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

96 results

Time (local)	Label
2022-04-02 10:16:38	ga_ls8c_ard_3-2-1_100071_2022-04-02_final
2022-04-02 10:17:02	ga_ls8c_ard_3-2-1_100072_2022-04-02_final
2022-04-02 10:18:14	ga_ls8c_ard_3-2-1_100075_2022-04-02_final
2022-04-02 10:18:38	ga_ls8c_ard_3-2-1_100076_2022-04-02_final
2022-04-02 10:19:02	ga_ls8c_ard_3-2-1_100077_2022-04-02_final
2022-04-02 10:19:50	ga_ls8c_ard_3-2-1_100079_2022-04-02_final
2022-04-03 09:21:25	ga_ls8c_ard_3-2-1_091072_2022-04-02_final
2022-04-03 09:21:49	ga_ls8c_ard_3-2-1_091073_2022-04-02_final
2022-04-03 09:22:13	ga_ls8c_ard_3-2-1_091074_2022-04-02_final
2022-04-03 09:22:37	ga_ls8c_ard_3-2-1_091075_2022-04-02_final
2022-04-03 09:23:01	ga_ls8c_ard_3-2-1_091076_2022-04-02_final
2022-04-03 09:23:49	ga_ls8c_ard_3-2-1_091078_2022-04-02_final
2022-04-03 09:24:13	ga_ls8c_ard_3-2-1_091079_2022-04-02_final
2022-04-03 09:26:12	ga_ls8c_ard_3-2-1_091084_2022-04-02_final
2022-04-03 09:27:24	ga_ls8c_ard_3-2-1_091087_2022-04-02_final
2022-04-03 09:28:36	ga_ls8c_ard_3-2-1_091090_2022-04-02_final
2022-04-03 11:00:18	ga_ls8c_ard_3-2-1_107072_2022-04-03_final
2022-04-03 11:05:05	ga_ls8c_ard_3-2-1_107084_2022-04-03_final
2022-04-04 10:03:06	ga_ls8c_ard_3-2-1_098068_2022-04-04_final
2022-04-04 10:04:42	ga_ls8c_ard_3-2-1_098072_2022-04-04_final
2022-04-04 10:05:05	ga_ls8c_ard_3-2-1_098073_2022-04-04_final
2022-04-04 10:06:17	ga_ls8c_ard_3-2-1_098076_2022-04-04_final
2022-04-04 10:07:05	ga_ls8c_ard_3-2-1_098078_2022-04-04_final
2022-04-04 10:08:17	ga_ls8c_ard_3-2-1_098081_2022-04-04_final
2022-04-04 10:09:53	ga_ls8c_ard_3-2-1_098085_2022-04-04_final
2022-04-04 11:45:58	ga_ls8c_ard_3-2-1_114078_2022-04-04_final
2022-04-04 11:46:46	ga_ls8c_ard_3-2-1_114080_2022-04-04_final
2022-04-05 09:09:53	ga_ls8c_ard_3-2-1_089074_2022-04-04_final
2022-04-05 09:10:17	ga_ls8c_ard_3-2-1_089075_2022-04-04_final
2022-04-05 09:10:41	ga_ls8c_ard_3-2-1_089076_2022-04-04_final
2022-04-05 09:14:40	ga_ls8c_ard_3-2-1_089086_2022-04-04_final
2022-04-05 10:46:46	ga_ls8c_ard_3-2-1_105069_2022-04-05_final
2022-04-05 10:49:10	ga_ls8c_ard_3-2-1_105075_2022-04-05_final
2022-04-05 10:49:58	ga_ls8c_ard_3-2-1_105077_2022-04-05_final
2022-04-05 10:50:22	ga_ls8c_ard_3-2-1_105078_2022-04-05_final
2022-04-05 10:50:46	ga_ls8c_ard_3-2-1_105079_2022-04-05_final
2022-04-05 10:51:57	ga_ls8c_ard_3-2-1_105082_2022-04-05_final
2022-04-05 10:52:21	ga_ls8c_ard_3-2-1_105083_2022-04-05_final
2022-04-06 09:51:33	ga_ls8c_ard_3-2-1_096070_2022-04-06_final
2022-04-06 09:51:57	ga_ls8c_ard_3-2-1_096071_2022-04-06_final
2022-04-06 09:52:21	ga_ls8c_ard_3-2-1_096072_2022-04-06_final
2022-04-06 09:52:45	ga_ls8c_ard_3-2-1_096073_2022-04-06_final
2022-04-06 09:53:09	ga_ls8c_ard_3-2-1_096074_2022-04-06_final
2022-04-06 09:53:33	ga_ls8c_ard_3-2-1_096075_2022-04-06_final
2022-04-06 09:53:57	ga_ls8c_ard_3-2-1_096076_2022-04-06_final
2022-04-06 09:54:21	ga_ls8c_ard_3-2-1_096077_2022-04-06_final
2022-04-06 09:54:45	ga_ls8c_ard_3-2-1_096078_2022-04-06_final
2022-04-06 09:55:09	ga_ls8c_ard_3-2-1_096079_2022-04-06_final
2022-04-06 09:55:33	ga_ls8c_ard_3-2-1_096080_2022-04-06_final
2022-04-06 09:55:57	ga_ls8c_ard_3-2-1_096081_2022-04-06_final
2022-04-06 09:56:21	ga_ls8c_ard_3-2-1_096082_2022-04-06_final
2022-04-06 09:56:45	ga_ls8c_ard_3-2-1_096083_2022-04-06_final
2022-04-06 09:57:09	ga_ls8c_ard_3-2-1_096084_2022-04-06_final
2022-04-06 09:57:33	ga_ls8c_ard_3-2-1_096085_2022-04-06_final
2022-04-06 09:57:57	ga_ls8c_ard_3-2-1_096086_2022-04-06_final
2022-04-06 11:32:26	ga_ls8c_ard_3-2-1_112075_2022-04-06_final
2022-04-06 11:32:50	ga_ls8c_ard_3-2-1_112076_2022-04-06_final
2022-04-06 11:33:14	ga_ls8c_ard_3-2-1_112077_2022-04-06_final
2022-04-06 11:33:38	ga_ls8c_ard_3-2-1_112078_2022-04-06_final
2022-04-06 11:34:02	ga_ls8c_ard_3-2-1_112079_2022-04-06_final
2022-04-06 11:34:50	ga_ls8c_ard_3-2-1_112081_2022-04-06_final
2022-04-06 11:35:14	ga_ls8c_ard_3-2-1_112082_2022-04-06_final
2022-04-06 11:35:38	ga_ls8c_ard_3-2-1_112083_2022-04-06_final
2022-04-07 10:34:26	ga_ls8c_ard_3-2-1_103069_2022-04-07_final
2022-04-07 10:34:50	ga_ls8c_ard_3-2-1_103070_2022-04-07_final
2022-04-07 10:35:14	ga_ls8c_ard_3-2-1_103071_2022-04-07_final
2022-04-07 10:36:02	ga_ls8c_ard_3-2-1_103073_2022-04-07_final
2022-04-07 10:36:26	ga_ls8c_ard_3-2-1_103074_2022-04-07_final
2022-04-07 10:37:13	ga_ls8c_ard_3-2-1_103076_2022-04-07_final
2022-04-07 10:37:37	ga_ls8c_ard_3-2-1_103077_2022-04-07_final
2022-04-07 10:38:01	ga_ls8c_ard_3-2-1_103078_2022-04-07_final
2022-04-07 10:38:25	ga_ls8c_ard_3-2-1_103079_2022-04-07_final
2022-04-07 10:38:49	ga_ls8c_ard_3-2-1_103080_2022-04-07_final
2022-04-07 10:39:13	ga_ls8c_ard_3-2-1_103081_2022-04-07_final
2022-04-08 09:39:37	ga_ls8c_ard_3-2-1_094071_2022-04-08_final
2022-04-08 09:40:25	ga_ls8c_ard_3-2-1_094073_2022-04-08_final
2022-04-08 09:41:37	ga_ls8c_ard_3-2-1_094076_2022-04-08_final
2022-04-08 09:42:01	ga_ls8c_ard_3-2-1_094077_2022-04-08_final
2022-04-08 09:42:25	ga_ls8c_ard_3-2-1_094078_2022-04-08_final
2022-04-08 09:42:49	ga_ls8c_ard_3-2-1_094079_2022-04-08_final
2022-04-08 09:43:12	ga_ls8c_ard_3-2-1_094080_2022-04-08_final
2022-04-08 09:44:24	ga_ls8c_ard_3-2-1_094083_2022-04-08_final
2022-04-08 09:44:48	ga_ls8c_ard_3-2-1_094084_2022-04-08_final
2022-04-08 09:45:12	ga_ls8c_ard_3-2-1_094085_2022-04-08_final
2022-04-08 09:45:36	ga_ls8c_ard_3-2-1_094086_2022-04-08_final
2022-04-08 09:46:00	ga_ls8c_ard_3-2-1_094087_2022-04-08_final
2022-04-08 11:18:06	ga_ls8c_ard_3-2-1_110070_2022-04-08_final
2022-04-08 11:19:18	ga_ls8c_ard_3-2-1_110073_2022-04-08_final
2022-04-08 11:20:06	ga_ls8c_ard_3-2-1_110075_2022-04-08_final
2022-04-08 11:20:30	ga_ls8c_ard_3-2-1_110076_2022-04-08_final
2022-04-08 11:21:42	ga_ls8c_ard_3-2-1_110079_2022-04-08_final
2022-04-08 11:22:06	ga_ls8c_ard_3-2-1_110080_2022-04-08_final
2022-04-08 11:22:30	ga_ls8c_ard_3-2-1_110081_2022-04-08_final
2022-04-08 11:22:53	ga_ls8c_ard_3-2-1_110082_2022-04-08_final
2022-04-08 11:23:17	ga_ls8c_ard_3-2-1_110083_2022-04-08_final
2022-04-08 11:23:41	ga_ls8c_ard_3-2-1_110084_2022-04-08_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