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
2016-11-09 10:28:00	ga_ls8c_ard_3-0-0_102067_2016-11-09_final
2016-11-09 10:28:24	ga_ls8c_ard_3-0-0_102068_2016-11-09_final
2016-11-09 10:28:48	ga_ls8c_ard_3-0-0_102069_2016-11-09_final
2016-11-09 10:29:12	ga_ls8c_ard_3-0-0_102070_2016-11-09_final
2016-11-09 10:29:36	ga_ls8c_ard_3-0-0_102071_2016-11-09_final
2016-11-09 10:30:00	ga_ls8c_ard_3-0-0_102072_2016-11-09_final
2016-11-09 10:30:24	ga_ls8c_ard_3-0-0_102073_2016-11-09_final
2016-11-09 10:30:47	ga_ls8c_ard_3-0-0_102074_2016-11-09_final
2016-11-09 10:31:11	ga_ls8c_ard_3-0-0_102075_2016-11-09_final
2016-11-09 10:31:35	ga_ls8c_ard_3-0-0_102076_2016-11-09_final
2016-11-09 10:31:59	ga_ls8c_ard_3-0-0_102077_2016-11-09_final
2016-11-09 10:32:23	ga_ls8c_ard_3-0-0_102078_2016-11-09_final
2016-11-09 10:32:47	ga_ls8c_ard_3-0-0_102079_2016-11-09_final
2016-11-09 10:33:11	ga_ls8c_ard_3-0-0_102080_2016-11-09_final
2016-11-09 10:33:35	ga_ls8c_ard_3-0-0_102081_2016-11-09_final
2016-11-09 10:33:59	ga_ls8c_ard_3-0-0_102082_2016-11-09_final
2016-11-09 10:34:23	ga_ls8c_ard_3-0-0_102083_2016-11-09_final
2016-11-10 09:32:22	ga_ls8c_ard_3-0-0_093067_2016-11-10_final
2016-11-10 09:32:46	ga_ls8c_ard_3-0-0_093068_2016-11-10_final
2016-11-10 09:33:58	ga_ls8c_ard_3-0-0_093071_2016-11-10_final
2016-11-10 09:34:22	ga_ls8c_ard_3-0-0_093072_2016-11-10_final
2016-11-10 09:34:46	ga_ls8c_ard_3-0-0_093073_2016-11-10_final
2016-11-10 09:35:10	ga_ls8c_ard_3-0-0_093074_2016-11-10_final
2016-11-10 09:35:34	ga_ls8c_ard_3-0-0_093075_2016-11-10_final
2016-11-10 09:35:58	ga_ls8c_ard_3-0-0_093076_2016-11-10_final
2016-11-10 09:36:22	ga_ls8c_ard_3-0-0_093077_2016-11-10_final
2016-11-10 09:36:46	ga_ls8c_ard_3-0-0_093078_2016-11-10_final
2016-11-10 09:37:10	ga_ls8c_ard_3-0-0_093079_2016-11-10_final
2016-11-10 09:37:34	ga_ls8c_ard_3-0-0_093080_2016-11-10_final
2016-11-10 09:37:58	ga_ls8c_ard_3-0-0_093081_2016-11-10_final
2016-11-10 09:38:21	ga_ls8c_ard_3-0-0_093082_2016-11-10_final
2016-11-10 09:38:45	ga_ls8c_ard_3-0-0_093083_2016-11-10_final
2016-11-10 09:39:09	ga_ls8c_ard_3-0-0_093084_2016-11-10_final
2016-11-10 09:39:33	ga_ls8c_ard_3-0-0_093085_2016-11-10_final
2016-11-10 09:39:57	ga_ls8c_ard_3-0-0_093086_2016-11-10_final
2016-11-10 09:40:21	ga_ls8c_ard_3-0-0_093087_2016-11-10_final
2016-11-10 09:40:45	ga_ls8c_ard_3-0-0_093088_2016-11-10_final
2016-11-10 11:11:15	ga_ls8c_ard_3-0-0_109067_2016-11-10_final
2016-11-10 11:11:39	ga_ls8c_ard_3-0-0_109068_2016-11-10_final
2016-11-10 11:12:03	ga_ls8c_ard_3-0-0_109069_2016-11-10_final
2016-11-10 11:12:27	ga_ls8c_ard_3-0-0_109070_2016-11-10_final
2016-11-10 11:12:51	ga_ls8c_ard_3-0-0_109071_2016-11-10_final
2016-11-10 11:13:15	ga_ls8c_ard_3-0-0_109072_2016-11-10_final
2016-11-10 11:13:39	ga_ls8c_ard_3-0-0_109073_2016-11-10_final
2016-11-10 11:14:03	ga_ls8c_ard_3-0-0_109074_2016-11-10_final
2016-11-10 11:14:27	ga_ls8c_ard_3-0-0_109075_2016-11-10_final
2016-11-10 11:14:51	ga_ls8c_ard_3-0-0_109076_2016-11-10_final
2016-11-10 11:15:15	ga_ls8c_ard_3-0-0_109077_2016-11-10_final
2016-11-10 11:15:39	ga_ls8c_ard_3-0-0_109078_2016-11-10_final
2016-11-10 11:16:03	ga_ls8c_ard_3-0-0_109079_2016-11-10_final
2016-11-10 11:16:27	ga_ls8c_ard_3-0-0_109080_2016-11-10_final
2016-11-10 11:16:51	ga_ls8c_ard_3-0-0_109081_2016-11-10_final
2016-11-10 11:17:14	ga_ls8c_ard_3-0-0_109082_2016-11-10_final
2016-11-10 11:17:38	ga_ls8c_ard_3-0-0_109083_2016-11-10_final
2016-11-10 11:18:02	ga_ls8c_ard_3-0-0_109084_2016-11-10_final
2016-11-10 11:18:26	ga_ls8c_ard_3-0-0_109085_2016-11-10_final
2016-11-11 08:42:44	ga_ls8c_ard_3-2-1_084082_2016-11-10_final
2016-11-11 10:15:38	ga_ls8c_ard_3-0-0_100067_2016-11-11_final
2016-11-11 10:16:02	ga_ls8c_ard_3-0-0_100068_2016-11-11_final
2016-11-11 10:16:26	ga_ls8c_ard_3-0-0_100069_2016-11-11_final
2016-11-11 10:16:50	ga_ls8c_ard_3-0-0_100070_2016-11-11_final
2016-11-11 10:17:14	ga_ls8c_ard_3-0-0_100071_2016-11-11_final
2016-11-11 10:17:38	ga_ls8c_ard_3-0-0_100072_2016-11-11_final
2016-11-11 10:18:02	ga_ls8c_ard_3-0-0_100073_2016-11-11_final
2016-11-11 10:18:26	ga_ls8c_ard_3-0-0_100074_2016-11-11_final
2016-11-11 10:18:50	ga_ls8c_ard_3-0-0_100075_2016-11-11_final
2016-11-11 10:19:13	ga_ls8c_ard_3-0-0_100076_2016-11-11_final
2016-11-11 10:19:37	ga_ls8c_ard_3-0-0_100077_2016-11-11_final
2016-11-11 10:20:01	ga_ls8c_ard_3-0-0_100078_2016-11-11_final
2016-11-11 10:20:25	ga_ls8c_ard_3-0-0_100079_2016-11-11_final
2016-11-11 10:20:49	ga_ls8c_ard_3-0-0_100080_2016-11-11_final
2016-11-11 10:21:13	ga_ls8c_ard_3-0-0_100081_2016-11-11_final
2016-11-11 10:21:37	ga_ls8c_ard_3-0-0_100082_2016-11-11_final
2016-11-11 10:22:01	ga_ls8c_ard_3-0-0_100083_2016-11-11_final
2016-11-11 10:22:25	ga_ls8c_ard_3-0-0_100084_2016-11-11_final
2016-11-11 10:22:49	ga_ls8c_ard_3-0-0_100085_2016-11-11_final
2016-11-11 11:57:19	ga_ls8c_ard_3-0-0_116074_2016-11-11_final
2016-11-11 11:57:43	ga_ls8c_ard_3-0-0_116075_2016-11-11_final
2016-11-11 11:58:07	ga_ls8c_ard_3-0-0_116076_2016-11-11_final
2016-11-11 11:58:30	ga_ls8c_ard_3-0-0_116077_2016-11-11_final
2016-11-11 11:58:54	ga_ls8c_ard_3-0-0_116078_2016-11-11_final
2016-11-12 09:20:25	ga_ls8c_ard_3-0-0_091068_2016-11-11_final
2016-11-23 09:06:17	ga_ls8c_ard_3-0-0_088079_2016-11-22_final
2016-11-23 09:06:41	ga_ls8c_ard_3-0-0_088080_2016-11-22_final
2016-11-23 09:07:04	ga_ls8c_ard_3-1-0_088081_2016-11-22_final
2016-11-23 09:07:28	ga_ls8c_ard_3-0-0_088082_2016-11-22_final
2016-11-23 09:07:52	ga_ls8c_ard_3-0-0_088083_2016-11-22_final
2016-11-23 09:08:16	ga_ls8c_ard_3-0-0_088084_2016-11-22_final
2016-11-24 09:44:45	ga_ls8c_ard_3-0-0_095067_2016-11-24_final
2016-11-24 09:45:57	ga_ls8c_ard_3-0-0_095070_2016-11-24_final
2016-11-24 09:46:21	ga_ls8c_ard_3-0-0_095071_2016-11-24_final
2016-11-24 09:46:45	ga_ls8c_ard_3-0-0_095072_2016-11-24_final
2016-11-24 09:47:09	ga_ls8c_ard_3-0-0_095073_2016-11-24_final
2016-11-24 09:47:33	ga_ls8c_ard_3-0-0_095074_2016-11-24_final
2016-11-24 09:47:56	ga_ls8c_ard_3-0-0_095075_2016-11-24_final
2016-11-24 09:48:20	ga_ls8c_ard_3-0-0_095076_2016-11-24_final
2016-11-24 09:48:44	ga_ls8c_ard_3-0-0_095077_2016-11-24_final
2016-11-24 09:49:08	ga_ls8c_ard_3-0-0_095078_2016-11-24_final
2016-11-24 09:49:32	ga_ls8c_ard_3-0-0_095079_2016-11-24_final
2016-11-24 09:49:56	ga_ls8c_ard_3-0-0_095080_2016-11-24_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

2016

November

All days