09:11:11	ga_ls8c_ard_3-0-0_089077_2019-01-06_final
2019-01-07 10:50:04	ga_ls8c_ard_3-0-0_105077_2019-01-07_final
2023-03-23 10:50:03	ga_ls8c_ard_3-2-1_105077_2023-03-23_final
2023-03-24 09:54:25	ga_ls8c_ard_3-2-1_096077_2023-03-24_final
2023-03-24 11:33:18	ga_ls8c_ard_3-2-1_112077_2023-03-24_final
2023-03-25 10:37:40	ga_ls8c_ard_3-2-1_103077_2023-03-25_final
2023-03-26 09:42:03	ga_ls8c_ard_3-2-1_094077_2023-03-26_final
2023-03-26 11:20:56	ga_ls8c_ard_3-2-1_110077_2023-03-26_final
2023-03-29 10:12:32	ga_ls8c_ard_3-2-1_099076_2023-03-29_final
2023-03-29 10:12:56	ga_ls8c_ard_3-2-1_099077_2023-03-29_final
2023-03-29 11:51:25	ga_ls8c_ard_3-2-1_115076_2023-03-29_final
2023-03-29 11:51:49	ga_ls8c_ard_3-2-1_115077_2023-03-29_final
2023-03-30 09:16:54	ga_ls8c_ard_3-2-1_090076_2023-03-29_final
2023-03-30 09:17:18	ga_ls8c_ard_3-2-1_090077_2023-03-29_final
2023-03-30 10:56:11	ga_ls8c_ard_3-2-1_106077_2023-03-30_final
2023-03-31 10:00:33	ga_ls8c_ard_3-2-1_097077_2023-03-31_final
2023-03-31 11:39:26	ga_ls8c_ard_3-2-1_113077_2023-03-31_final
2023-04-04 11:14:39	ga_ls8c_ard_3-2-1_109077_2023-04-04_final
2023-04-06 11:02:14	ga_ls8c_ard_3-2-1_107077_2023-04-06_final
2023-04-08 10:49:50	ga_ls8c_ard_3-2-1_105077_2023-04-08_final
2023-04-09 09:54:11	ga_ls8c_ard_3-2-1_096077_2023-04-09_final
2023-04-14 10:12:17	ga_ls8c_ard_3-2-1_099076_2023-04-14_final
2023-04-14 10:12:40	ga_ls8c_ard_3-2-1_099077_2023-04-14_final
2023-04-14 11:51:34	ga_ls8c_ard_3-2-1_115077_2023-04-14_final
2023-04-15 09:17:03	ga_ls8c_ard_3-2-1_090077_2023-04-14_final
2023-04-15 10:55:56	ga_ls8c_ard_3-2-1_106077_2023-04-15_final
2023-04-20 11:14:26	ga_ls8c_ard_3-2-1_109077_2023-04-20_final
2023-04-21 10:18:49	ga_ls8c_ard_3-2-1_100077_2023-04-21_final
2023-04-21 11:57:42	ga_ls8c_ard_3-2-1_116077_2023-04-21_final
2023-04-24 09:10:50	ga_ls8c_ard_3-2-1_089077_2023-04-23_final
2023-04-24 10:49:43	ga_ls8c_ard_3-2-1_105077_2023-04-24_final
2023-04-25 09:54:06	ga_ls8c_ard_3-2-1_096077_2023-04-25_final
2023-04-27 09:41:43	ga_ls8c_ard_3-2-1_094077_2023-04-27_final
2023-04-27 11:20:36	ga_ls8c_ard_3-2-1_110077_2023-04-27_final
2023-04-28 10:24:59	ga_ls8c_ard_3-2-1_101077_2023-04-28_final
2023-05-01 10:55:51	ga_ls8c_ard_3-2-1_106077_2023-05-01_final
2023-05-02 10:00:13	ga_ls8c_ard_3-2-1_097077_2023-05-02_final
2023-05-02 11:39:06	ga_ls8c_ard_3-2-1_113077_2023-05-02_final
2023-05-04 09:47:50	ga_ls8c_ard_3-2-1_095077_2023-05-04_final
2023-05-04 11:26:43	ga_ls8c_ard_3-2-1_111077_2023-05-04_final
2023-05-05 10:31:05	ga_ls8c_ard_3-2-1_102077_2023-05-05_final
2023-05-08 09:23:03	ga_ls8c_ard_3-2-1_091077_2023-05-07_final
2023-07-18 11:08:03	ga_ls8c_ard_3-2-1_108076_2023-07-18_final
2023-07-18 11:08:27	ga_ls8c_ard_3-2-1_108077_2023-07-18_final
2023-07-19 10:12:49	ga_ls8c_ard_3-2-1_099077_2023-07-19_final
2023-07-19 11:51:18	ga_ls8c_ard_3-2-1_115076_2023-07-19_final
2023-07-19 11:51:42	ga_ls8c_ard_3-2-1_115077_2023-07-19_final
2023-07-20 09:16:48	ga_ls8c_ard_3-2-1_090076_2023-07-19_final
2023-07-20 09:17:12	ga_ls8c_ard_3-2-1_090077_2023-07-19_final
2023-07-21 10:00:04	ga_ls8c_ard_3-2-1_097076_2023-07-21_final
2023-07-21 10:00:27	ga_ls8c_ard_3-2-1_097077_2023-07-21_final
2023-07-21 11:38:57	ga_ls8c_ard_3-2-1_113076_2023-07-21_final
2023-07-21 11:39:21	ga_ls8c_ard_3-2-1_113077_2023-07-21_final
2023-07-22 10:43:20	ga_ls8c_ard_3-2-1_104076_2023-07-22_final
2023-07-22 10:43:44	ga_ls8c_ard_3-2-1_104077_2023-07-22_final
2023-07-23 09:47:44	ga_ls8c_ard_3-2-1_095076_2023-07-23_final
2023-07-23 09:48:08	ga_ls8c_ard_3-2-1_095077_2023-07-23_final
2023-07-23 11:27:01	ga_ls8c_ard_3-2-1_111077_2023-07-23_final
2023-07-26 10:18:41	ga_ls8c_ard_3-2-1_100076_2023-07-26_final
2023-07-26 10:19:05	ga_ls8c_ard_3-2-1_100077_2023-07-26_final
2023-07-26 11:57:34	ga_ls8c_ard_3-2-1_116076_2023-07-26_final
2023-07-26 11:57:58	ga_ls8c_ard_3-2-1_116077_2023-07-26_final
2023-07-27 09:23:04	ga_ls8c_ard_3-2-1_091076_2023-07-26_final
2023-07-27 09:23:28	ga_ls8c_ard_3-2-1_091077_2023-07-26_final
2023-07-27 11:01:57	ga_ls8c_ard_3-2-1_107076_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