Search ga_ls8c_ard_3 on 18th June 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
2018-06-18 09:24:47	ga_ls8c_ard_3-0-0_092067_2018-06-17_final
2018-06-18 09:25:11	ga_ls8c_ard_3-0-0_092068_2018-06-17_final
2018-06-18 09:26:23	ga_ls8c_ard_3-0-0_092071_2018-06-17_final
2018-06-18 09:26:47	ga_ls8c_ard_3-0-0_092072_2018-06-17_final
2018-06-18 09:27:11	ga_ls8c_ard_3-0-0_092073_2018-06-17_final
2018-06-18 09:27:35	ga_ls8c_ard_3-0-0_092074_2018-06-17_final
2018-06-18 09:27:59	ga_ls8c_ard_3-0-0_092075_2018-06-17_final
2018-06-18 09:28:23	ga_ls8c_ard_3-0-0_092076_2018-06-17_final
2018-06-18 09:28:47	ga_ls8c_ard_3-0-0_092077_2018-06-17_final
2018-06-18 09:29:11	ga_ls8c_ard_3-0-0_092078_2018-06-17_final
2018-06-18 09:29:35	ga_ls8c_ard_3-0-0_092079_2018-06-17_final
2018-06-18 09:29:59	ga_ls8c_ard_3-0-0_092080_2018-06-17_final
2018-06-18 09:30:23	ga_ls8c_ard_3-0-0_092081_2018-06-18_final
2018-06-18 09:30:47	ga_ls8c_ard_3-0-0_092082_2018-06-18_final
2018-06-18 09:31:11	ga_ls8c_ard_3-0-0_092083_2018-06-18_final
2018-06-18 09:31:34	ga_ls8c_ard_3-0-0_092084_2018-06-18_final
2018-06-18 09:31:58	ga_ls8c_ard_3-0-0_092085_2018-06-18_final
2018-06-18 09:32:22	ga_ls8c_ard_3-0-0_092086_2018-06-18_final
2018-06-18 09:32:46	ga_ls8c_ard_3-0-0_092087_2018-06-18_final
2018-06-18 09:33:10	ga_ls8c_ard_3-0-0_092088_2018-06-18_final
2018-06-18 09:33:34	ga_ls8c_ard_3-0-0_092089_2018-06-18_final
2018-06-18 09:33:58	ga_ls8c_ard_3-0-0_092090_2018-06-18_final
2018-06-18 11:03:41	ga_ls8c_ard_3-0-0_108067_2018-06-18_final
2018-06-18 11:04:04	ga_ls8c_ard_3-0-0_108068_2018-06-18_final
2018-06-18 11:04:28	ga_ls8c_ard_3-0-0_108069_2018-06-18_final
2018-06-18 11:04:52	ga_ls8c_ard_3-0-0_108070_2018-06-18_final
2018-06-18 11:05:16	ga_ls8c_ard_3-0-0_108071_2018-06-18_final
2018-06-18 11:05:40	ga_ls8c_ard_3-0-0_108072_2018-06-18_final
2018-06-18 11:06:04	ga_ls8c_ard_3-0-0_108073_2018-06-18_final
2018-06-18 11:06:28	ga_ls8c_ard_3-0-0_108074_2018-06-18_final
2018-06-18 11:06:52	ga_ls8c_ard_3-0-0_108075_2018-06-18_final
2018-06-18 11:07:16	ga_ls8c_ard_3-0-0_108076_2018-06-18_final
2018-06-18 11:07:40	ga_ls8c_ard_3-0-0_108077_2018-06-18_final
2018-06-18 11:08:04	ga_ls8c_ard_3-0-0_108078_2018-06-18_final
2018-06-18 11:08:28	ga_ls8c_ard_3-0-0_108079_2018-06-18_final
2018-06-18 11:08:52	ga_ls8c_ard_3-0-0_108080_2018-06-18_final
2018-06-18 11:09:16	ga_ls8c_ard_3-0-0_108081_2018-06-18_final
2018-06-18 11:09:40	ga_ls8c_ard_3-0-0_108082_2018-06-18_final
2018-06-18 11:10:04	ga_ls8c_ard_3-0-0_108083_2018-06-18_final
2018-06-18 11:10:28	ga_ls8c_ard_3-0-0_108084_2018-06-18_final
2018-06-18 11:10:51	ga_ls8c_ard_3-0-0_108085_2018-06-18_final

Return to ga_ls8c_ard_3 on 18th June 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

June

18th