Search ga_ls8c_ard_3 on 18th September 2018

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

41 results

Time (local)	Label
2018-09-18 08:23:43	ga_ls8c_ard_3-2-1_080098_2018-09-17_final
2018-09-18 09:50:13	ga_ls8c_ard_3-0-0_096067_2018-09-18_final
2018-09-18 09:50:37	ga_ls8c_ard_3-0-0_096068_2018-09-18_final
2018-09-18 09:51:01	ga_ls8c_ard_3-0-0_096069_2018-09-18_final
2018-09-18 09:51:25	ga_ls8c_ard_3-0-0_096070_2018-09-18_final
2018-09-18 09:51:49	ga_ls8c_ard_3-0-0_096071_2018-09-18_final
2018-09-18 09:52:13	ga_ls8c_ard_3-0-0_096072_2018-09-18_final
2018-09-18 09:52:37	ga_ls8c_ard_3-0-0_096073_2018-09-18_final
2018-09-18 09:53:01	ga_ls8c_ard_3-0-0_096074_2018-09-18_final
2018-09-18 09:53:25	ga_ls8c_ard_3-0-0_096075_2018-09-18_final
2018-09-18 09:53:49	ga_ls8c_ard_3-0-0_096076_2018-09-18_final
2018-09-18 09:54:13	ga_ls8c_ard_3-0-0_096077_2018-09-18_final
2018-09-18 09:54:37	ga_ls8c_ard_3-0-0_096078_2018-09-18_final
2018-09-18 09:55:01	ga_ls8c_ard_3-0-0_096079_2018-09-18_final
2018-09-18 09:55:24	ga_ls8c_ard_3-0-0_096080_2018-09-18_final
2018-09-18 09:55:48	ga_ls8c_ard_3-0-0_096081_2018-09-18_final
2018-09-18 09:56:12	ga_ls8c_ard_3-0-0_096082_2018-09-18_final
2018-09-18 09:56:36	ga_ls8c_ard_3-0-0_096083_2018-09-18_final
2018-09-18 09:57:00	ga_ls8c_ard_3-0-0_096084_2018-09-18_final
2018-09-18 09:57:24	ga_ls8c_ard_3-0-0_096085_2018-09-18_final
2018-09-18 09:57:48	ga_ls8c_ard_3-0-0_096086_2018-09-18_final
2018-09-18 09:58:12	ga_ls8c_ard_3-0-0_096087_2018-09-18_final
2018-09-18 11:29:06	ga_ls8c_ard_3-0-0_112067_2018-09-18_final
2018-09-18 11:29:30	ga_ls8c_ard_3-0-0_112068_2018-09-18_final
2018-09-18 11:29:54	ga_ls8c_ard_3-0-0_112069_2018-09-18_final
2018-09-18 11:30:18	ga_ls8c_ard_3-0-0_112070_2018-09-18_final
2018-09-18 11:30:42	ga_ls8c_ard_3-0-0_112071_2018-09-18_final
2018-09-18 11:31:06	ga_ls8c_ard_3-0-0_112072_2018-09-18_final
2018-09-18 11:31:30	ga_ls8c_ard_3-0-0_112073_2018-09-18_final
2018-09-18 11:31:54	ga_ls8c_ard_3-0-0_112074_2018-09-18_final
2018-09-18 11:32:18	ga_ls8c_ard_3-0-0_112075_2018-09-18_final
2018-09-18 11:32:42	ga_ls8c_ard_3-0-0_112076_2018-09-18_final
2018-09-18 11:33:06	ga_ls8c_ard_3-0-0_112077_2018-09-18_final
2018-09-18 11:33:30	ga_ls8c_ard_3-0-0_112078_2018-09-18_final
2018-09-18 11:33:54	ga_ls8c_ard_3-0-0_112079_2018-09-18_final
2018-09-18 11:34:18	ga_ls8c_ard_3-0-0_112080_2018-09-18_final
2018-09-18 11:34:41	ga_ls8c_ard_3-0-0_112081_2018-09-18_final
2018-09-18 11:35:05	ga_ls8c_ard_3-0-0_112082_2018-09-18_final
2018-09-18 11:35:29	ga_ls8c_ard_3-0-0_112083_2018-09-18_final
2018-09-18 11:35:53	ga_ls8c_ard_3-0-0_112084_2018-09-18_final
2018-09-18 11:36:17	ga_ls8c_ard_3-0-0_112085_2018-09-18_final

Return to ga_ls8c_ard_3 on 18th September 2018 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

2018

September

18th