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

84 results

Time (local)	Label
2023-07-12 10:02:39	ga_ls8c_ard_3-2-1_098067_2023-07-12_final
2023-07-12 10:03:03	ga_ls8c_ard_3-2-1_098068_2023-07-12_final
2023-07-12 10:03:27	ga_ls8c_ard_3-2-1_098069_2023-07-12_final
2023-07-12 10:03:51	ga_ls8c_ard_3-2-1_098070_2023-07-12_final
2023-07-12 10:04:15	ga_ls8c_ard_3-2-1_098071_2023-07-12_final
2023-07-12 10:04:39	ga_ls8c_ard_3-2-1_098072_2023-07-12_final
2023-07-12 10:05:03	ga_ls8c_ard_3-2-1_098073_2023-07-12_final
2023-07-12 10:05:26	ga_ls8c_ard_3-2-1_098074_2023-07-12_final
2023-07-12 10:05:50	ga_ls8c_ard_3-2-1_098075_2023-07-12_final
2023-07-12 10:06:14	ga_ls8c_ard_3-2-1_098076_2023-07-12_final
2023-07-12 10:06:38	ga_ls8c_ard_3-2-1_098077_2023-07-12_final
2023-07-12 10:07:02	ga_ls8c_ard_3-2-1_098078_2023-07-12_final
2023-07-12 10:07:50	ga_ls8c_ard_3-2-1_098080_2023-07-12_final
2023-07-12 10:08:14	ga_ls8c_ard_3-2-1_098081_2023-07-12_final
2023-07-12 10:08:38	ga_ls8c_ard_3-2-1_098082_2023-07-12_final
2023-07-12 10:09:02	ga_ls8c_ard_3-2-1_098083_2023-07-12_final
2023-07-12 10:09:26	ga_ls8c_ard_3-2-1_098084_2023-07-12_final
2023-07-12 11:44:20	ga_ls8c_ard_3-2-1_114074_2023-07-12_final
2023-07-12 11:44:43	ga_ls8c_ard_3-2-1_114075_2023-07-12_final
2023-07-12 11:45:07	ga_ls8c_ard_3-2-1_114076_2023-07-12_final
2023-07-12 11:45:31	ga_ls8c_ard_3-2-1_114077_2023-07-12_final
2023-07-12 11:45:55	ga_ls8c_ard_3-2-1_114078_2023-07-12_final
2023-07-12 11:46:19	ga_ls8c_ard_3-2-1_114079_2023-07-12_final
2023-07-12 11:46:43	ga_ls8c_ard_3-2-1_114080_2023-07-12_final
2023-07-12 11:47:07	ga_ls8c_ard_3-2-1_114081_2023-07-12_final
2023-07-13 09:09:49	ga_ls8c_ard_3-2-1_089074_2023-07-12_final
2023-07-13 09:10:13	ga_ls8c_ard_3-2-1_089075_2023-07-12_final
2023-07-13 09:10:37	ga_ls8c_ard_3-2-1_089076_2023-07-12_final
2023-07-13 09:11:01	ga_ls8c_ard_3-2-1_089077_2023-07-12_final
2023-07-13 09:11:25	ga_ls8c_ard_3-2-1_089078_2023-07-12_final
2023-07-13 09:11:49	ga_ls8c_ard_3-2-1_089079_2023-07-12_final
2023-07-13 09:12:13	ga_ls8c_ard_3-2-1_089080_2023-07-12_final
2023-07-13 09:12:37	ga_ls8c_ard_3-2-1_089081_2023-07-12_final
2023-07-13 09:13:01	ga_ls8c_ard_3-2-1_089082_2023-07-12_final
2023-07-13 09:13:25	ga_ls8c_ard_3-2-1_089083_2023-07-12_final
2023-07-13 09:13:49	ga_ls8c_ard_3-2-1_089084_2023-07-12_final
2023-07-13 09:14:13	ga_ls8c_ard_3-2-1_089085_2023-07-12_final
2023-07-13 09:14:37	ga_ls8c_ard_3-2-1_089086_2023-07-12_final
2023-07-13 09:15:49	ga_ls8c_ard_3-2-1_089089_2023-07-12_final
2023-07-13 09:16:13	ga_ls8c_ard_3-2-1_089090_2023-07-12_final
2023-07-13 10:45:55	ga_ls8c_ard_3-2-1_105067_2023-07-13_final
2023-07-13 10:46:19	ga_ls8c_ard_3-2-1_105068_2023-07-13_final
2023-07-13 10:46:43	ga_ls8c_ard_3-2-1_105069_2023-07-13_final
2023-07-13 10:47:07	ga_ls8c_ard_3-2-1_105070_2023-07-13_final
2023-07-13 10:47:31	ga_ls8c_ard_3-2-1_105071_2023-07-13_final
2023-07-13 10:47:54	ga_ls8c_ard_3-2-1_105072_2023-07-13_final
2023-07-13 10:48:18	ga_ls8c_ard_3-2-1_105073_2023-07-13_final
2023-07-13 10:48:42	ga_ls8c_ard_3-2-1_105074_2023-07-13_final
2023-07-13 10:49:06	ga_ls8c_ard_3-2-1_105075_2023-07-13_final
2023-07-13 10:49:30	ga_ls8c_ard_3-2-1_105076_2023-07-13_final
2023-07-13 10:49:54	ga_ls8c_ard_3-2-1_105077_2023-07-13_final
2023-07-13 10:50:18	ga_ls8c_ard_3-2-1_105078_2023-07-13_final
2023-07-13 10:50:42	ga_ls8c_ard_3-2-1_105079_2023-07-13_final
2023-07-13 10:51:06	ga_ls8c_ard_3-2-1_105080_2023-07-13_final
2023-07-13 10:51:30	ga_ls8c_ard_3-2-1_105081_2023-07-13_final
2023-07-13 10:52:18	ga_ls8c_ard_3-2-1_105083_2023-07-13_final
2023-07-14 09:51:29	ga_ls8c_ard_3-2-1_096070_2023-07-14_final
2023-07-14 09:51:53	ga_ls8c_ard_3-2-1_096071_2023-07-14_final
2023-07-14 09:52:17	ga_ls8c_ard_3-2-1_096072_2023-07-14_final
2023-07-14 09:52:41	ga_ls8c_ard_3-2-1_096073_2023-07-14_final
2023-07-14 09:53:05	ga_ls8c_ard_3-2-1_096074_2023-07-14_final
2023-07-14 09:53:29	ga_ls8c_ard_3-2-1_096075_2023-07-14_final
2023-07-14 09:53:53	ga_ls8c_ard_3-2-1_096076_2023-07-14_final
2023-07-14 09:54:17	ga_ls8c_ard_3-2-1_096077_2023-07-14_final
2023-07-14 09:55:29	ga_ls8c_ard_3-2-1_096080_2023-07-14_final
2023-07-14 09:55:53	ga_ls8c_ard_3-2-1_096081_2023-07-14_final
2023-07-14 09:56:17	ga_ls8c_ard_3-2-1_096082_2023-07-14_final
2023-07-14 09:56:41	ga_ls8c_ard_3-2-1_096083_2023-07-14_final
2023-07-14 09:57:05	ga_ls8c_ard_3-2-1_096084_2023-07-14_final
2023-07-14 09:57:29	ga_ls8c_ard_3-2-1_096085_2023-07-14_final
2023-07-14 09:57:53	ga_ls8c_ard_3-2-1_096086_2023-07-14_final
2023-07-14 11:31:10	ga_ls8c_ard_3-2-1_112072_2023-07-14_final
2023-07-14 11:31:34	ga_ls8c_ard_3-2-1_112073_2023-07-14_final
2023-07-14 11:31:58	ga_ls8c_ard_3-2-1_112074_2023-07-14_final
2023-07-14 11:32:22	ga_ls8c_ard_3-2-1_112075_2023-07-14_final
2023-07-14 11:32:46	ga_ls8c_ard_3-2-1_112076_2023-07-14_final
2023-07-14 11:33:10	ga_ls8c_ard_3-2-1_112077_2023-07-14_final
2023-07-14 11:33:34	ga_ls8c_ard_3-2-1_112078_2023-07-14_final
2023-07-14 11:33:58	ga_ls8c_ard_3-2-1_112079_2023-07-14_final
2023-07-14 11:34:22	ga_ls8c_ard_3-2-1_112080_2023-07-14_final
2023-07-14 11:34:46	ga_ls8c_ard_3-2-1_112081_2023-07-14_final
2023-07-14 11:35:10	ga_ls8c_ard_3-2-1_112082_2023-07-14_final
2023-07-14 11:35:34	ga_ls8c_ard_3-2-1_112083_2023-07-14_final
2023-07-14 11:35:58	ga_ls8c_ard_3-2-1_112084_2023-07-14_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years