Search ga_ls8c_ard_3 across 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
2017-01-04 09:38:26	ga_ls8c_ard_3-0-0_094067_2017-01-04_final
2017-01-04 09:40:02	ga_ls8c_ard_3-0-0_094071_2017-01-04_final
2017-01-04 09:40:26	ga_ls8c_ard_3-0-0_094072_2017-01-04_final
2017-01-04 09:40:49	ga_ls8c_ard_3-0-0_094073_2017-01-04_final
2017-01-04 09:41:13	ga_ls8c_ard_3-0-0_094074_2017-01-04_final
2017-01-04 09:41:37	ga_ls8c_ard_3-0-0_094075_2017-01-04_final
2017-01-04 09:42:01	ga_ls8c_ard_3-0-0_094076_2017-01-04_final
2017-01-04 09:42:25	ga_ls8c_ard_3-0-0_094077_2017-01-04_final
2017-01-04 09:42:49	ga_ls8c_ard_3-0-0_094078_2017-01-04_final
2017-01-04 09:43:13	ga_ls8c_ard_3-0-0_094079_2017-01-04_final
2017-01-04 09:43:37	ga_ls8c_ard_3-0-0_094080_2017-01-04_final
2017-01-04 09:44:01	ga_ls8c_ard_3-0-0_094081_2017-01-04_final
2017-01-04 09:44:25	ga_ls8c_ard_3-0-0_094082_2017-01-04_final
2017-01-04 09:44:49	ga_ls8c_ard_3-0-0_094083_2017-01-04_final
2017-01-04 09:45:13	ga_ls8c_ard_3-0-0_094084_2017-01-04_final
2017-01-04 09:45:37	ga_ls8c_ard_3-0-0_094085_2017-01-04_final
2017-01-04 09:46:01	ga_ls8c_ard_3-0-0_094086_2017-01-04_final
2017-01-04 09:46:25	ga_ls8c_ard_3-0-0_094087_2017-01-04_final
2017-01-04 09:46:49	ga_ls8c_ard_3-0-0_094088_2017-01-04_final
2017-01-04 11:17:19	ga_ls8c_ard_3-0-0_110067_2017-01-04_final
2017-01-04 11:17:43	ga_ls8c_ard_3-0-0_110068_2017-01-04_final
2017-01-04 11:18:07	ga_ls8c_ard_3-0-0_110069_2017-01-04_final
2017-01-04 11:18:31	ga_ls8c_ard_3-0-0_110070_2017-01-04_final
2017-01-04 11:18:55	ga_ls8c_ard_3-0-0_110071_2017-01-04_final
2017-01-04 11:19:19	ga_ls8c_ard_3-0-0_110072_2017-01-04_final
2017-01-04 11:19:43	ga_ls8c_ard_3-0-0_110073_2017-01-04_final
2017-01-04 11:20:06	ga_ls8c_ard_3-0-0_110074_2017-01-04_final
2017-01-04 11:20:30	ga_ls8c_ard_3-0-0_110075_2017-01-04_final
2017-01-04 11:20:54	ga_ls8c_ard_3-0-0_110076_2017-01-04_final
2017-01-04 11:21:18	ga_ls8c_ard_3-0-0_110077_2017-01-04_final
2017-01-04 11:21:42	ga_ls8c_ard_3-0-0_110078_2017-01-04_final
2017-01-04 11:22:06	ga_ls8c_ard_3-0-0_110079_2017-01-04_final
2017-01-04 11:22:30	ga_ls8c_ard_3-0-0_110080_2017-01-04_final
2017-01-04 11:22:54	ga_ls8c_ard_3-0-0_110081_2017-01-04_final
2017-01-04 11:23:18	ga_ls8c_ard_3-0-0_110082_2017-01-04_final
2017-01-04 11:23:42	ga_ls8c_ard_3-0-0_110083_2017-01-04_final
2017-01-04 11:24:06	ga_ls8c_ard_3-0-0_110084_2017-01-04_final
2017-01-04 11:24:30	ga_ls8c_ard_3-0-0_110085_2017-01-04_final
2017-01-05 10:21:41	ga_ls8c_ard_3-0-0_101067_2017-01-05_final
2017-01-05 10:22:05	ga_ls8c_ard_3-0-0_101068_2017-01-05_final
2017-01-05 10:22:29	ga_ls8c_ard_3-0-0_101069_2017-01-05_final
2017-01-05 10:22:53	ga_ls8c_ard_3-0-0_101070_2017-01-05_final
2017-01-05 10:23:17	ga_ls8c_ard_3-0-0_101071_2017-01-05_final
2017-01-05 10:23:41	ga_ls8c_ard_3-0-0_101072_2017-01-05_final
2017-01-05 10:24:05	ga_ls8c_ard_3-0-0_101073_2017-01-05_final
2017-01-05 10:24:29	ga_ls8c_ard_3-0-0_101074_2017-01-05_final
2017-01-05 10:24:53	ga_ls8c_ard_3-0-0_101075_2017-01-05_final
2017-01-05 10:25:17	ga_ls8c_ard_3-0-0_101076_2017-01-05_final
2017-01-05 10:25:41	ga_ls8c_ard_3-0-0_101077_2017-01-05_final
2017-01-05 10:26:05	ga_ls8c_ard_3-0-0_101078_2017-01-05_final
2017-01-05 10:26:29	ga_ls8c_ard_3-0-0_101079_2017-01-05_final
2017-01-05 10:26:53	ga_ls8c_ard_3-0-0_101080_2017-01-05_final
2017-01-05 10:27:17	ga_ls8c_ard_3-0-0_101081_2017-01-05_final
2017-01-05 10:27:40	ga_ls8c_ard_3-0-0_101082_2017-01-05_final
2017-01-05 10:28:04	ga_ls8c_ard_3-0-0_101083_2017-01-05_final
2017-01-05 10:28:28	ga_ls8c_ard_3-0-0_101084_2017-01-05_final
2017-01-06 09:26:04	ga_ls8c_ard_3-0-0_092067_2017-01-05_final
2017-01-06 09:26:28	ga_ls8c_ard_3-0-0_092068_2017-01-05_final
2017-01-06 09:27:40	ga_ls8c_ard_3-0-0_092071_2017-01-05_final
2017-01-06 09:28:04	ga_ls8c_ard_3-0-0_092072_2017-01-05_final
2017-01-06 09:28:28	ga_ls8c_ard_3-0-0_092073_2017-01-05_final
2017-01-06 09:28:51	ga_ls8c_ard_3-0-0_092074_2017-01-05_final
2017-01-06 09:29:15	ga_ls8c_ard_3-0-0_092075_2017-01-05_final
2017-01-06 09:29:39	ga_ls8c_ard_3-0-0_092076_2017-01-05_final
2017-01-06 09:30:03	ga_ls8c_ard_3-0-0_092077_2017-01-06_final
2017-01-06 09:30:27	ga_ls8c_ard_3-0-0_092078_2017-01-06_final
2017-01-06 09:30:51	ga_ls8c_ard_3-0-0_092079_2017-01-06_final
2017-01-06 09:31:15	ga_ls8c_ard_3-0-0_092080_2017-01-06_final
2017-01-06 09:31:39	ga_ls8c_ard_3-0-0_092081_2017-01-06_final
2017-01-06 09:32:03	ga_ls8c_ard_3-0-0_092082_2017-01-06_final
2017-01-06 09:32:27	ga_ls8c_ard_3-0-0_092083_2017-01-06_final
2017-01-06 09:32:51	ga_ls8c_ard_3-0-0_092084_2017-01-06_final
2017-01-06 09:33:15	ga_ls8c_ard_3-0-0_092085_2017-01-06_final
2017-01-06 09:33:39	ga_ls8c_ard_3-0-0_092086_2017-01-06_final
2017-01-06 09:34:03	ga_ls8c_ard_3-0-0_092087_2017-01-06_final
2017-01-06 09:34:27	ga_ls8c_ard_3-0-0_092088_2017-01-06_final
2017-01-06 09:34:51	ga_ls8c_ard_3-0-0_092089_2017-01-06_final
2017-01-06 09:35:15	ga_ls8c_ard_3-0-0_092090_2017-01-06_final
2017-01-06 11:04:57	ga_ls8c_ard_3-0-0_108067_2017-01-06_final
2017-01-06 11:05:21	ga_ls8c_ard_3-0-0_108068_2017-01-06_final
2017-01-06 11:05:45	ga_ls8c_ard_3-0-0_108069_2017-01-06_final
2017-01-06 11:06:09	ga_ls8c_ard_3-0-0_108070_2017-01-06_final
2017-01-06 11:06:33	ga_ls8c_ard_3-0-0_108071_2017-01-06_final
2017-01-06 11:06:57	ga_ls8c_ard_3-0-0_108072_2017-01-06_final
2017-01-06 11:07:20	ga_ls8c_ard_3-0-0_108073_2017-01-06_final
2017-01-06 11:07:44	ga_ls8c_ard_3-0-0_108074_2017-01-06_final
2017-01-06 11:08:08	ga_ls8c_ard_3-0-0_108075_2017-01-06_final
2017-01-06 11:08:32	ga_ls8c_ard_3-0-0_108076_2017-01-06_final
2017-01-06 11:08:56	ga_ls8c_ard_3-0-0_108077_2017-01-06_final
2017-01-06 11:09:20	ga_ls8c_ard_3-0-0_108078_2017-01-06_final
2017-01-06 11:09:44	ga_ls8c_ard_3-0-0_108079_2017-01-06_final
2017-01-06 11:10:08	ga_ls8c_ard_3-0-0_108080_2017-01-06_final
2017-01-06 11:10:32	ga_ls8c_ard_3-0-0_108081_2017-01-06_final
2017-01-06 11:10:56	ga_ls8c_ard_3-0-0_108082_2017-01-06_final
2017-01-06 11:11:20	ga_ls8c_ard_3-0-0_108083_2017-01-06_final
2017-01-06 11:11:44	ga_ls8c_ard_3-0-0_108084_2017-01-06_final
2017-01-06 11:12:08	ga_ls8c_ard_3-0-0_108085_2017-01-06_final
2017-03-14 09:56:30	ga_ls8c_ard_3-0-0_097067_2017-03-14_final
2017-03-14 09:56:54	ga_ls8c_ard_3-0-0_097068_2017-03-14_final
2017-03-14 09:57:18	ga_ls8c_ard_3-0-0_097069_2017-03-14_final

Return to ga_ls8c_ard_3 across 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

All months