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
2015-01-31 09:38:11	ga_ls8c_ard_3-0-0_094067_2015-01-31_final
2015-01-31 11:17:04	ga_ls8c_ard_3-0-0_110067_2015-01-31_final
2015-02-02 09:25:49	ga_ls8c_ard_3-0-0_092067_2015-02-01_final
2015-02-02 11:04:42	ga_ls8c_ard_3-0-0_108067_2015-02-02_final
2015-04-12 11:22:40	ga_ls8c_ard_3-0-0_111067_2015-04-12_final
2015-04-13 10:27:03	ga_ls8c_ard_3-0-0_102067_2015-04-13_final
2015-04-14 09:31:26	ga_ls8c_ard_3-0-0_093067_2015-04-14_final
2015-04-20 10:33:13	ga_ls8c_ard_3-0-0_103067_2015-04-20_final
2015-04-21 09:37:36	ga_ls8c_ard_3-0-0_094067_2015-04-21_final
2015-04-21 11:16:29	ga_ls8c_ard_3-0-0_110067_2015-04-21_final
2015-04-23 09:25:13	ga_ls8c_ard_3-0-0_092067_2015-04-22_final
2015-05-12 09:55:49	ga_ls8c_ard_3-0-0_097067_2015-05-12_final
2015-05-12 11:34:42	ga_ls8c_ard_3-0-0_113067_2015-05-12_final
2015-05-13 10:39:04	ga_ls8c_ard_3-0-0_104067_2015-05-13_final
2015-05-14 09:43:25	ga_ls8c_ard_3-0-0_095067_2015-05-14_final
2015-05-14 11:22:18	ga_ls8c_ard_3-0-0_111067_2015-05-14_final
2015-05-15 10:26:40	ga_ls8c_ard_3-0-0_102067_2015-05-15_final
2015-05-15 10:27:04	ga_ls8c_ard_3-0-0_102068_2015-05-15_final
2015-05-16 09:31:04	ga_ls8c_ard_3-0-0_093067_2015-05-16_final
2015-05-16 09:31:28	ga_ls8c_ard_3-0-0_093068_2015-05-16_final
2018-02-13 09:56:35	ga_ls8c_ard_3-0-0_097067_2018-02-13_final
2018-02-13 11:35:28	ga_ls8c_ard_3-0-0_113067_2018-02-13_final
2018-02-14 10:39:51	ga_ls8c_ard_3-0-0_104067_2018-02-14_final
2018-02-15 09:44:13	ga_ls8c_ard_3-0-0_095067_2018-02-15_final
2018-02-15 11:23:06	ga_ls8c_ard_3-0-0_111067_2018-02-15_final
2018-02-16 10:27:28	ga_ls8c_ard_3-0-0_102067_2018-02-16_final
2018-02-16 10:27:52	ga_ls8c_ard_3-1-0_102068_2018-02-16_final
2018-02-17 09:31:51	ga_ls8c_ard_3-0-0_093067_2018-02-17_final
2018-02-17 11:10:44	ga_ls8c_ard_3-0-0_109067_2018-02-17_final
2018-02-18 10:15:06	ga_ls8c_ard_3-0-0_100067_2018-02-18_final
2018-04-16 10:08:26	ga_ls8c_ard_3-0-0_099067_2018-04-16_final
2018-04-17 10:51:41	ga_ls8c_ard_3-0-0_106067_2018-04-17_final
2018-04-18 09:56:03	ga_ls8c_ard_3-0-0_097067_2018-04-18_final
2018-04-18 11:34:56	ga_ls8c_ard_3-0-0_113067_2018-04-18_final
2018-06-03 10:07:55	ga_ls8c_ard_3-0-0_099067_2018-06-03_final
2018-06-03 10:08:19	ga_ls8c_ard_3-0-0_099068_2018-06-03_final
2018-06-04 10:51:10	ga_ls8c_ard_3-0-0_106067_2018-06-04_final
2018-06-04 10:51:34	ga_ls8c_ard_3-0-0_106068_2018-06-04_final
2018-06-05 09:55:33	ga_ls8c_ard_3-0-0_097067_2018-06-05_final
2018-06-05 09:55:57	ga_ls8c_ard_3-0-0_097068_2018-06-05_final
2018-06-05 11:34:26	ga_ls8c_ard_3-0-0_113067_2018-06-05_final
2022-08-02 10:52:49	ga_ls8c_ard_3-2-1_106067_2022-08-02_final
2022-08-02 10:53:13	ga_ls8c_ard_3-2-1_106068_2022-08-02_final
2022-08-02 12:31:43	ga_ls8c_ard_3-2-1_122067_2022-08-02_final
2022-08-03 09:57:13	ga_ls8c_ard_3-2-1_097067_2022-08-03_final
2022-08-17 10:09:39	ga_ls8c_ard_3-2-1_099067_2022-08-17_final
2022-08-17 10:10:03	ga_ls8c_ard_3-2-1_099068_2022-08-17_final
2022-10-30 10:46:51	ga_ls8c_ard_3-2-1_105067_2022-10-30_final
2022-10-30 10:47:15	ga_ls8c_ard_3-2-1_105068_2022-10-30_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 12:31:55	ga_ls8c_ard_3-2-1_122067_2022-11-06_final
2022-11-07 09:57:24	ga_ls8c_ard_3-2-1_097067_2022-11-07_final
2022-11-07 09:57:48	ga_ls8c_ard_3-2-1_097068_2022-11-07_final
2022-11-08 10:40:39	ga_ls8c_ard_3-2-1_104067_2022-11-08_final
2022-11-09 11:24:19	ga_ls8c_ard_3-2-1_111068_2022-11-09_final
2022-11-10 10:28:17	ga_ls8c_ard_3-2-1_102067_2022-11-10_final
2022-11-10 10:28:41	ga_ls8c_ard_3-2-1_102068_2022-11-10_final
2022-11-15 10:46:46	ga_ls8c_ard_3-2-1_105067_2022-11-15_final
2022-11-29 12:38:01	ga_ls8c_ard_3-2-1_123067_2022-11-29_final
2022-11-30 10:03:31	ga_ls8c_ard_3-2-1_098067_2022-11-30_final
2022-11-30 10:03:55	ga_ls8c_ard_3-2-1_098068_2022-11-30_final
2023-01-16 12:37:45	ga_ls8c_ard_3-2-1_123067_2023-01-16_final
2023-01-17 10:03:14	ga_ls8c_ard_3-2-1_098067_2023-01-17_final
2023-01-18 10:46:29	ga_ls8c_ard_3-2-1_105067_2023-01-18_final
2023-01-18 10:46:53	ga_ls8c_ard_3-2-1_105068_2023-01-18_final
2023-01-25 10:52:45	ga_ls8c_ard_3-2-1_106067_2023-01-25_final
2023-01-25 12:31:38	ga_ls8c_ard_3-2-1_122067_2023-01-25_final
2023-02-02 10:03:20	ga_ls8c_ard_3-2-1_098067_2023-02-02_final
2023-02-03 10:46:36	ga_ls8c_ard_3-2-1_105067_2023-02-03_final
2023-02-03 10:46:59	ga_ls8c_ard_3-2-1_105068_2023-02-03_final
2023-03-23 10:46:03	ga_ls8c_ard_3-2-1_105067_2023-03-23_final
2023-07-12 10:02:39	ga_ls8c_ard_3-2-1_098067_2023-07-12_final
2023-07-12 10:03:03	ga_ls8c_ard_3-2-1_098068_2023-07-12_final
2023-07-13 10:45:55	ga_ls8c_ard_3-2-1_105067_2023-07-13_final
2023-07-13 10:46:19	ga_ls8c_ard_3-2-1_105068_2023-07-13_final
2023-07-15 10:33:57	ga_ls8c_ard_3-2-1_103068_2023-07-15_final
2023-07-19 10:08:50	ga_ls8c_ard_3-2-1_099067_2023-07-19_final
2023-07-19 10:09:14	ga_ls8c_ard_3-2-1_099068_2023-07-19_final
2023-07-20 10:52:05	ga_ls8c_ard_3-2-1_106067_2023-07-20_final
2023-07-20 10:52:29	ga_ls8c_ard_3-2-1_106068_2023-07-20_final
2023-07-20 12:30:58	ga_ls8c_ard_3-2-1_122067_2023-07-20_final
2023-07-21 09:56:28	ga_ls8c_ard_3-2-1_097067_2023-07-21_final
2023-07-21 09:56:52	ga_ls8c_ard_3-2-1_097068_2023-07-21_final
2023-07-22 10:39:45	ga_ls8c_ard_3-2-1_104067_2023-07-22_final
2023-07-22 10:40:09	ga_ls8c_ard_3-2-1_104068_2023-07-22_final
2023-07-23 11:23:26	ga_ls8c_ard_3-2-1_111068_2023-07-23_final
2023-07-31 10:34:05	ga_ls8c_ard_3-2-1_103068_2023-07-31_final
2023-10-07 10:09:15	ga_ls8c_ard_3-2-1_099067_2023-10-07_final
2023-10-07 10:09:39	ga_ls8c_ard_3-2-1_099068_2023-10-07_final
2023-10-08 10:52:32	ga_ls8c_ard_3-2-1_106067_2023-10-08_final
2023-10-08 12:31:25	ga_ls8c_ard_3-2-1_122067_2023-10-08_final
2023-10-09 09:56:55	ga_ls8c_ard_3-2-1_097067_2023-10-09_final
2023-10-10 10:40:11	ga_ls8c_ard_3-2-1_104067_2023-10-10_final
2023-10-10 10:40:35	ga_ls8c_ard_3-2-1_104068_2023-10-10_final
2023-11-08 10:09:17	ga_ls8c_ard_3-2-1_099067_2023-11-08_final
2023-11-08 10:09:41	ga_ls8c_ard_3-2-1_099068_2023-11-08_final
2023-11-09 10:52:31	ga_ls8c_ard_3-2-1_106067_2023-11-09_final
2023-11-09 12:31:24	ga_ls8c_ard_3-2-1_122067_2023-11-09_final
2023-11-10 09:56:53	ga_ls8c_ard_3-2-1_097067_2023-11-10_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years