Search ga_ls8c_ard_3 across December 2017

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
2017-12-02 10:03:06	ga_ls8c_ard_3-0-0_098067_2017-12-02_final
2017-12-02 10:03:30	ga_ls8c_ard_3-0-0_098068_2017-12-02_final
2017-12-02 10:03:54	ga_ls8c_ard_3-0-0_098069_2017-12-02_final
2017-12-02 10:04:17	ga_ls8c_ard_3-0-0_098070_2017-12-02_final
2017-12-02 10:04:41	ga_ls8c_ard_3-0-0_098071_2017-12-02_final
2017-12-02 10:05:05	ga_ls8c_ard_3-0-0_098072_2017-12-02_final
2017-12-02 10:05:29	ga_ls8c_ard_3-0-0_098073_2017-12-02_final
2017-12-02 10:05:53	ga_ls8c_ard_3-0-0_098074_2017-12-02_final
2017-12-02 10:06:17	ga_ls8c_ard_3-0-0_098075_2017-12-02_final
2017-12-02 10:06:41	ga_ls8c_ard_3-0-0_098076_2017-12-02_final
2017-12-02 10:07:05	ga_ls8c_ard_3-0-0_098077_2017-12-02_final
2017-12-02 10:07:29	ga_ls8c_ard_3-0-0_098078_2017-12-02_final
2017-12-02 10:07:53	ga_ls8c_ard_3-0-0_098079_2017-12-02_final
2017-12-02 10:08:17	ga_ls8c_ard_3-0-0_098080_2017-12-02_final
2017-12-02 10:08:41	ga_ls8c_ard_3-0-0_098081_2017-12-02_final
2017-12-02 10:09:05	ga_ls8c_ard_3-0-0_098082_2017-12-02_final
2017-12-02 10:09:29	ga_ls8c_ard_3-0-0_098083_2017-12-02_final
2017-12-02 10:09:53	ga_ls8c_ard_3-0-0_098084_2017-12-02_final
2017-12-02 10:10:17	ga_ls8c_ard_3-0-0_098085_2017-12-02_final
2017-12-02 10:10:41	ga_ls8c_ard_3-0-0_098086_2017-12-02_final
2017-12-02 11:41:59	ga_ls8c_ard_3-0-0_114067_2017-12-02_final
2017-12-02 11:44:46	ga_ls8c_ard_3-0-0_114074_2017-12-02_final
2017-12-02 11:45:10	ga_ls8c_ard_3-0-0_114075_2017-12-02_final
2017-12-02 11:45:34	ga_ls8c_ard_3-0-0_114076_2017-12-02_final
2017-12-02 11:45:58	ga_ls8c_ard_3-0-0_114077_2017-12-02_final
2017-12-02 11:46:22	ga_ls8c_ard_3-0-0_114078_2017-12-02_final
2017-12-02 11:46:46	ga_ls8c_ard_3-0-0_114079_2017-12-02_final
2017-12-02 11:47:10	ga_ls8c_ard_3-0-0_114080_2017-12-02_final
2017-12-02 11:47:34	ga_ls8c_ard_3-0-0_114081_2017-12-02_final
2017-12-03 09:10:16	ga_ls8c_ard_3-0-0_089074_2017-12-02_final
2017-12-03 09:10:40	ga_ls8c_ard_3-0-0_089075_2017-12-02_final
2017-12-03 09:11:04	ga_ls8c_ard_3-0-0_089076_2017-12-02_final
2017-12-03 09:11:28	ga_ls8c_ard_3-0-0_089077_2017-12-02_final
2017-12-03 09:11:52	ga_ls8c_ard_3-0-0_089078_2017-12-02_final
2017-12-03 09:12:16	ga_ls8c_ard_3-0-0_089079_2017-12-02_final
2017-12-03 09:12:40	ga_ls8c_ard_3-0-0_089080_2017-12-02_final
2017-12-03 09:13:04	ga_ls8c_ard_3-0-0_089081_2017-12-02_final
2017-12-03 09:13:28	ga_ls8c_ard_3-0-0_089082_2017-12-02_final
2017-12-03 09:13:51	ga_ls8c_ard_3-0-0_089083_2017-12-02_final
2017-12-03 09:14:15	ga_ls8c_ard_3-0-0_089084_2017-12-02_final
2017-12-03 09:14:39	ga_ls8c_ard_3-0-0_089085_2017-12-02_final
2017-12-03 09:15:03	ga_ls8c_ard_3-0-0_089086_2017-12-02_final
2017-12-03 09:15:27	ga_ls8c_ard_3-0-0_089087_2017-12-02_final
2017-12-03 09:15:51	ga_ls8c_ard_3-0-0_089088_2017-12-02_final
2017-12-03 09:16:15	ga_ls8c_ard_3-0-0_089089_2017-12-02_final
2017-12-03 09:16:39	ga_ls8c_ard_3-0-0_089090_2017-12-02_final
2017-12-03 10:46:21	ga_ls8c_ard_3-0-0_105067_2017-12-03_final
2017-12-03 10:46:45	ga_ls8c_ard_3-0-0_105068_2017-12-03_final
2017-12-03 10:47:09	ga_ls8c_ard_3-0-0_105069_2017-12-03_final
2017-12-03 10:47:33	ga_ls8c_ard_3-0-0_105070_2017-12-03_final
2017-12-03 10:47:57	ga_ls8c_ard_3-0-0_105071_2017-12-03_final
2017-12-03 10:48:21	ga_ls8c_ard_3-0-0_105072_2017-12-03_final
2017-12-03 10:48:45	ga_ls8c_ard_3-0-0_105073_2017-12-03_final
2017-12-03 10:49:09	ga_ls8c_ard_3-0-0_105074_2017-12-03_final
2017-12-03 10:49:33	ga_ls8c_ard_3-0-0_105075_2017-12-03_final
2017-12-03 10:49:57	ga_ls8c_ard_3-0-0_105076_2017-12-03_final
2017-12-03 10:50:21	ga_ls8c_ard_3-0-0_105077_2017-12-03_final
2017-12-03 10:50:45	ga_ls8c_ard_3-0-0_105078_2017-12-03_final
2017-12-03 10:51:09	ga_ls8c_ard_3-0-0_105079_2017-12-03_final
2017-12-03 10:51:33	ga_ls8c_ard_3-0-0_105080_2017-12-03_final
2017-12-03 10:51:57	ga_ls8c_ard_3-0-0_105081_2017-12-03_final
2017-12-03 10:52:21	ga_ls8c_ard_3-0-0_105082_2017-12-03_final
2017-12-03 10:52:44	ga_ls8c_ard_3-0-0_105083_2017-12-03_final
2017-12-18 10:03:08	ga_ls8c_ard_3-0-0_098067_2017-12-18_final
2017-12-18 10:03:32	ga_ls8c_ard_3-0-0_098068_2017-12-18_final
2017-12-18 10:03:56	ga_ls8c_ard_3-0-0_098069_2017-12-18_final
2017-12-18 10:04:20	ga_ls8c_ard_3-0-0_098070_2017-12-18_final
2017-12-18 10:04:44	ga_ls8c_ard_3-0-0_098071_2017-12-18_final
2017-12-18 10:05:08	ga_ls8c_ard_3-0-0_098072_2017-12-18_final
2017-12-18 10:05:32	ga_ls8c_ard_3-0-0_098073_2017-12-18_final
2017-12-18 10:05:56	ga_ls8c_ard_3-0-0_098074_2017-12-18_final
2017-12-18 10:06:20	ga_ls8c_ard_3-0-0_098075_2017-12-18_final
2017-12-18 10:06:44	ga_ls8c_ard_3-0-0_098076_2017-12-18_final
2017-12-18 10:07:08	ga_ls8c_ard_3-0-0_098077_2017-12-18_final
2017-12-18 10:07:31	ga_ls8c_ard_3-0-0_098078_2017-12-18_final
2017-12-18 10:07:55	ga_ls8c_ard_3-0-0_098079_2017-12-18_final
2017-12-18 10:08:19	ga_ls8c_ard_3-0-0_098080_2017-12-18_final
2017-12-18 10:08:43	ga_ls8c_ard_3-0-0_098081_2017-12-18_final
2017-12-18 10:09:07	ga_ls8c_ard_3-0-0_098082_2017-12-18_final
2017-12-18 10:09:31	ga_ls8c_ard_3-0-0_098083_2017-12-18_final
2017-12-18 10:09:55	ga_ls8c_ard_3-0-0_098084_2017-12-18_final
2017-12-18 10:10:19	ga_ls8c_ard_3-0-0_098085_2017-12-18_final
2017-12-18 10:10:43	ga_ls8c_ard_3-0-0_098086_2017-12-18_final
2017-12-19 09:10:19	ga_ls8c_ard_3-0-0_089074_2017-12-18_final
2017-12-19 09:10:43	ga_ls8c_ard_3-0-0_089075_2017-12-18_final
2017-12-19 09:11:07	ga_ls8c_ard_3-0-0_089076_2017-12-18_final
2017-12-19 09:11:30	ga_ls8c_ard_3-0-0_089077_2017-12-18_final
2017-12-19 09:11:54	ga_ls8c_ard_3-0-0_089078_2017-12-18_final
2017-12-19 09:12:18	ga_ls8c_ard_3-0-0_089079_2017-12-18_final
2017-12-19 09:12:42	ga_ls8c_ard_3-0-0_089080_2017-12-18_final
2017-12-19 09:13:06	ga_ls8c_ard_3-0-0_089081_2017-12-18_final
2017-12-19 09:13:30	ga_ls8c_ard_3-0-0_089082_2017-12-18_final
2017-12-19 09:13:54	ga_ls8c_ard_3-0-0_089083_2017-12-18_final
2017-12-19 09:14:18	ga_ls8c_ard_3-0-0_089084_2017-12-18_final
2017-12-19 09:14:42	ga_ls8c_ard_3-0-0_089085_2017-12-18_final
2017-12-19 09:15:06	ga_ls8c_ard_3-0-0_089086_2017-12-18_final
2017-12-19 09:15:30	ga_ls8c_ard_3-0-0_089087_2017-12-18_final
2017-12-19 09:15:54	ga_ls8c_ard_3-0-0_089088_2017-12-18_final
2017-12-19 09:16:18	ga_ls8c_ard_3-0-0_089089_2017-12-18_final
2017-12-19 09:16:42	ga_ls8c_ard_3-0-0_089090_2017-12-18_final

Return to ga_ls8c_ard_3 across December 2017 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

2017

December

All days