Search ga_ls8c_ard_3 whole collection

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
2018-10-24 11:07:50	ga_ls8c_ard_3-0-0_108075_2018-10-24_final
2018-10-24 11:08:14	ga_ls8c_ard_3-0-0_108076_2018-10-24_final
2018-10-24 11:08:38	ga_ls8c_ard_3-0-0_108077_2018-10-24_final
2018-10-24 11:09:01	ga_ls8c_ard_3-0-0_108078_2018-10-24_final
2018-10-24 11:09:25	ga_ls8c_ard_3-0-0_108079_2018-10-24_final
2018-10-24 11:09:49	ga_ls8c_ard_3-0-0_108080_2018-10-24_final
2018-10-24 11:10:13	ga_ls8c_ard_3-0-0_108081_2018-10-24_final
2018-10-26 10:58:40	ga_ls8c_ard_3-0-0_106083_2018-10-26_final
2018-10-26 10:59:04	ga_ls8c_ard_3-0-0_106084_2018-10-26_final
2018-11-18 11:03:18	ga_ls8c_ard_3-0-0_107079_2018-11-18_final
2018-11-18 11:03:42	ga_ls8c_ard_3-0-0_107080_2018-11-18_final
2018-11-18 11:04:06	ga_ls8c_ard_3-0-0_107081_2018-11-18_final
2018-11-18 11:04:30	ga_ls8c_ard_3-1-0_107082_2018-11-18_final
2018-11-18 11:04:53	ga_ls8c_ard_3-0-0_107083_2018-11-18_final
2018-11-18 11:05:17	ga_ls8c_ard_3-0-0_107084_2018-11-18_final
2018-11-18 11:05:41	ga_ls8c_ard_3-0-0_107085_2018-11-18_final
2018-11-25 11:07:52	ga_ls8c_ard_3-0-0_108075_2018-11-25_final
2018-11-25 11:08:16	ga_ls8c_ard_3-0-0_108076_2018-11-25_final
2018-11-25 11:08:40	ga_ls8c_ard_3-0-0_108077_2018-11-25_final
2018-11-25 11:09:04	ga_ls8c_ard_3-0-0_108078_2018-11-25_final
2018-11-25 11:09:28	ga_ls8c_ard_3-0-0_108079_2018-11-25_final
2018-11-25 11:09:52	ga_ls8c_ard_3-0-0_108080_2018-11-25_final
2018-11-25 11:10:16	ga_ls8c_ard_3-0-0_108081_2018-11-25_final
2018-11-27 10:58:42	ga_ls8c_ard_3-0-0_106083_2018-11-27_final
2018-11-27 10:59:06	ga_ls8c_ard_3-0-0_106084_2018-11-27_final
2018-12-11 11:07:49	ga_ls8c_ard_3-0-0_108075_2018-12-11_final
2018-12-11 11:08:13	ga_ls8c_ard_3-0-0_108076_2018-12-11_final
2018-12-11 11:08:37	ga_ls8c_ard_3-0-0_108077_2018-12-11_final
2018-12-11 11:09:01	ga_ls8c_ard_3-0-0_108078_2018-12-11_final
2018-12-11 11:09:25	ga_ls8c_ard_3-0-0_108079_2018-12-11_final
2018-12-11 11:09:49	ga_ls8c_ard_3-0-0_108080_2018-12-11_final
2018-12-11 11:10:13	ga_ls8c_ard_3-0-0_108081_2018-12-11_final
2018-12-13 10:58:39	ga_ls8c_ard_3-0-0_106083_2018-12-13_final
2018-12-13 10:59:03	ga_ls8c_ard_3-0-0_106084_2018-12-13_final
2019-01-05 11:03:37	ga_ls8c_ard_3-0-0_107080_2019-01-05_final
2019-01-05 11:04:01	ga_ls8c_ard_3-0-0_107081_2019-01-05_final
2019-01-05 11:04:25	ga_ls8c_ard_3-1-0_107082_2019-01-05_final
2019-01-05 11:04:49	ga_ls8c_ard_3-0-0_107083_2019-01-05_final
2019-01-05 11:05:13	ga_ls8c_ard_3-0-0_107084_2019-01-05_final
2019-01-05 11:05:37	ga_ls8c_ard_3-0-0_107085_2019-01-05_final
2019-06-28 11:12:25	ga_ls8c_ard_3-1-0_109071_2019-06-28_final
2019-06-28 11:12:49	ga_ls8c_ard_3-1-0_109072_2019-06-28_final
2019-06-28 11:13:13	ga_ls8c_ard_3-1-0_109073_2019-06-28_final
2019-06-28 11:13:37	ga_ls8c_ard_3-1-0_109074_2019-06-28_final
2019-06-28 11:14:01	ga_ls8c_ard_3-1-0_109075_2019-06-28_final
2019-06-28 11:14:25	ga_ls8c_ard_3-1-0_109076_2019-06-28_final
2019-09-27 10:59:07	ga_ls8c_ard_3-1-0_106083_2019-09-27_final
2019-09-27 10:59:31	ga_ls8c_ard_3-1-0_106084_2019-09-27_final
2021-09-05 11:13:10	ga_ls8c_ard_3-2-0_109072_2021-09-05_final
2021-09-05 11:13:34	ga_ls8c_ard_3-2-0_109073_2021-09-05_final
2021-09-19 11:23:35	ga_ls8c_ard_3-2-0_111067_2021-09-19_final
2021-09-23 11:03:39	ga_ls8c_ard_3-2-0_107079_2021-09-23_final
2021-09-23 11:04:03	ga_ls8c_ard_3-2-0_107080_2021-09-23_final
2021-09-23 11:04:27	ga_ls8c_ard_3-2-0_107081_2021-09-23_final
2021-09-23 11:04:51	ga_ls8c_ard_3-2-0_107082_2021-09-23_final
2021-09-23 11:05:15	ga_ls8c_ard_3-2-0_107083_2021-09-23_final
2021-09-23 11:05:39	ga_ls8c_ard_3-2-0_107084_2021-09-23_final
2021-09-23 11:06:03	ga_ls8c_ard_3-2-0_107085_2021-09-23_final
2021-10-14 11:17:32	ga_ls8c_ard_3-2-0_110067_2021-10-14_final
2021-10-14 11:17:56	ga_ls8c_ard_3-2-0_110068_2021-10-14_final
2021-10-14 11:18:20	ga_ls8c_ard_3-2-0_110069_2021-10-14_final
2021-10-14 11:18:44	ga_ls8c_ard_3-2-0_110070_2021-10-14_final
2021-10-14 11:19:08	ga_ls8c_ard_3-2-0_110071_2021-10-14_final
2021-10-16 11:08:22	ga_ls8c_ard_3-2-0_108075_2021-10-16_final
2021-10-16 11:08:46	ga_ls8c_ard_3-2-0_108076_2021-10-16_final
2021-10-16 11:09:10	ga_ls8c_ard_3-2-0_108077_2021-10-16_final
2021-10-16 11:09:34	ga_ls8c_ard_3-2-0_108078_2021-10-16_final
2021-10-16 11:09:58	ga_ls8c_ard_3-2-0_108079_2021-10-16_final
2021-10-16 11:10:22	ga_ls8c_ard_3-2-0_108080_2021-10-16_final
2021-10-16 11:10:46	ga_ls8c_ard_3-2-0_108081_2021-10-16_final
2021-10-18 10:59:12	ga_ls8c_ard_3-2-0_106083_2021-10-18_final
2021-10-18 10:59:36	ga_ls8c_ard_3-2-0_106084_2021-10-18_final
2021-10-23 11:12:58	ga_ls8c_ard_3-2-0_109071_2021-10-23_final
2021-10-23 11:13:22	ga_ls8c_ard_3-2-0_109072_2021-10-23_final
2021-10-23 11:13:46	ga_ls8c_ard_3-2-0_109073_2021-10-23_final
2021-10-23 11:14:09	ga_ls8c_ard_3-2-0_109074_2021-10-23_final
2021-10-23 11:14:33	ga_ls8c_ard_3-2-0_109075_2021-10-23_final
2021-10-23 11:14:57	ga_ls8c_ard_3-2-0_109076_2021-10-23_final
2021-10-25 11:03:48	ga_ls8c_ard_3-2-0_107079_2021-10-25_final
2021-10-25 11:04:11	ga_ls8c_ard_3-2-0_107080_2021-10-25_final
2021-10-25 11:04:35	ga_ls8c_ard_3-2-0_107081_2021-10-25_final
2021-10-25 11:04:59	ga_ls8c_ard_3-2-0_107082_2021-10-25_final
2021-10-25 11:05:23	ga_ls8c_ard_3-2-0_107083_2021-10-25_final
2021-10-25 11:05:47	ga_ls8c_ard_3-2-0_107084_2021-10-25_final
2021-10-25 11:06:11	ga_ls8c_ard_3-2-0_107085_2021-10-25_final
2021-11-03 10:59:12	ga_ls8c_ard_3-2-0_106083_2021-11-03_final
2021-11-03 10:59:36	ga_ls8c_ard_3-2-0_106084_2021-11-03_final
2021-11-06 11:23:42	ga_ls8c_ard_3-2-0_111067_2021-11-06_final
2021-11-08 11:12:55	ga_ls8c_ard_3-2-0_109071_2021-11-08_final
2021-11-08 11:13:19	ga_ls8c_ard_3-2-0_109072_2021-11-08_final
2021-11-08 11:13:43	ga_ls8c_ard_3-2-0_109073_2021-11-08_final
2021-11-08 11:14:07	ga_ls8c_ard_3-2-0_109074_2021-11-08_final
2021-11-08 11:14:31	ga_ls8c_ard_3-2-0_109075_2021-11-08_final
2021-11-08 11:14:55	ga_ls8c_ard_3-2-0_109076_2021-11-08_final
2021-11-10 11:03:45	ga_ls8c_ard_3-2-0_107079_2021-11-10_final
2021-11-10 11:04:09	ga_ls8c_ard_3-2-0_107080_2021-11-10_final
2021-11-10 11:04:32	ga_ls8c_ard_3-2-0_107081_2021-11-10_final
2021-11-10 11:04:56	ga_ls8c_ard_3-2-0_107082_2021-11-10_final
2021-11-10 11:05:20	ga_ls8c_ard_3-2-0_107083_2021-11-10_final
2021-11-10 11:05:44	ga_ls8c_ard_3-2-0_107084_2021-11-10_final

Return to ga_ls8c_ard_3 whole collection 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

All years