Search ga_ls8c_ard_3 on 27th April 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

40 results

Time (local)	Label
2018-04-27 09:49:48	ga_ls8c_ard_3-0-0_096067_2018-04-27_final
2018-04-27 09:50:12	ga_ls8c_ard_3-0-0_096068_2018-04-27_final
2018-04-27 09:50:35	ga_ls8c_ard_3-0-0_096069_2018-04-27_final
2018-04-27 09:50:59	ga_ls8c_ard_3-0-0_096070_2018-04-27_final
2018-04-27 09:51:23	ga_ls8c_ard_3-0-0_096071_2018-04-27_final
2018-04-27 09:51:47	ga_ls8c_ard_3-0-0_096072_2018-04-27_final
2018-04-27 09:52:11	ga_ls8c_ard_3-0-0_096073_2018-04-27_final
2018-04-27 09:52:35	ga_ls8c_ard_3-0-0_096074_2018-04-27_final
2018-04-27 09:52:59	ga_ls8c_ard_3-0-0_096075_2018-04-27_final
2018-04-27 09:53:23	ga_ls8c_ard_3-0-0_096076_2018-04-27_final
2018-04-27 09:53:47	ga_ls8c_ard_3-0-0_096077_2018-04-27_final
2018-04-27 09:54:11	ga_ls8c_ard_3-0-0_096078_2018-04-27_final
2018-04-27 09:54:35	ga_ls8c_ard_3-0-0_096079_2018-04-27_final
2018-04-27 09:54:59	ga_ls8c_ard_3-0-0_096080_2018-04-27_final
2018-04-27 09:55:23	ga_ls8c_ard_3-0-0_096081_2018-04-27_final
2018-04-27 09:55:47	ga_ls8c_ard_3-0-0_096082_2018-04-27_final
2018-04-27 09:56:11	ga_ls8c_ard_3-0-0_096083_2018-04-27_final
2018-04-27 09:56:35	ga_ls8c_ard_3-0-0_096084_2018-04-27_final
2018-04-27 09:56:58	ga_ls8c_ard_3-0-0_096085_2018-04-27_final
2018-04-27 09:57:22	ga_ls8c_ard_3-0-0_096086_2018-04-27_final
2018-04-27 09:57:46	ga_ls8c_ard_3-0-0_096087_2018-04-27_final
2018-04-27 11:28:41	ga_ls8c_ard_3-0-0_112067_2018-04-27_final
2018-04-27 11:29:05	ga_ls8c_ard_3-0-0_112068_2018-04-27_final
2018-04-27 11:29:28	ga_ls8c_ard_3-0-0_112069_2018-04-27_final
2018-04-27 11:29:52	ga_ls8c_ard_3-0-0_112070_2018-04-27_final
2018-04-27 11:30:16	ga_ls8c_ard_3-0-0_112071_2018-04-27_final
2018-04-27 11:30:40	ga_ls8c_ard_3-0-0_112072_2018-04-27_final
2018-04-27 11:31:04	ga_ls8c_ard_3-0-0_112073_2018-04-27_final
2018-04-27 11:31:28	ga_ls8c_ard_3-0-0_112074_2018-04-27_final
2018-04-27 11:31:52	ga_ls8c_ard_3-0-0_112075_2018-04-27_final
2018-04-27 11:32:16	ga_ls8c_ard_3-0-0_112076_2018-04-27_final
2018-04-27 11:32:40	ga_ls8c_ard_3-0-0_112077_2018-04-27_final
2018-04-27 11:33:04	ga_ls8c_ard_3-0-0_112078_2018-04-27_final
2018-04-27 11:33:28	ga_ls8c_ard_3-0-0_112079_2018-04-27_final
2018-04-27 11:33:52	ga_ls8c_ard_3-0-0_112080_2018-04-27_final
2018-04-27 11:34:16	ga_ls8c_ard_3-0-0_112081_2018-04-27_final
2018-04-27 11:34:40	ga_ls8c_ard_3-0-0_112082_2018-04-27_final
2018-04-27 11:35:04	ga_ls8c_ard_3-0-0_112083_2018-04-27_final
2018-04-27 11:35:28	ga_ls8c_ard_3-0-0_112084_2018-04-27_final
2018-04-27 11:35:52	ga_ls8c_ard_3-0-0_112085_2018-04-27_final

Return to ga_ls8c_ard_3 on 27th April 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

April

27th