Search ga_ls8c_ard_3 across November 2016

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

First 100 results (query limit)

Time (local)	Label
2016-11-26 11:11:16	ga_ls8c_ard_3-0-0_109067_2016-11-26_final
2016-11-26 11:11:40	ga_ls8c_ard_3-0-0_109068_2016-11-26_final
2016-11-26 11:12:04	ga_ls8c_ard_3-0-0_109069_2016-11-26_final
2016-11-26 11:12:28	ga_ls8c_ard_3-0-0_109070_2016-11-26_final
2016-11-26 11:12:52	ga_ls8c_ard_3-0-0_109071_2016-11-26_final
2016-11-26 11:13:16	ga_ls8c_ard_3-0-0_109072_2016-11-26_final
2016-11-26 11:13:40	ga_ls8c_ard_3-0-0_109073_2016-11-26_final
2016-11-26 11:14:04	ga_ls8c_ard_3-0-0_109074_2016-11-26_final
2016-11-26 11:14:28	ga_ls8c_ard_3-1-0_109075_2016-11-26_final
2016-11-26 11:14:52	ga_ls8c_ard_3-0-0_109076_2016-11-26_final
2016-11-26 11:15:16	ga_ls8c_ard_3-0-0_109077_2016-11-26_final
2016-11-26 11:15:40	ga_ls8c_ard_3-0-0_109078_2016-11-26_final
2016-11-26 11:16:04	ga_ls8c_ard_3-0-0_109079_2016-11-26_final
2016-11-26 11:16:27	ga_ls8c_ard_3-0-0_109080_2016-11-26_final
2016-11-26 11:16:51	ga_ls8c_ard_3-0-0_109081_2016-11-26_final
2016-11-26 11:17:15	ga_ls8c_ard_3-0-0_109082_2016-11-26_final
2016-11-26 11:17:39	ga_ls8c_ard_3-0-0_109083_2016-11-26_final
2016-11-26 11:18:03	ga_ls8c_ard_3-0-0_109084_2016-11-26_final
2016-11-26 11:18:27	ga_ls8c_ard_3-0-0_109085_2016-11-26_final
2016-11-27 08:42:45	ga_ls8c_ard_3-2-1_084082_2016-11-26_final
2016-11-27 10:15:39	ga_ls8c_ard_3-0-0_100067_2016-11-27_final
2016-11-27 10:16:03	ga_ls8c_ard_3-0-0_100068_2016-11-27_final
2016-11-27 10:16:27	ga_ls8c_ard_3-0-0_100069_2016-11-27_final
2016-11-27 10:16:51	ga_ls8c_ard_3-0-0_100070_2016-11-27_final
2016-11-27 10:17:15	ga_ls8c_ard_3-0-0_100071_2016-11-27_final
2016-11-27 10:17:39	ga_ls8c_ard_3-0-0_100072_2016-11-27_final
2016-11-27 10:18:02	ga_ls8c_ard_3-0-0_100073_2016-11-27_final
2016-11-27 10:18:26	ga_ls8c_ard_3-0-0_100074_2016-11-27_final
2016-11-27 10:18:50	ga_ls8c_ard_3-0-0_100075_2016-11-27_final
2016-11-27 10:19:14	ga_ls8c_ard_3-0-0_100076_2016-11-27_final
2016-11-27 10:19:38	ga_ls8c_ard_3-0-0_100077_2016-11-27_final
2016-11-27 10:20:02	ga_ls8c_ard_3-0-0_100078_2016-11-27_final
2016-11-27 10:20:26	ga_ls8c_ard_3-0-0_100079_2016-11-27_final
2016-11-27 10:20:50	ga_ls8c_ard_3-0-0_100080_2016-11-27_final
2016-11-27 10:21:14	ga_ls8c_ard_3-0-0_100081_2016-11-27_final
2016-11-27 10:21:38	ga_ls8c_ard_3-0-0_100082_2016-11-27_final
2016-11-27 10:22:02	ga_ls8c_ard_3-0-0_100083_2016-11-27_final
2016-11-27 10:22:26	ga_ls8c_ard_3-0-0_100084_2016-11-27_final
2016-11-27 10:22:50	ga_ls8c_ard_3-0-0_100085_2016-11-27_final
2016-11-27 11:57:20	ga_ls8c_ard_3-0-0_116074_2016-11-27_final
2016-11-27 11:57:43	ga_ls8c_ard_3-0-0_116075_2016-11-27_final
2016-11-27 11:58:07	ga_ls8c_ard_3-0-0_116076_2016-11-27_final
2016-11-27 11:58:31	ga_ls8c_ard_3-0-0_116077_2016-11-27_final
2016-11-27 11:58:55	ga_ls8c_ard_3-0-0_116078_2016-11-27_final
2016-11-28 09:20:25	ga_ls8c_ard_3-0-0_091068_2016-11-27_final
2016-11-28 09:22:01	ga_ls8c_ard_3-0-0_091072_2016-11-27_final
2016-11-28 09:22:25	ga_ls8c_ard_3-0-0_091073_2016-11-27_final
2016-11-28 09:22:49	ga_ls8c_ard_3-0-0_091074_2016-11-27_final
2016-11-28 09:23:13	ga_ls8c_ard_3-0-0_091075_2016-11-27_final
2016-11-28 09:23:37	ga_ls8c_ard_3-0-0_091076_2016-11-27_final
2016-11-28 09:24:01	ga_ls8c_ard_3-0-0_091077_2016-11-27_final
2016-11-28 09:24:25	ga_ls8c_ard_3-0-0_091078_2016-11-27_final
2016-11-28 09:24:49	ga_ls8c_ard_3-0-0_091079_2016-11-27_final
2016-11-28 09:25:13	ga_ls8c_ard_3-0-0_091080_2016-11-27_final
2016-11-28 09:25:37	ga_ls8c_ard_3-0-0_091081_2016-11-27_final
2016-11-28 09:26:01	ga_ls8c_ard_3-0-0_091082_2016-11-27_final
2016-11-28 09:26:25	ga_ls8c_ard_3-0-0_091083_2016-11-27_final
2016-11-28 09:26:48	ga_ls8c_ard_3-0-0_091084_2016-11-27_final
2016-11-28 09:27:12	ga_ls8c_ard_3-0-0_091085_2016-11-27_final
2016-11-28 09:27:36	ga_ls8c_ard_3-0-0_091086_2016-11-27_final
2016-11-28 09:28:00	ga_ls8c_ard_3-0-0_091087_2016-11-27_final
2016-11-28 09:28:24	ga_ls8c_ard_3-0-0_091088_2016-11-27_final
2016-11-28 09:28:48	ga_ls8c_ard_3-0-0_091089_2016-11-27_final
2016-11-28 09:29:12	ga_ls8c_ard_3-0-0_091090_2016-11-27_final
2016-11-28 09:29:36	ga_ls8c_ard_3-0-0_091091_2016-11-27_final
2016-11-29 10:03:17	ga_ls8c_ard_3-0-0_098067_2016-11-29_final
2016-11-29 10:03:41	ga_ls8c_ard_3-0-0_098068_2016-11-29_final
2016-11-30 09:10:27	ga_ls8c_ard_3-0-0_089074_2016-11-29_final
2016-11-30 09:10:51	ga_ls8c_ard_3-0-0_089075_2016-11-29_final
2016-11-30 09:11:15	ga_ls8c_ard_3-0-0_089076_2016-11-29_final
2016-11-30 09:11:39	ga_ls8c_ard_3-0-0_089077_2016-11-29_final
2016-11-30 09:12:03	ga_ls8c_ard_3-0-0_089078_2016-11-29_final
2016-11-30 09:12:27	ga_ls8c_ard_3-0-0_089079_2016-11-29_final
2016-11-30 09:12:51	ga_ls8c_ard_3-0-0_089080_2016-11-29_final
2016-11-30 09:13:15	ga_ls8c_ard_3-0-0_089081_2016-11-29_final
2016-11-30 09:13:39	ga_ls8c_ard_3-0-0_089082_2016-11-29_final
2016-11-30 09:14:03	ga_ls8c_ard_3-0-0_089083_2016-11-29_final
2016-11-30 09:14:27	ga_ls8c_ard_3-0-0_089084_2016-11-29_final
2016-11-30 09:14:51	ga_ls8c_ard_3-0-0_089085_2016-11-29_final
2016-11-30 09:15:15	ga_ls8c_ard_3-0-0_089086_2016-11-29_final
2016-11-30 09:15:39	ga_ls8c_ard_3-0-0_089087_2016-11-29_final
2016-11-30 09:16:02	ga_ls8c_ard_3-0-0_089088_2016-11-29_final
2016-11-30 09:16:26	ga_ls8c_ard_3-0-0_089089_2016-11-29_final
2016-11-30 09:16:50	ga_ls8c_ard_3-0-0_089090_2016-11-29_final
2016-11-30 10:46:33	ga_ls8c_ard_3-0-0_105067_2016-11-30_final
2016-11-30 10:46:57	ga_ls8c_ard_3-0-0_105068_2016-11-30_final
2016-11-30 10:47:21	ga_ls8c_ard_3-0-0_105069_2016-11-30_final
2016-11-30 10:47:44	ga_ls8c_ard_3-0-0_105070_2016-11-30_final
2016-11-30 10:48:08	ga_ls8c_ard_3-0-0_105071_2016-11-30_final
2016-11-30 10:48:32	ga_ls8c_ard_3-0-0_105072_2016-11-30_final
2016-11-30 10:48:56	ga_ls8c_ard_3-0-0_105073_2016-11-30_final
2016-11-30 10:49:20	ga_ls8c_ard_3-0-0_105074_2016-11-30_final
2016-11-30 10:49:44	ga_ls8c_ard_3-0-0_105075_2016-11-30_final
2016-11-30 10:50:08	ga_ls8c_ard_3-0-0_105076_2016-11-30_final
2016-11-30 10:50:32	ga_ls8c_ard_3-0-0_105077_2016-11-30_final
2016-11-30 10:50:56	ga_ls8c_ard_3-0-0_105078_2016-11-30_final
2016-11-30 10:51:20	ga_ls8c_ard_3-0-0_105079_2016-11-30_final
2016-11-30 10:51:44	ga_ls8c_ard_3-0-0_105080_2016-11-30_final
2016-11-30 10:52:08	ga_ls8c_ard_3-1-0_105081_2016-11-30_final
2016-11-30 10:52:32	ga_ls8c_ard_3-0-0_105082_2016-11-30_final

Return to ga_ls8c_ard_3 across November 2016 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

2016

November

All days