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
2017-04-09 10:36:33	ga_ls8c_ard_3-0-0_103075_2017-04-09_final
2017-04-11 10:27:22	ga_ls8c_ard_3-0-0_101083_2017-04-11_final
2017-04-11 10:27:46	ga_ls8c_ard_3-0-0_101084_2017-04-11_final
2017-05-13 10:27:17	ga_ls8c_ard_3-0-0_101083_2017-05-13_final
2017-05-13 10:27:41	ga_ls8c_ard_3-0-0_101084_2017-05-13_final
2018-06-15 10:35:32	ga_ls8c_ard_3-0-0_103074_2018-06-15_final
2018-06-15 10:35:56	ga_ls8c_ard_3-0-0_103075_2018-06-15_final
2018-06-15 10:36:20	ga_ls8c_ard_3-0-0_103076_2018-06-15_final
2018-06-15 10:36:44	ga_ls8c_ard_3-0-0_103077_2018-06-15_final
2018-06-15 10:37:08	ga_ls8c_ard_3-0-0_103078_2018-06-15_final
2018-06-15 10:37:32	ga_ls8c_ard_3-0-0_103079_2018-06-15_final
2018-06-15 10:37:56	ga_ls8c_ard_3-0-0_103080_2018-06-15_final
2018-06-17 10:26:47	ga_ls8c_ard_3-0-0_101083_2018-06-17_final
2018-06-17 10:27:11	ga_ls8c_ard_3-0-0_101084_2018-06-17_final
2018-07-01 10:35:42	ga_ls8c_ard_3-0-0_103074_2018-07-01_final
2018-07-01 10:36:06	ga_ls8c_ard_3-0-0_103075_2018-07-01_final
2018-07-01 10:36:30	ga_ls8c_ard_3-0-0_103076_2018-07-01_final
2018-07-01 10:36:54	ga_ls8c_ard_3-0-0_103077_2018-07-01_final
2018-07-01 10:37:18	ga_ls8c_ard_3-0-0_103078_2018-07-01_final
2018-07-01 10:37:42	ga_ls8c_ard_3-0-0_103079_2018-07-01_final
2018-07-01 10:38:06	ga_ls8c_ard_3-0-0_103080_2018-07-01_final
2018-07-03 10:26:57	ga_ls8c_ard_3-0-0_101083_2018-07-03_final
2018-07-03 10:27:21	ga_ls8c_ard_3-0-0_101084_2018-07-03_final
2018-08-18 10:36:30	ga_ls8c_ard_3-0-0_103075_2018-08-18_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
2018-08-18 10:37:42	ga_ls8c_ard_3-0-0_103078_2018-08-18_final
2018-08-18 10:38:06	ga_ls8c_ard_3-0-0_103079_2018-08-18_final
2018-08-18 10:38:30	ga_ls8c_ard_3-0-0_103080_2018-08-18_final
2018-08-20 10:27:21	ga_ls8c_ard_3-0-0_101083_2018-08-20_final
2018-08-20 10:27:45	ga_ls8c_ard_3-0-0_101084_2018-08-20_final
2018-09-05 10:27:27	ga_ls8c_ard_3-0-0_101083_2018-09-05_final
2018-09-05 10:27:51	ga_ls8c_ard_3-0-0_101084_2018-09-05_final
2018-09-17 10:45:50	ga_ls8c_ard_3-0-0_105067_2018-09-17_final
2018-09-17 10:46:14	ga_ls8c_ard_3-0-0_105068_2018-09-17_final
2018-09-17 10:46:38	ga_ls8c_ard_3-0-0_105069_2018-09-17_final
2018-09-17 10:47:02	ga_ls8c_ard_3-0-0_105070_2018-09-17_final
2018-09-17 10:47:26	ga_ls8c_ard_3-0-0_105071_2018-09-17_final
2018-10-14 10:32:17	ga_ls8c_ard_3-0-0_102079_2018-10-14_final
2018-10-14 10:32:41	ga_ls8c_ard_3-0-0_102080_2018-10-14_final
2018-10-14 10:33:05	ga_ls8c_ard_3-0-0_102081_2018-10-14_final
2018-10-14 10:33:29	ga_ls8c_ard_3-0-0_102082_2018-10-14_final
2018-10-14 10:33:53	ga_ls8c_ard_3-0-0_102083_2018-10-14_final
2018-10-21 10:36:31	ga_ls8c_ard_3-0-0_103074_2018-10-21_final
2018-10-21 10:36:55	ga_ls8c_ard_3-0-0_103075_2018-10-21_final
2018-10-21 10:37:19	ga_ls8c_ard_3-0-0_103076_2018-10-21_final
2018-10-21 10:37:43	ga_ls8c_ard_3-0-0_103077_2018-10-21_final
2018-10-21 10:38:07	ga_ls8c_ard_3-0-0_103078_2018-10-21_final
2018-10-21 10:38:31	ga_ls8c_ard_3-0-0_103079_2018-10-21_final
2018-10-21 10:38:54	ga_ls8c_ard_3-0-0_103080_2018-10-21_final
2018-10-23 10:27:45	ga_ls8c_ard_3-0-0_101083_2018-10-23_final
2018-10-23 10:28:09	ga_ls8c_ard_3-0-0_101084_2018-10-23_final
2018-11-08 10:27:48	ga_ls8c_ard_3-0-0_101083_2018-11-08_final
2018-11-08 10:28:12	ga_ls8c_ard_3-0-0_101084_2018-11-08_final
2018-11-13 10:41:10	ga_ls8c_ard_3-0-0_104070_2018-11-13_final
2018-11-13 10:41:34	ga_ls8c_ard_3-0-0_104071_2018-11-13_final
2018-11-13 10:41:58	ga_ls8c_ard_3-0-0_104072_2018-11-13_final
2018-11-13 10:42:22	ga_ls8c_ard_3-0-0_104073_2018-11-13_final
2018-11-13 10:42:46	ga_ls8c_ard_3-0-0_104074_2018-11-13_final
2018-11-13 10:43:09	ga_ls8c_ard_3-0-0_104075_2018-11-13_final
2018-12-24 10:36:55	ga_ls8c_ard_3-0-0_103075_2018-12-24_final
2018-12-24 10:37:19	ga_ls8c_ard_3-0-0_103076_2018-12-24_final
2018-12-24 10:37:43	ga_ls8c_ard_3-0-0_103077_2018-12-24_final
2018-12-24 10:38:07	ga_ls8c_ard_3-0-0_103078_2018-12-24_final
2018-12-24 10:38:31	ga_ls8c_ard_3-0-0_103079_2018-12-24_final
2018-12-24 10:38:55	ga_ls8c_ard_3-0-0_103080_2018-12-24_final
2018-12-26 10:27:45	ga_ls8c_ard_3-0-0_101083_2018-12-26_final
2018-12-26 10:28:09	ga_ls8c_ard_3-0-0_101084_2018-12-26_final
2019-01-07 10:46:04	ga_ls8c_ard_3-0-0_105067_2019-01-07_final
2019-01-07 10:46:28	ga_ls8c_ard_3-0-0_105068_2019-01-07_final
2019-01-07 10:46:52	ga_ls8c_ard_3-0-0_105069_2019-01-07_final
2019-01-07 10:47:16	ga_ls8c_ard_3-0-0_105070_2019-01-07_final
2019-01-07 10:47:40	ga_ls8c_ard_3-0-0_105071_2019-01-07_final
2023-08-23 10:41:13	ga_ls8c_ard_3-2-1_104070_2023-08-23_final
2023-08-23 10:41:37	ga_ls8c_ard_3-2-1_104071_2023-08-23_final
2023-08-23 10:42:01	ga_ls8c_ard_3-2-1_104072_2023-08-23_final
2023-08-23 10:42:25	ga_ls8c_ard_3-2-1_104073_2023-08-23_final
2023-08-23 10:42:49	ga_ls8c_ard_3-2-1_104074_2023-08-23_final
2023-08-23 10:43:13	ga_ls8c_ard_3-2-1_104075_2023-08-23_final
2023-08-25 10:32:27	ga_ls8c_ard_3-2-1_102079_2023-08-25_final
2023-08-25 10:32:51	ga_ls8c_ard_3-2-1_102080_2023-08-25_final
2023-08-25 10:33:15	ga_ls8c_ard_3-2-1_102081_2023-08-25_final
2023-08-25 10:33:39	ga_ls8c_ard_3-2-1_102082_2023-08-25_final
2023-09-01 10:36:38	ga_ls8c_ard_3-2-1_103074_2023-09-01_final
2023-09-01 10:37:02	ga_ls8c_ard_3-2-1_103075_2023-09-01_final
2023-09-01 10:37:26	ga_ls8c_ard_3-2-1_103076_2023-09-01_final
2023-09-01 10:37:50	ga_ls8c_ard_3-2-1_103077_2023-09-01_final
2023-09-01 10:38:14	ga_ls8c_ard_3-2-1_103078_2023-09-01_final
2023-09-01 10:38:38	ga_ls8c_ard_3-2-1_103079_2023-09-01_final
2023-09-01 10:39:02	ga_ls8c_ard_3-2-1_103080_2023-09-01_final
2023-09-03 10:27:52	ga_ls8c_ard_3-2-1_101083_2023-09-03_final
2023-09-08 10:41:12	ga_ls8c_ard_3-2-1_104070_2023-09-08_final
2023-09-08 10:41:36	ga_ls8c_ard_3-2-1_104071_2023-09-08_final
2023-09-08 10:42:00	ga_ls8c_ard_3-2-1_104072_2023-09-08_final
2023-09-08 10:42:24	ga_ls8c_ard_3-2-1_104073_2023-09-08_final
2023-09-08 10:42:48	ga_ls8c_ard_3-2-1_104074_2023-09-08_final
2023-09-08 10:43:12	ga_ls8c_ard_3-2-1_104075_2023-09-08_final
2023-09-10 10:32:28	ga_ls8c_ard_3-2-1_102079_2023-09-10_final
2023-09-10 10:32:52	ga_ls8c_ard_3-2-1_102080_2023-09-10_final
2023-09-10 10:33:16	ga_ls8c_ard_3-2-1_102081_2023-09-10_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