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
2018-06-20 10:51:20	ga_ls8c_ard_3-0-0_106067_2018-06-20_final
2018-06-20 10:51:44	ga_ls8c_ard_3-0-0_106068_2018-06-20_final
2018-06-20 10:52:08	ga_ls8c_ard_3-0-0_106069_2018-06-20_final
2018-06-20 10:52:32	ga_ls8c_ard_3-0-0_106070_2018-06-20_final
2018-06-22 10:41:47	ga_ls8c_ard_3-0-0_104074_2018-06-22_final
2018-06-22 10:42:11	ga_ls8c_ard_3-0-0_104075_2018-06-22_final
2018-06-22 10:42:35	ga_ls8c_ard_3-0-0_104076_2018-06-22_final
2018-06-22 10:42:59	ga_ls8c_ard_3-1-0_104077_2018-06-22_final
2018-06-22 10:43:23	ga_ls8c_ard_3-0-0_104078_2018-06-22_final
2018-06-22 10:43:47	ga_ls8c_ard_3-0-0_104079_2018-06-22_final
2018-06-22 10:44:11	ga_ls8c_ard_3-0-0_104080_2018-06-22_final
2018-07-06 10:51:29	ga_ls8c_ard_3-0-0_106067_2018-07-06_final
2018-07-06 10:51:53	ga_ls8c_ard_3-0-0_106068_2018-07-06_final
2018-07-06 10:52:17	ga_ls8c_ard_3-0-0_106069_2018-07-06_final
2018-07-06 10:52:41	ga_ls8c_ard_3-0-0_106070_2018-07-06_final
2018-07-08 10:41:56	ga_ls8c_ard_3-0-0_104074_2018-07-08_final
2018-07-08 10:42:20	ga_ls8c_ard_3-0-0_104075_2018-07-08_final
2018-07-08 10:42:44	ga_ls8c_ard_3-0-0_104076_2018-07-08_final
2018-07-08 10:43:08	ga_ls8c_ard_3-1-0_104077_2018-07-08_final
2018-07-08 10:43:32	ga_ls8c_ard_3-0-0_104078_2018-07-08_final
2018-07-08 10:43:56	ga_ls8c_ard_3-0-0_104079_2018-07-08_final
2018-07-08 10:44:20	ga_ls8c_ard_3-0-0_104080_2018-07-08_final
2018-08-23 10:51:53	ga_ls8c_ard_3-0-0_106067_2018-08-23_final
2018-08-23 10:52:17	ga_ls8c_ard_3-0-0_106068_2018-08-23_final
2018-08-23 10:52:41	ga_ls8c_ard_3-0-0_106069_2018-08-23_final
2018-08-23 10:53:05	ga_ls8c_ard_3-0-0_106070_2018-08-23_final
2018-08-25 10:42:20	ga_ls8c_ard_3-0-0_104074_2018-08-25_final
2018-08-25 10:42:44	ga_ls8c_ard_3-0-0_104075_2018-08-25_final
2018-08-25 10:43:08	ga_ls8c_ard_3-0-0_104076_2018-08-25_final
2018-08-25 10:43:32	ga_ls8c_ard_3-1-0_104077_2018-08-25_final
2018-08-25 10:43:56	ga_ls8c_ard_3-0-0_104078_2018-08-25_final
2018-08-25 10:44:20	ga_ls8c_ard_3-0-0_104079_2018-08-25_final
2018-08-25 10:44:44	ga_ls8c_ard_3-0-0_104080_2018-08-25_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
2018-09-17 10:49:02	ga_ls8c_ard_3-0-0_105075_2018-09-17_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
2019-01-07 10:49:16	ga_ls8c_ard_3-0-0_105075_2019-01-07_final
2022-08-22 10:34:12	ga_ls8c_ard_3-2-1_102082_2022-08-22_final
2022-09-19 10:53:02	ga_ls8c_ard_3-2-1_106067_2022-09-19_final
2022-09-19 10:53:26	ga_ls8c_ard_3-2-1_106068_2022-09-19_final
2022-09-19 10:53:50	ga_ls8c_ard_3-2-1_106069_2022-09-19_final
2022-09-19 10:54:14	ga_ls8c_ard_3-2-1_106070_2022-09-19_final
2022-09-21 10:43:28	ga_ls8c_ard_3-2-1_104074_2022-09-21_final
2022-09-21 10:43:52	ga_ls8c_ard_3-2-1_104075_2022-09-21_final
2022-09-21 10:44:16	ga_ls8c_ard_3-2-1_104076_2022-09-21_final
2022-09-21 10:44:40	ga_ls8c_ard_3-2-1_104077_2022-09-21_final
2022-09-21 10:45:04	ga_ls8c_ard_3-2-1_104078_2022-09-21_final
2022-09-21 10:45:28	ga_ls8c_ard_3-2-1_104079_2022-09-21_final
2022-09-21 10:45:52	ga_ls8c_ard_3-2-1_104080_2022-09-21_final
2022-10-07 10:43:25	ga_ls8c_ard_3-2-1_104074_2022-10-07_final
2022-10-07 10:43:49	ga_ls8c_ard_3-2-1_104075_2022-10-07_final
2022-10-07 10:44:13	ga_ls8c_ard_3-2-1_104076_2022-10-07_final
2022-10-07 10:44:37	ga_ls8c_ard_3-2-1_104077_2022-10-07_final
2022-10-07 10:45:00	ga_ls8c_ard_3-2-1_104078_2022-10-07_final
2022-10-07 10:45:24	ga_ls8c_ard_3-2-1_104079_2022-10-07_final
2022-10-07 10:45:48	ga_ls8c_ard_3-2-1_104080_2022-10-07_final
2022-10-09 10:34:13	ga_ls8c_ard_3-2-1_102082_2022-10-09_final
2022-10-30 10:47:39	ga_ls8c_ard_3-2-1_105069_2022-10-30_final
2022-10-30 10:48:03	ga_ls8c_ard_3-2-1_105070_2022-10-30_final
2022-10-30 10:48:27	ga_ls8c_ard_3-2-1_105071_2022-10-30_final
2022-10-30 10:48:51	ga_ls8c_ard_3-2-1_105072_2022-10-30_final
2022-10-30 10:49:15	ga_ls8c_ard_3-2-1_105073_2022-10-30_final
2022-10-30 10:49:39	ga_ls8c_ard_3-2-1_105074_2022-10-30_final
2022-10-30 10:50:03	ga_ls8c_ard_3-2-1_105075_2022-10-30_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
2022-11-08 10:44:15	ga_ls8c_ard_3-2-1_104076_2022-11-08_final
2022-11-08 10:45:27	ga_ls8c_ard_3-2-1_104079_2022-11-08_final
2022-11-24 10:43:22	ga_ls8c_ard_3-2-1_104074_2022-11-24_final
2022-11-24 10:43:46	ga_ls8c_ard_3-2-1_104075_2022-11-24_final
2022-11-24 10:44:10	ga_ls8c_ard_3-2-1_104076_2022-11-24_final
2022-11-24 10:44:34	ga_ls8c_ard_3-2-1_104077_2022-11-24_final
2022-11-24 10:44:58	ga_ls8c_ard_3-2-1_104078_2022-11-24_final
2022-11-24 10:45:22	ga_ls8c_ard_3-2-1_104079_2022-11-24_final
2022-11-24 10:45:46	ga_ls8c_ard_3-2-1_104080_2022-11-24_final
2022-12-01 10:47:58	ga_ls8c_ard_3-2-1_105070_2022-12-01_final
2022-12-01 10:48:22	ga_ls8c_ard_3-2-1_105071_2022-12-01_final
2022-12-01 10:48:46	ga_ls8c_ard_3-2-1_105072_2022-12-01_final
2022-12-01 10:49:10	ga_ls8c_ard_3-2-1_105073_2022-12-01_final
2022-12-01 10:49:34	ga_ls8c_ard_3-2-1_105074_2022-12-01_final
2022-12-01 10:49:58	ga_ls8c_ard_3-2-1_105075_2022-12-01_final
2022-12-03 10:38:48	ga_ls8c_ard_3-2-1_103078_2022-12-03_final
2022-12-03 10:39:12	ga_ls8c_ard_3-2-1_103079_2022-12-03_final
2022-12-03 10:39:36	ga_ls8c_ard_3-2-1_103080_2022-12-03_final
2022-12-03 10:40:00	ga_ls8c_ard_3-2-1_103081_2022-12-03_final
2022-12-03 10:40:24	ga_ls8c_ard_3-2-1_103082_2022-12-03_final
2022-12-08 10:52:56	ga_ls8c_ard_3-2-1_106067_2022-12-08_final
2022-12-08 10:53:20	ga_ls8c_ard_3-2-1_106068_2022-12-08_final
2022-12-08 10:53:44	ga_ls8c_ard_3-2-1_106069_2022-12-08_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