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
2015-08-31 10:52:12	ga_ls8c_ard_3-0-0_106067_2015-08-31_final
2015-08-31 10:52:36	ga_ls8c_ard_3-0-0_106068_2015-08-31_final
2015-08-31 10:53:00	ga_ls8c_ard_3-0-0_106069_2015-08-31_final
2015-09-02 10:42:14	ga_ls8c_ard_3-0-0_104073_2015-09-02_final
2015-09-02 10:42:38	ga_ls8c_ard_3-0-0_104074_2015-09-02_final
2015-09-02 10:43:02	ga_ls8c_ard_3-0-0_104075_2015-09-02_final
2015-09-02 10:43:26	ga_ls8c_ard_3-0-0_104076_2015-09-02_final
2015-09-02 10:43:50	ga_ls8c_ard_3-1-0_104077_2015-09-02_final
2015-09-02 10:44:14	ga_ls8c_ard_3-0-0_104078_2015-09-02_final
2015-09-02 10:44:38	ga_ls8c_ard_3-0-0_104079_2015-09-02_final
2015-09-16 10:52:20	ga_ls8c_ard_3-0-0_106067_2015-09-16_final
2015-09-16 10:52:44	ga_ls8c_ard_3-0-0_106068_2015-09-16_final
2015-09-16 10:53:08	ga_ls8c_ard_3-0-0_106069_2015-09-16_final
2015-09-18 10:42:23	ga_ls8c_ard_3-0-0_104073_2015-09-18_final
2015-09-18 10:42:47	ga_ls8c_ard_3-0-0_104074_2015-09-18_final
2015-09-18 10:43:10	ga_ls8c_ard_3-0-0_104075_2015-09-18_final
2015-09-18 10:43:34	ga_ls8c_ard_3-0-0_104076_2015-09-18_final
2015-09-18 10:43:58	ga_ls8c_ard_3-0-0_104077_2015-09-18_final
2015-09-18 10:44:22	ga_ls8c_ard_3-0-0_104078_2015-09-18_final
2015-09-18 10:44:46	ga_ls8c_ard_3-0-0_104079_2015-09-18_final
2015-09-20 10:33:37	ga_ls8c_ard_3-0-0_102082_2015-09-20_final
2015-09-20 10:34:01	ga_ls8c_ard_3-0-0_102083_2015-09-20_final
2015-10-22 10:33:43	ga_ls8c_ard_3-0-0_102082_2015-10-22_final
2015-10-22 10:34:07	ga_ls8c_ard_3-0-0_102083_2015-10-22_final
2015-11-19 10:52:32	ga_ls8c_ard_3-0-0_106067_2015-11-19_final
2015-11-19 10:52:56	ga_ls8c_ard_3-0-0_106068_2015-11-19_final
2015-11-19 10:53:19	ga_ls8c_ard_3-0-0_106069_2015-11-19_final
2015-11-21 10:42:34	ga_ls8c_ard_3-0-0_104073_2015-11-21_final
2015-11-21 10:42:58	ga_ls8c_ard_3-0-0_104074_2015-11-21_final
2015-11-21 10:43:22	ga_ls8c_ard_3-0-0_104075_2015-11-21_final
2015-11-21 10:43:46	ga_ls8c_ard_3-0-0_104076_2015-11-21_final
2015-11-21 10:44:10	ga_ls8c_ard_3-1-0_104077_2015-11-21_final
2015-11-21 10:44:34	ga_ls8c_ard_3-0-0_104078_2015-11-21_final
2015-11-21 10:44:58	ga_ls8c_ard_3-0-0_104079_2015-11-21_final
2018-09-17 10:46:14	ga_ls8c_ard_3-0-0_105068_2018-09-17_final
2018-09-17 10:46:38	ga_ls8c_ard_3-0-0_105069_2018-09-17_final
2018-09-17 10:47:02	ga_ls8c_ard_3-0-0_105070_2018-09-17_final
2018-09-17 10:47:26	ga_ls8c_ard_3-0-0_105071_2018-09-17_final
2018-09-17 10:47:50	ga_ls8c_ard_3-0-0_105072_2018-09-17_final
2018-09-17 10:48:14	ga_ls8c_ard_3-0-0_105073_2018-09-17_final
2018-09-17 10:48:38	ga_ls8c_ard_3-0-0_105074_2018-09-17_final
2019-01-07 10:46:28	ga_ls8c_ard_3-0-0_105068_2019-01-07_final
2019-01-07 10:46:52	ga_ls8c_ard_3-0-0_105069_2019-01-07_final
2019-01-07 10:47:16	ga_ls8c_ard_3-0-0_105070_2019-01-07_final
2019-01-07 10:47:40	ga_ls8c_ard_3-0-0_105071_2019-01-07_final
2019-01-07 10:48:04	ga_ls8c_ard_3-0-0_105072_2019-01-07_final
2019-01-07 10:48:28	ga_ls8c_ard_3-0-0_105073_2019-01-07_final
2019-01-07 10:48:52	ga_ls8c_ard_3-0-0_105074_2019-01-07_final
2019-03-03 10:52:04	ga_ls8c_ard_3-0-0_106067_2019-03-03_final
2019-03-03 10:52:28	ga_ls8c_ard_3-0-0_106068_2019-03-03_final
2019-03-03 10:52:52	ga_ls8c_ard_3-0-0_106069_2019-03-03_final
2019-03-05 10:42:05	ga_ls8c_ard_3-0-0_104073_2019-03-05_final
2019-03-05 10:42:29	ga_ls8c_ard_3-0-0_104074_2019-03-05_final
2019-03-05 10:42:53	ga_ls8c_ard_3-0-0_104075_2019-03-05_final
2019-03-05 10:43:17	ga_ls8c_ard_3-0-0_104076_2019-03-05_final
2019-03-05 10:43:41	ga_ls8c_ard_3-0-0_104077_2019-03-05_final
2019-03-05 10:44:05	ga_ls8c_ard_3-0-0_104078_2019-03-05_final
2019-03-05 10:44:29	ga_ls8c_ard_3-0-0_104079_2019-03-05_final
2019-06-07 10:52:10	ga_ls8c_ard_3-0-0_106067_2019-06-07_final
2019-06-07 10:52:34	ga_ls8c_ard_3-0-0_106068_2019-06-07_final
2019-06-07 10:52:58	ga_ls8c_ard_3-0-0_106069_2019-06-07_final
2019-06-09 10:42:13	ga_ls8c_ard_3-0-0_104073_2019-06-09_final
2019-06-09 10:42:37	ga_ls8c_ard_3-0-0_104074_2019-06-09_final
2019-06-09 10:43:00	ga_ls8c_ard_3-0-0_104075_2019-06-09_final
2019-06-09 10:43:24	ga_ls8c_ard_3-0-0_104076_2019-06-09_final
2019-06-09 10:43:48	ga_ls8c_ard_3-1-0_104077_2019-06-09_final
2019-06-09 10:44:12	ga_ls8c_ard_3-0-0_104078_2019-06-09_final
2019-06-09 10:44:36	ga_ls8c_ard_3-0-0_104079_2019-06-09_final
2022-08-22 10:33:48	ga_ls8c_ard_3-2-1_102081_2022-08-22_final
2022-08-22 10:34:12	ga_ls8c_ard_3-2-1_102082_2022-08-22_final
2022-10-14 10:47:06	ga_ls8c_ard_3-2-1_105068_2022-10-14_final
2022-10-14 10:47:54	ga_ls8c_ard_3-2-1_105070_2022-10-14_final
2022-10-14 10:48:18	ga_ls8c_ard_3-2-1_105071_2022-10-14_final
2022-10-14 10:48:42	ga_ls8c_ard_3-2-1_105072_2022-10-14_final
2022-10-14 10:49:30	ga_ls8c_ard_3-2-1_105074_2022-10-14_final
2022-10-21 10:52:58	ga_ls8c_ard_3-2-1_106067_2022-10-21_final
2022-10-21 10:53:22	ga_ls8c_ard_3-2-1_106068_2022-10-21_final
2022-10-21 10:53:46	ga_ls8c_ard_3-2-1_106069_2022-10-21_final
2022-10-23 10:43:01	ga_ls8c_ard_3-2-1_104073_2022-10-23_final
2022-10-23 10:43:25	ga_ls8c_ard_3-2-1_104074_2022-10-23_final
2022-10-23 10:43:49	ga_ls8c_ard_3-2-1_104075_2022-10-23_final
2022-10-23 10:44:13	ga_ls8c_ard_3-2-1_104076_2022-10-23_final
2022-10-23 10:44:37	ga_ls8c_ard_3-2-1_104077_2022-10-23_final
2022-10-23 10:45:01	ga_ls8c_ard_3-2-1_104078_2022-10-23_final
2022-10-23 10:45:25	ga_ls8c_ard_3-2-1_104079_2022-10-23_final
2022-11-01 10:38:29	ga_ls8c_ard_3-2-1_103077_2022-11-01_final
2022-11-01 10:38:53	ga_ls8c_ard_3-2-1_103078_2022-11-01_final
2022-11-01 10:39:17	ga_ls8c_ard_3-2-1_103079_2022-11-01_final
2022-11-01 10:39:41	ga_ls8c_ard_3-2-1_103080_2022-11-01_final
2022-11-01 10:40:05	ga_ls8c_ard_3-2-1_103081_2022-11-01_final
2022-11-01 10:40:29	ga_ls8c_ard_3-2-1_103082_2022-11-01_final
2022-11-06 10:53:02	ga_ls8c_ard_3-2-1_106067_2022-11-06_final
2022-11-06 10:53:26	ga_ls8c_ard_3-2-1_106068_2022-11-06_final
2022-11-06 10:53:49	ga_ls8c_ard_3-2-1_106069_2022-11-06_final
2022-11-08 10:43:03	ga_ls8c_ard_3-2-1_104073_2022-11-08_final
2022-11-08 10:43:27	ga_ls8c_ard_3-2-1_104074_2022-11-08_final
2022-11-08 10:43:51	ga_ls8c_ard_3-2-1_104075_2022-11-08_final
2022-11-08 10:44:15	ga_ls8c_ard_3-2-1_104076_2022-11-08_final
2022-11-08 10:44:39	ga_ls8c_ard_3-2-1_104077_2022-11-08_final
2022-11-08 10:45:03	ga_ls8c_ard_3-2-1_104078_2022-11-08_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