Search ga_ls8c_ard_3 across April 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

First 100 results (query limit)

Time (local)	Label
2018-04-09 10:02:20	ga_ls8c_ard_3-0-0_098067_2018-04-09_final
2018-04-09 10:02:44	ga_ls8c_ard_3-0-0_098068_2018-04-09_final
2018-04-09 10:03:07	ga_ls8c_ard_3-0-0_098069_2018-04-09_final
2018-04-09 10:03:31	ga_ls8c_ard_3-0-0_098070_2018-04-09_final
2018-04-09 10:03:55	ga_ls8c_ard_3-0-0_098071_2018-04-09_final
2018-04-09 10:04:19	ga_ls8c_ard_3-0-0_098072_2018-04-09_final
2018-04-09 10:04:43	ga_ls8c_ard_3-0-0_098073_2018-04-09_final
2018-04-09 10:05:07	ga_ls8c_ard_3-0-0_098074_2018-04-09_final
2018-04-09 10:05:31	ga_ls8c_ard_3-0-0_098075_2018-04-09_final
2018-04-09 10:05:55	ga_ls8c_ard_3-0-0_098076_2018-04-09_final
2018-04-09 10:06:19	ga_ls8c_ard_3-0-0_098077_2018-04-09_final
2018-04-09 10:06:43	ga_ls8c_ard_3-0-0_098078_2018-04-09_final
2018-04-09 10:07:07	ga_ls8c_ard_3-0-0_098079_2018-04-09_final
2018-04-09 10:07:31	ga_ls8c_ard_3-0-0_098080_2018-04-09_final
2018-04-09 10:07:55	ga_ls8c_ard_3-0-0_098081_2018-04-09_final
2018-04-09 10:08:19	ga_ls8c_ard_3-0-0_098082_2018-04-09_final
2018-04-09 10:08:43	ga_ls8c_ard_3-0-0_098083_2018-04-09_final
2018-04-09 10:09:07	ga_ls8c_ard_3-0-0_098084_2018-04-09_final
2018-04-09 10:09:30	ga_ls8c_ard_3-0-0_098085_2018-04-09_final
2018-04-09 10:09:54	ga_ls8c_ard_3-0-0_098086_2018-04-09_final
2018-04-10 09:09:29	ga_ls8c_ard_3-0-0_089074_2018-04-09_final
2018-04-10 09:09:53	ga_ls8c_ard_3-0-0_089075_2018-04-09_final
2018-04-10 09:10:17	ga_ls8c_ard_3-0-0_089076_2018-04-09_final
2018-04-10 09:10:41	ga_ls8c_ard_3-0-0_089077_2018-04-09_final
2018-04-10 09:11:05	ga_ls8c_ard_3-0-0_089078_2018-04-09_final
2018-04-10 09:11:29	ga_ls8c_ard_3-0-0_089079_2018-04-09_final
2018-04-10 09:11:53	ga_ls8c_ard_3-0-0_089080_2018-04-09_final
2018-04-10 09:12:17	ga_ls8c_ard_3-0-0_089081_2018-04-09_final
2018-04-10 09:12:41	ga_ls8c_ard_3-0-0_089082_2018-04-09_final
2018-04-10 09:13:05	ga_ls8c_ard_3-0-0_089083_2018-04-09_final
2018-04-10 09:13:29	ga_ls8c_ard_3-0-0_089084_2018-04-09_final
2018-04-10 09:13:53	ga_ls8c_ard_3-0-0_089085_2018-04-09_final
2018-04-10 09:14:17	ga_ls8c_ard_3-0-0_089086_2018-04-09_final
2018-04-10 09:14:41	ga_ls8c_ard_3-0-0_089087_2018-04-09_final
2018-04-10 09:15:05	ga_ls8c_ard_3-0-0_089088_2018-04-09_final
2018-04-10 09:15:28	ga_ls8c_ard_3-0-0_089089_2018-04-09_final
2018-04-10 09:15:52	ga_ls8c_ard_3-0-0_089090_2018-04-09_final
2018-04-10 10:45:35	ga_ls8c_ard_3-0-0_105067_2018-04-10_final
2018-04-10 10:45:59	ga_ls8c_ard_3-0-0_105068_2018-04-10_final
2018-04-10 10:46:23	ga_ls8c_ard_3-0-0_105069_2018-04-10_final
2018-04-10 10:46:46	ga_ls8c_ard_3-0-0_105070_2018-04-10_final
2018-04-10 10:47:10	ga_ls8c_ard_3-0-0_105071_2018-04-10_final
2018-04-10 10:47:34	ga_ls8c_ard_3-0-0_105072_2018-04-10_final
2018-04-10 10:47:58	ga_ls8c_ard_3-0-0_105073_2018-04-10_final
2018-04-10 10:48:22	ga_ls8c_ard_3-0-0_105074_2018-04-10_final
2018-04-29 09:37:25	ga_ls8c_ard_3-0-0_094067_2018-04-29_final
2018-04-29 09:39:01	ga_ls8c_ard_3-0-0_094071_2018-04-29_final
2018-04-29 09:39:25	ga_ls8c_ard_3-0-0_094072_2018-04-29_final
2018-04-29 09:39:48	ga_ls8c_ard_3-0-0_094073_2018-04-29_final
2018-04-29 09:40:12	ga_ls8c_ard_3-0-0_094074_2018-04-29_final
2018-04-29 09:40:36	ga_ls8c_ard_3-0-0_094075_2018-04-29_final
2018-04-29 09:41:00	ga_ls8c_ard_3-0-0_094076_2018-04-29_final
2018-04-29 09:41:24	ga_ls8c_ard_3-0-0_094077_2018-04-29_final
2018-04-29 09:41:48	ga_ls8c_ard_3-0-0_094078_2018-04-29_final
2018-04-29 09:42:12	ga_ls8c_ard_3-0-0_094079_2018-04-29_final
2018-04-29 09:42:36	ga_ls8c_ard_3-0-0_094080_2018-04-29_final
2018-04-29 09:43:00	ga_ls8c_ard_3-0-0_094081_2018-04-29_final
2018-04-29 09:43:24	ga_ls8c_ard_3-0-0_094082_2018-04-29_final
2018-04-29 09:43:48	ga_ls8c_ard_3-0-0_094083_2018-04-29_final
2018-04-29 09:44:12	ga_ls8c_ard_3-0-0_094084_2018-04-29_final
2018-04-29 09:44:36	ga_ls8c_ard_3-0-0_094085_2018-04-29_final
2018-04-29 09:45:00	ga_ls8c_ard_3-0-0_094086_2018-04-29_final
2018-04-29 09:45:24	ga_ls8c_ard_3-0-0_094087_2018-04-29_final
2018-04-29 09:45:48	ga_ls8c_ard_3-0-0_094088_2018-04-29_final
2018-04-29 11:16:18	ga_ls8c_ard_3-0-0_110067_2018-04-29_final
2018-04-29 11:16:42	ga_ls8c_ard_3-0-0_110068_2018-04-29_final
2018-04-29 11:17:06	ga_ls8c_ard_3-0-0_110069_2018-04-29_final
2018-04-29 11:17:30	ga_ls8c_ard_3-0-0_110070_2018-04-29_final
2018-04-29 11:17:54	ga_ls8c_ard_3-0-0_110071_2018-04-29_final
2018-04-29 11:18:18	ga_ls8c_ard_3-0-0_110072_2018-04-29_final
2018-04-29 11:18:41	ga_ls8c_ard_3-0-0_110073_2018-04-29_final
2018-04-29 11:19:05	ga_ls8c_ard_3-0-0_110074_2018-04-29_final
2018-04-29 11:19:29	ga_ls8c_ard_3-0-0_110075_2018-04-29_final
2018-04-29 11:19:53	ga_ls8c_ard_3-0-0_110076_2018-04-29_final
2018-04-29 11:20:17	ga_ls8c_ard_3-0-0_110077_2018-04-29_final
2018-04-29 11:20:41	ga_ls8c_ard_3-0-0_110078_2018-04-29_final
2018-04-29 11:21:05	ga_ls8c_ard_3-0-0_110079_2018-04-29_final
2018-04-29 11:21:29	ga_ls8c_ard_3-0-0_110080_2018-04-29_final
2018-04-29 11:21:53	ga_ls8c_ard_3-0-0_110081_2018-04-29_final
2018-04-29 11:22:17	ga_ls8c_ard_3-0-0_110082_2018-04-29_final
2018-04-29 11:22:41	ga_ls8c_ard_3-0-0_110083_2018-04-29_final
2018-04-29 11:23:05	ga_ls8c_ard_3-0-0_110084_2018-04-29_final
2018-04-29 11:23:29	ga_ls8c_ard_3-0-0_110085_2018-04-29_final
2018-04-30 10:20:40	ga_ls8c_ard_3-0-0_101067_2018-04-30_final
2018-04-30 10:21:04	ga_ls8c_ard_3-0-0_101068_2018-04-30_final
2018-04-30 10:21:28	ga_ls8c_ard_3-0-0_101069_2018-04-30_final
2018-04-30 10:21:52	ga_ls8c_ard_3-0-0_101070_2018-04-30_final
2018-04-30 10:22:16	ga_ls8c_ard_3-0-0_101071_2018-04-30_final
2018-04-30 10:22:40	ga_ls8c_ard_3-0-0_101072_2018-04-30_final
2018-04-30 10:23:04	ga_ls8c_ard_3-0-0_101073_2018-04-30_final
2018-04-30 10:23:28	ga_ls8c_ard_3-0-0_101074_2018-04-30_final
2018-04-30 10:23:51	ga_ls8c_ard_3-0-0_101075_2018-04-30_final
2018-04-30 10:24:15	ga_ls8c_ard_3-0-0_101076_2018-04-30_final
2018-04-30 10:24:39	ga_ls8c_ard_3-0-0_101077_2018-04-30_final
2018-04-30 10:25:03	ga_ls8c_ard_3-0-0_101078_2018-04-30_final
2018-04-30 10:25:27	ga_ls8c_ard_3-0-0_101079_2018-04-30_final
2018-04-30 10:25:51	ga_ls8c_ard_3-0-0_101080_2018-04-30_final
2018-04-30 10:26:15	ga_ls8c_ard_3-0-0_101081_2018-04-30_final
2018-04-30 10:26:39	ga_ls8c_ard_3-0-0_101082_2018-04-30_final
2018-04-30 10:27:03	ga_ls8c_ard_3-0-0_101083_2018-04-30_final

Return to ga_ls8c_ard_3 across April 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

April

All days