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

53 results

Time (local)	Label
2022-03-23 09:40:28	ga_ls8c_ard_3-2-1_094073_2022-03-23_final
2022-03-23 09:40:52	ga_ls8c_ard_3-2-1_094074_2022-03-23_final
2022-03-23 09:43:39	ga_ls8c_ard_3-2-1_094081_2022-03-23_final
2022-03-23 09:45:39	ga_ls8c_ard_3-2-1_094086_2022-03-23_final
2022-03-23 09:46:03	ga_ls8c_ard_3-2-1_094087_2022-03-23_final
2022-03-23 11:18:09	ga_ls8c_ard_3-2-1_110070_2022-03-23_final
2022-03-23 11:20:32	ga_ls8c_ard_3-2-1_110076_2022-03-23_final
2022-03-23 11:21:20	ga_ls8c_ard_3-2-1_110078_2022-03-23_final
2022-03-23 11:22:08	ga_ls8c_ard_3-2-1_110080_2022-03-23_final
2022-03-23 11:23:20	ga_ls8c_ard_3-2-1_110083_2022-03-23_final
2022-03-24 10:24:06	ga_ls8c_ard_3-2-1_101074_2022-03-24_final
2022-03-24 10:24:30	ga_ls8c_ard_3-2-1_101075_2022-03-24_final
2022-03-24 10:25:18	ga_ls8c_ard_3-2-1_101077_2022-03-24_final
2022-03-25 09:31:16	ga_ls8c_ard_3-2-1_092081_2022-03-25_final
2022-03-25 09:32:04	ga_ls8c_ard_3-2-1_092083_2022-03-25_final
2022-03-25 09:32:28	ga_ls8c_ard_3-2-1_092084_2022-03-25_final
2022-03-25 09:34:27	ga_ls8c_ard_3-2-1_092089_2022-03-25_final
2022-03-25 11:06:57	ga_ls8c_ard_3-2-1_108073_2022-03-25_final
2022-03-25 11:07:21	ga_ls8c_ard_3-2-1_108074_2022-03-25_final
2022-03-25 11:07:45	ga_ls8c_ard_3-2-1_108075_2022-03-25_final
2022-03-25 11:08:09	ga_ls8c_ard_3-2-1_108076_2022-03-25_final
2022-03-25 11:09:21	ga_ls8c_ard_3-2-1_108079_2022-03-25_final
2022-03-25 11:09:45	ga_ls8c_ard_3-2-1_108080_2022-03-25_final
2022-03-25 11:10:57	ga_ls8c_ard_3-2-1_108083_2022-03-25_final
2022-03-25 11:11:21	ga_ls8c_ard_3-2-1_108084_2022-03-25_final
2022-03-26 10:10:55	ga_ls8c_ard_3-2-1_099072_2022-03-26_final
2022-03-26 10:11:19	ga_ls8c_ard_3-2-1_099073_2022-03-26_final
2022-03-26 10:11:43	ga_ls8c_ard_3-2-1_099074_2022-03-26_final
2022-03-26 10:12:07	ga_ls8c_ard_3-2-1_099075_2022-03-26_final
2022-03-26 10:12:31	ga_ls8c_ard_3-2-1_099076_2022-03-26_final
2022-03-26 10:13:43	ga_ls8c_ard_3-2-1_099079_2022-03-26_final
2022-03-26 10:14:31	ga_ls8c_ard_3-2-1_099081_2022-03-26_final
2022-03-26 10:15:42	ga_ls8c_ard_3-2-1_099084_2022-03-26_final
2022-03-27 09:18:05	ga_ls8c_ard_3-2-1_090079_2022-03-26_final
2022-03-27 09:20:04	ga_ls8c_ard_3-2-1_090084_2022-03-26_final
2022-03-27 09:22:04	ga_ls8c_ard_3-2-1_090089_2022-03-26_final
2022-03-27 09:22:28	ga_ls8c_ard_3-2-1_090090_2022-03-26_final
2022-03-27 10:52:34	ga_ls8c_ard_3-2-1_106068_2022-03-27_final
2022-03-27 10:52:58	ga_ls8c_ard_3-2-1_106069_2022-03-27_final
2022-03-27 10:53:22	ga_ls8c_ard_3-2-1_106070_2022-03-27_final
2022-03-27 10:53:46	ga_ls8c_ard_3-2-1_106071_2022-03-27_final
2022-03-27 10:54:10	ga_ls8c_ard_3-2-1_106072_2022-03-27_final
2022-03-27 10:54:34	ga_ls8c_ard_3-2-1_106073_2022-03-27_final
2022-03-27 10:54:58	ga_ls8c_ard_3-2-1_106074_2022-03-27_final
2022-03-27 10:55:22	ga_ls8c_ard_3-2-1_106075_2022-03-27_final
2022-03-27 10:55:46	ga_ls8c_ard_3-2-1_106076_2022-03-27_final
2022-03-27 10:56:10	ga_ls8c_ard_3-2-1_106077_2022-03-27_final
2022-03-27 10:56:34	ga_ls8c_ard_3-2-1_106078_2022-03-27_final
2022-03-27 10:56:57	ga_ls8c_ard_3-2-1_106079_2022-03-27_final
2022-03-27 10:57:21	ga_ls8c_ard_3-2-1_106080_2022-03-27_final
2022-03-27 10:57:45	ga_ls8c_ard_3-2-1_106081_2022-03-27_final
2022-03-27 10:58:09	ga_ls8c_ard_3-2-1_106082_2022-03-27_final
2022-03-27 10:58:33	ga_ls8c_ard_3-2-1_106083_2022-03-27_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