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

60 results

Time (local)	Label
2023-05-06 09:33:03	ga_ls8c_ard_3-2-1_093071_2023-05-06_final
2023-05-06 09:33:27	ga_ls8c_ard_3-2-1_093072_2023-05-06_final
2023-05-06 09:33:51	ga_ls8c_ard_3-2-1_093073_2023-05-06_final
2023-05-06 09:34:39	ga_ls8c_ard_3-2-1_093075_2023-05-06_final
2023-05-06 09:35:51	ga_ls8c_ard_3-2-1_093078_2023-05-06_final
2023-05-06 09:36:15	ga_ls8c_ard_3-2-1_093079_2023-05-06_final
2023-05-06 09:37:27	ga_ls8c_ard_3-2-1_093082_2023-05-06_final
2023-05-06 09:37:51	ga_ls8c_ard_3-2-1_093083_2023-05-06_final
2023-05-06 09:39:02	ga_ls8c_ard_3-2-1_093086_2023-05-06_final
2023-05-06 09:39:26	ga_ls8c_ard_3-2-1_093087_2023-05-06_final
2023-05-06 09:39:50	ga_ls8c_ard_3-2-1_093088_2023-05-06_final
2023-05-06 11:12:20	ga_ls8c_ard_3-2-1_109072_2023-05-06_final
2023-05-06 11:12:44	ga_ls8c_ard_3-2-1_109073_2023-05-06_final
2023-05-06 11:13:08	ga_ls8c_ard_3-2-1_109074_2023-05-06_final
2023-05-06 11:14:20	ga_ls8c_ard_3-2-1_109077_2023-05-06_final
2023-05-06 11:14:44	ga_ls8c_ard_3-2-1_109078_2023-05-06_final
2023-05-06 11:15:08	ga_ls8c_ard_3-2-1_109079_2023-05-06_final
2023-05-06 11:16:44	ga_ls8c_ard_3-2-1_109083_2023-05-06_final
2023-05-07 10:16:42	ga_ls8c_ard_3-2-1_100072_2023-05-07_final
2023-05-07 10:19:06	ga_ls8c_ard_3-2-1_100078_2023-05-07_final
2023-05-07 10:19:30	ga_ls8c_ard_3-2-1_100079_2023-05-07_final
2023-05-07 11:57:59	ga_ls8c_ard_3-2-1_116078_2023-05-07_final
2023-05-08 09:21:04	ga_ls8c_ard_3-2-1_091072_2023-05-07_final
2023-05-08 09:21:28	ga_ls8c_ard_3-2-1_091073_2023-05-07_final
2023-05-08 09:21:51	ga_ls8c_ard_3-2-1_091074_2023-05-07_final
2023-05-08 09:22:15	ga_ls8c_ard_3-2-1_091075_2023-05-07_final
2023-05-08 09:22:39	ga_ls8c_ard_3-2-1_091076_2023-05-07_final
2023-05-08 09:23:51	ga_ls8c_ard_3-2-1_091079_2023-05-07_final
2023-05-08 09:25:27	ga_ls8c_ard_3-2-1_091083_2023-05-07_final
2023-05-08 09:26:39	ga_ls8c_ard_3-2-1_091086_2023-05-07_final
2023-05-08 09:27:03	ga_ls8c_ard_3-2-1_091087_2023-05-07_final
2023-05-08 09:27:27	ga_ls8c_ard_3-2-1_091088_2023-05-07_final
2023-05-08 11:00:20	ga_ls8c_ard_3-2-1_107073_2023-05-08_final
2023-05-08 11:01:08	ga_ls8c_ard_3-2-1_107075_2023-05-08_final
2023-05-08 11:01:56	ga_ls8c_ard_3-2-1_107077_2023-05-08_final
2023-05-08 11:02:20	ga_ls8c_ard_3-2-1_107078_2023-05-08_final
2023-05-08 11:03:08	ga_ls8c_ard_3-2-1_107080_2023-05-08_final
2023-05-08 11:04:44	ga_ls8c_ard_3-2-1_107084_2023-05-08_final
2023-05-09 10:03:06	ga_ls8c_ard_3-2-1_098069_2023-05-09_final
2023-05-09 10:05:06	ga_ls8c_ard_3-2-1_098074_2023-05-09_final
2023-05-09 10:05:30	ga_ls8c_ard_3-2-1_098075_2023-05-09_final
2023-05-09 10:06:42	ga_ls8c_ard_3-2-1_098078_2023-05-09_final
2023-05-09 10:07:06	ga_ls8c_ard_3-2-1_098079_2023-05-09_final
2023-05-09 10:08:18	ga_ls8c_ard_3-2-1_098082_2023-05-09_final
2023-05-09 10:08:41	ga_ls8c_ard_3-2-1_098083_2023-05-09_final
2023-05-09 10:09:05	ga_ls8c_ard_3-2-1_098084_2023-05-09_final
2023-05-09 10:09:29	ga_ls8c_ard_3-2-1_098085_2023-05-09_final
2023-05-09 11:43:59	ga_ls8c_ard_3-2-1_114074_2023-05-09_final
2023-05-09 11:44:23	ga_ls8c_ard_3-2-1_114075_2023-05-09_final
2023-05-09 11:45:11	ga_ls8c_ard_3-2-1_114077_2023-05-09_final
2023-05-10 09:09:27	ga_ls8c_ard_3-2-1_089074_2023-05-09_final
2023-05-10 09:09:51	ga_ls8c_ard_3-2-1_089075_2023-05-09_final
2023-05-10 09:10:15	ga_ls8c_ard_3-2-1_089076_2023-05-09_final
2023-05-10 09:10:39	ga_ls8c_ard_3-2-1_089077_2023-05-09_final
2023-05-10 09:11:03	ga_ls8c_ard_3-2-1_089078_2023-05-09_final
2023-05-10 09:11:51	ga_ls8c_ard_3-2-1_089080_2023-05-09_final
2023-05-10 09:12:15	ga_ls8c_ard_3-2-1_089081_2023-05-09_final
2023-05-10 09:12:39	ga_ls8c_ard_3-2-1_089082_2023-05-09_final
2023-05-10 09:15:27	ga_ls8c_ard_3-2-1_089089_2023-05-09_final
2023-05-10 09:15:51	ga_ls8c_ard_3-2-1_089090_2023-05-09_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