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
2014-12-14 11:17:12	ga_ls8c_ard_3-0-0_110067_2014-12-14_final
2014-12-30 11:17:09	ga_ls8c_ard_3-0-0_110067_2014-12-30_final
2015-01-08 11:11:47	ga_ls8c_ard_3-0-0_109069_2015-01-08_final
2015-01-08 11:12:11	ga_ls8c_ard_3-0-0_109070_2015-01-08_final
2015-01-08 11:12:35	ga_ls8c_ard_3-0-0_109071_2015-01-08_final
2015-01-08 11:12:59	ga_ls8c_ard_3-0-0_109072_2015-01-08_final
2015-01-31 11:17:04	ga_ls8c_ard_3-0-0_110067_2015-01-31_final
2015-02-02 11:06:18	ga_ls8c_ard_3-0-0_108071_2015-02-02_final
2015-02-02 11:06:42	ga_ls8c_ard_3-0-0_108072_2015-02-02_final
2015-02-02 11:07:05	ga_ls8c_ard_3-0-0_108073_2015-02-02_final
2015-02-02 11:07:29	ga_ls8c_ard_3-0-0_108074_2015-02-02_final
2015-02-02 11:07:53	ga_ls8c_ard_3-0-0_108075_2015-02-02_final
2015-02-02 11:08:17	ga_ls8c_ard_3-0-0_108076_2015-02-02_final
2015-02-25 11:10:44	ga_ls8c_ard_3-0-0_109067_2015-02-25_final
2015-02-25 11:11:08	ga_ls8c_ard_3-0-0_109068_2015-02-25_final
2015-02-25 11:11:32	ga_ls8c_ard_3-0-0_109069_2015-02-25_final
2015-02-25 11:11:56	ga_ls8c_ard_3-0-0_109070_2015-02-25_final
2015-02-25 11:12:20	ga_ls8c_ard_3-0-0_109071_2015-02-25_final
2015-02-25 11:12:43	ga_ls8c_ard_3-0-0_109072_2015-02-25_final
2015-03-08 10:57:16	ga_ls8c_ard_3-0-0_106080_2015-03-08_final
2015-03-08 10:57:40	ga_ls8c_ard_3-0-0_106081_2015-03-08_final
2015-03-08 10:58:04	ga_ls8c_ard_3-0-0_106082_2015-03-08_final
2015-03-08 10:58:28	ga_ls8c_ard_3-0-0_106083_2015-03-08_final
2015-03-24 10:57:07	ga_ls8c_ard_3-0-0_106080_2015-03-24_final
2018-02-08 11:16:57	ga_ls8c_ard_3-0-0_110067_2018-02-08_final
2018-02-24 11:16:51	ga_ls8c_ard_3-0-0_110067_2018-02-24_final
2018-03-28 11:16:36	ga_ls8c_ard_3-0-0_110067_2018-03-28_final
2018-05-24 11:09:50	ga_ls8c_ard_3-0-0_109067_2018-05-24_final
2018-05-24 11:10:14	ga_ls8c_ard_3-0-0_109068_2018-05-24_final
2018-05-24 11:10:38	ga_ls8c_ard_3-0-0_109069_2018-05-24_final
2018-05-24 11:11:02	ga_ls8c_ard_3-0-0_109070_2018-05-24_final
2018-05-24 11:11:26	ga_ls8c_ard_3-0-0_109071_2018-05-24_final
2018-05-24 11:11:50	ga_ls8c_ard_3-0-0_109072_2018-05-24_final
2018-06-09 11:09:45	ga_ls8c_ard_3-0-0_109067_2018-06-09_final
2018-06-09 11:10:09	ga_ls8c_ard_3-0-0_109068_2018-06-09_final
2018-06-09 11:10:33	ga_ls8c_ard_3-0-0_109069_2018-06-09_final
2018-06-09 11:10:57	ga_ls8c_ard_3-0-0_109070_2018-06-09_final
2018-06-09 11:11:21	ga_ls8c_ard_3-0-0_109071_2018-06-09_final
2018-06-09 11:11:45	ga_ls8c_ard_3-0-0_109072_2018-06-09_final
2018-06-11 11:00:36	ga_ls8c_ard_3-0-0_107075_2018-06-11_final
2018-06-11 11:01:00	ga_ls8c_ard_3-0-0_107076_2018-06-11_final
2018-06-11 11:01:24	ga_ls8c_ard_3-0-0_107077_2018-06-11_final
2018-06-11 11:01:48	ga_ls8c_ard_3-0-0_107078_2018-06-11_final
2018-06-11 11:02:12	ga_ls8c_ard_3-0-0_107079_2018-06-11_final
2018-06-11 11:02:36	ga_ls8c_ard_3-0-0_107080_2018-06-11_final
2018-06-11 11:03:00	ga_ls8c_ard_3-0-0_107081_2018-06-11_final
2018-06-25 11:09:56	ga_ls8c_ard_3-0-0_109067_2018-06-25_final
2018-06-25 11:10:20	ga_ls8c_ard_3-0-0_109068_2018-06-25_final
2018-06-25 11:10:44	ga_ls8c_ard_3-0-0_109069_2018-06-25_final
2018-06-25 11:11:08	ga_ls8c_ard_3-0-0_109070_2018-06-25_final
2018-06-25 11:11:32	ga_ls8c_ard_3-0-0_109071_2018-06-25_final
2018-06-25 11:11:55	ga_ls8c_ard_3-0-0_109072_2018-06-25_final
2018-06-27 11:00:47	ga_ls8c_ard_3-0-0_107075_2018-06-27_final
2018-06-27 11:01:11	ga_ls8c_ard_3-0-0_107076_2018-06-27_final
2018-06-27 11:01:35	ga_ls8c_ard_3-0-0_107077_2018-06-27_final
2018-06-27 11:01:59	ga_ls8c_ard_3-0-0_107078_2018-06-27_final
2018-06-27 11:02:23	ga_ls8c_ard_3-0-0_107079_2018-06-27_final
2018-06-27 11:02:47	ga_ls8c_ard_3-0-0_107080_2018-06-27_final
2018-06-27 11:03:10	ga_ls8c_ard_3-0-0_107081_2018-06-27_final
2018-07-11 11:10:04	ga_ls8c_ard_3-0-0_109067_2018-07-11_final
2018-07-11 11:10:28	ga_ls8c_ard_3-0-0_109068_2018-07-11_final
2018-07-11 11:10:52	ga_ls8c_ard_3-0-0_109069_2018-07-11_final
2018-07-11 11:11:16	ga_ls8c_ard_3-0-0_109070_2018-07-11_final
2018-07-11 11:11:40	ga_ls8c_ard_3-0-0_109071_2018-07-11_final
2018-07-11 11:12:04	ga_ls8c_ard_3-0-0_109072_2018-07-11_final
2018-07-13 11:00:55	ga_ls8c_ard_3-0-0_107075_2018-07-13_final
2018-07-13 11:01:19	ga_ls8c_ard_3-0-0_107076_2018-07-13_final
2018-07-13 11:01:43	ga_ls8c_ard_3-0-0_107077_2018-07-13_final
2018-07-13 11:02:07	ga_ls8c_ard_3-0-0_107078_2018-07-13_final
2018-07-13 11:02:31	ga_ls8c_ard_3-0-0_107079_2018-07-13_final
2018-07-13 11:02:55	ga_ls8c_ard_3-0-0_107080_2018-07-13_final
2018-07-13 11:03:19	ga_ls8c_ard_3-0-0_107081_2018-07-13_final
2018-07-29 11:01:02	ga_ls8c_ard_3-0-0_107075_2018-07-29_final
2018-07-29 11:01:26	ga_ls8c_ard_3-0-0_107076_2018-07-29_final
2018-07-29 11:01:49	ga_ls8c_ard_3-0-0_107077_2018-07-29_final
2018-07-29 11:02:13	ga_ls8c_ard_3-0-0_107078_2018-07-29_final
2018-07-29 11:02:37	ga_ls8c_ard_3-0-0_107079_2018-07-29_final
2018-07-29 11:03:01	ga_ls8c_ard_3-0-0_107080_2018-07-29_final
2018-07-29 11:03:25	ga_ls8c_ard_3-0-0_107081_2018-07-29_final
2018-08-14 11:01:11	ga_ls8c_ard_3-0-0_107075_2018-08-14_final
2018-08-14 11:01:35	ga_ls8c_ard_3-0-0_107076_2018-08-14_final
2018-08-14 11:01:59	ga_ls8c_ard_3-0-0_107077_2018-08-14_final
2018-08-14 11:02:23	ga_ls8c_ard_3-0-0_107078_2018-08-14_final
2018-08-14 11:02:47	ga_ls8c_ard_3-0-0_107079_2018-08-14_final
2018-08-14 11:03:11	ga_ls8c_ard_3-0-0_107080_2018-08-14_final
2018-08-14 11:03:35	ga_ls8c_ard_3-0-0_107081_2018-08-14_final
2018-08-30 11:01:18	ga_ls8c_ard_3-0-0_107075_2018-08-30_final
2018-08-30 11:01:42	ga_ls8c_ard_3-0-0_107076_2018-08-30_final
2018-08-30 11:02:06	ga_ls8c_ard_3-0-0_107077_2018-08-30_final
2018-08-30 11:02:30	ga_ls8c_ard_3-0-0_107078_2018-08-30_final
2018-08-30 11:02:54	ga_ls8c_ard_3-0-0_107079_2018-08-30_final
2018-08-30 11:03:18	ga_ls8c_ard_3-0-0_107080_2018-08-30_final
2018-08-30 11:03:42	ga_ls8c_ard_3-0-0_107081_2018-08-30_final
2018-09-17 10:52:13	ga_ls8c_ard_3-0-0_105083_2018-09-17_final
2018-10-06 11:16:53	ga_ls8c_ard_3-0-0_110067_2018-10-06_final
2018-12-25 11:16:59	ga_ls8c_ard_3-0-0_110067_2018-12-25_final
2019-01-07 10:52:27	ga_ls8c_ard_3-0-0_105083_2019-01-07_final
2023-08-10 11:11:35	ga_ls8c_ard_3-2-1_109069_2023-08-10_final
2023-08-10 11:11:59	ga_ls8c_ard_3-2-1_109070_2023-08-10_final
2023-08-10 11:12:23	ga_ls8c_ard_3-2-1_109071_2023-08-10_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