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

72 results

Time (local)	Label
2023-07-30 09:51:37	ga_ls8c_ard_3-2-1_096070_2023-07-30_final
2023-07-30 09:52:01	ga_ls8c_ard_3-2-1_096071_2023-07-30_final
2023-07-30 09:52:24	ga_ls8c_ard_3-2-1_096072_2023-07-30_final
2023-07-30 09:52:48	ga_ls8c_ard_3-2-1_096073_2023-07-30_final
2023-07-30 09:53:12	ga_ls8c_ard_3-2-1_096074_2023-07-30_final
2023-07-30 09:53:36	ga_ls8c_ard_3-2-1_096075_2023-07-30_final
2023-07-30 09:54:00	ga_ls8c_ard_3-2-1_096076_2023-07-30_final
2023-07-30 09:54:24	ga_ls8c_ard_3-2-1_096077_2023-07-30_final
2023-07-30 09:54:48	ga_ls8c_ard_3-2-1_096078_2023-07-30_final
2023-07-30 09:55:12	ga_ls8c_ard_3-2-1_096079_2023-07-30_final
2023-07-30 09:55:36	ga_ls8c_ard_3-2-1_096080_2023-07-30_final
2023-07-30 09:56:00	ga_ls8c_ard_3-2-1_096081_2023-07-30_final
2023-07-30 09:56:24	ga_ls8c_ard_3-2-1_096082_2023-07-30_final
2023-07-30 09:56:48	ga_ls8c_ard_3-2-1_096083_2023-07-30_final
2023-07-30 09:57:12	ga_ls8c_ard_3-2-1_096084_2023-07-30_final
2023-07-30 09:57:36	ga_ls8c_ard_3-2-1_096085_2023-07-30_final
2023-07-30 09:58:00	ga_ls8c_ard_3-2-1_096086_2023-07-30_final
2023-07-30 11:31:18	ga_ls8c_ard_3-2-1_112072_2023-07-30_final
2023-07-30 11:31:41	ga_ls8c_ard_3-2-1_112073_2023-07-30_final
2023-07-30 11:32:05	ga_ls8c_ard_3-2-1_112074_2023-07-30_final
2023-07-30 11:32:29	ga_ls8c_ard_3-2-1_112075_2023-07-30_final
2023-07-30 11:32:53	ga_ls8c_ard_3-2-1_112076_2023-07-30_final
2023-07-30 11:33:17	ga_ls8c_ard_3-2-1_112077_2023-07-30_final
2023-07-30 11:33:41	ga_ls8c_ard_3-2-1_112078_2023-07-30_final
2023-07-30 11:34:05	ga_ls8c_ard_3-2-1_112079_2023-07-30_final
2023-07-30 11:34:29	ga_ls8c_ard_3-2-1_112080_2023-07-30_final
2023-07-30 11:34:53	ga_ls8c_ard_3-2-1_112081_2023-07-30_final
2023-07-30 11:35:17	ga_ls8c_ard_3-2-1_112082_2023-07-30_final
2023-07-30 11:35:41	ga_ls8c_ard_3-2-1_112083_2023-07-30_final
2023-07-30 11:36:05	ga_ls8c_ard_3-2-1_112084_2023-07-30_final
2023-07-31 10:34:05	ga_ls8c_ard_3-2-1_103068_2023-07-31_final
2023-07-31 10:34:29	ga_ls8c_ard_3-2-1_103069_2023-07-31_final
2023-07-31 10:34:53	ga_ls8c_ard_3-2-1_103070_2023-07-31_final
2023-07-31 10:35:17	ga_ls8c_ard_3-2-1_103071_2023-07-31_final
2023-07-31 10:35:41	ga_ls8c_ard_3-2-1_103072_2023-07-31_final
2023-07-31 10:36:05	ga_ls8c_ard_3-2-1_103073_2023-07-31_final
2023-07-31 10:36:29	ga_ls8c_ard_3-2-1_103074_2023-07-31_final
2023-07-31 10:36:53	ga_ls8c_ard_3-2-1_103075_2023-07-31_final
2023-07-31 10:37:16	ga_ls8c_ard_3-2-1_103076_2023-07-31_final
2023-07-31 10:37:40	ga_ls8c_ard_3-2-1_103077_2023-07-31_final
2023-07-31 10:38:04	ga_ls8c_ard_3-2-1_103078_2023-07-31_final
2023-07-31 10:38:28	ga_ls8c_ard_3-2-1_103079_2023-07-31_final
2023-07-31 10:38:52	ga_ls8c_ard_3-2-1_103080_2023-07-31_final
2023-07-31 10:39:16	ga_ls8c_ard_3-2-1_103081_2023-07-31_final
2023-07-31 10:39:40	ga_ls8c_ard_3-2-1_103082_2023-07-31_final
2023-08-01 09:40:28	ga_ls8c_ard_3-2-1_094073_2023-08-01_final
2023-08-01 09:41:16	ga_ls8c_ard_3-2-1_094075_2023-08-01_final
2023-08-01 09:41:40	ga_ls8c_ard_3-2-1_094076_2023-08-01_final
2023-08-01 09:42:03	ga_ls8c_ard_3-2-1_094077_2023-08-01_final
2023-08-01 09:42:27	ga_ls8c_ard_3-2-1_094078_2023-08-01_final
2023-08-01 09:42:51	ga_ls8c_ard_3-2-1_094079_2023-08-01_final
2023-08-01 09:43:15	ga_ls8c_ard_3-2-1_094080_2023-08-01_final
2023-08-01 09:43:39	ga_ls8c_ard_3-2-1_094081_2023-08-01_final
2023-08-01 09:44:27	ga_ls8c_ard_3-2-1_094083_2023-08-01_final
2023-08-01 09:44:51	ga_ls8c_ard_3-2-1_094084_2023-08-01_final
2023-08-01 09:45:15	ga_ls8c_ard_3-2-1_094085_2023-08-01_final
2023-08-01 09:46:03	ga_ls8c_ard_3-2-1_094087_2023-08-01_final
2023-08-01 11:18:09	ga_ls8c_ard_3-2-1_110070_2023-08-01_final
2023-08-01 11:18:33	ga_ls8c_ard_3-2-1_110071_2023-08-01_final
2023-08-01 11:18:57	ga_ls8c_ard_3-2-1_110072_2023-08-01_final
2023-08-01 11:19:21	ga_ls8c_ard_3-2-1_110073_2023-08-01_final
2023-08-01 11:19:45	ga_ls8c_ard_3-2-1_110074_2023-08-01_final
2023-08-01 11:20:09	ga_ls8c_ard_3-2-1_110075_2023-08-01_final
2023-08-01 11:20:33	ga_ls8c_ard_3-2-1_110076_2023-08-01_final
2023-08-01 11:20:57	ga_ls8c_ard_3-2-1_110077_2023-08-01_final
2023-08-01 11:21:21	ga_ls8c_ard_3-2-1_110078_2023-08-01_final
2023-08-01 11:21:44	ga_ls8c_ard_3-2-1_110079_2023-08-01_final
2023-08-01 11:22:08	ga_ls8c_ard_3-2-1_110080_2023-08-01_final
2023-08-01 11:22:32	ga_ls8c_ard_3-2-1_110081_2023-08-01_final
2023-08-01 11:23:20	ga_ls8c_ard_3-2-1_110083_2023-08-01_final
2023-08-01 11:23:44	ga_ls8c_ard_3-2-1_110084_2023-08-01_final
2023-08-01 11:24:08	ga_ls8c_ard_3-2-1_110085_2023-08-01_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