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
2013-03-19 10:01:20	ga_ls8c_ard_3-0-0_097073_2013-03-19_final
2013-03-22 10:18:31	ga_ls8c_ard_3-0-0_100073_2013-03-22_final
2013-03-23 10:57:06	ga_ls8c_ard_3-0-0_106073_2013-03-23_final
2013-03-24 09:57:06	ga_ls8c_ard_3-0-0_096073_2013-03-24_final
2013-03-26 09:35:42	ga_ls8c_ard_3-0-0_093073_2013-03-26_final
2013-03-26 11:14:16	ga_ls8c_ard_3-0-0_109073_2013-03-26_final
2013-03-27 10:14:17	ga_ls8c_ard_3-1-0_099073_2013-03-27_final
2013-10-04 10:07:14	ga_ls8c_ard_3-0-0_098073_2013-10-04_final
2013-10-05 10:50:29	ga_ls8c_ard_3-0-0_105073_2013-10-05_final
2013-10-06 09:54:52	ga_ls8c_ard_3-0-0_096073_2013-10-06_final
2013-10-06 11:33:45	ga_ls8c_ard_3-0-0_112073_2013-10-06_final
2013-10-07 10:38:08	ga_ls8c_ard_3-0-0_103073_2013-10-07_final
2013-10-08 09:42:31	ga_ls8c_ard_3-0-0_094073_2013-10-08_final
2013-10-08 11:21:24	ga_ls8c_ard_3-0-0_110073_2013-10-08_final
2013-10-09 10:25:46	ga_ls8c_ard_3-0-0_101073_2013-10-09_final
2013-10-10 11:09:02	ga_ls8c_ard_3-0-0_108073_2013-10-10_final
2013-10-12 10:56:40	ga_ls8c_ard_3-0-0_106073_2013-10-12_final
2019-02-07 10:05:06	ga_ls8c_ard_3-0-0_098073_2019-02-07_final
2019-02-08 10:48:22	ga_ls8c_ard_3-0-0_105073_2019-02-08_final
2019-02-09 09:52:44	ga_ls8c_ard_3-0-0_096073_2019-02-09_final
2019-02-09 11:31:37	ga_ls8c_ard_3-0-0_112073_2019-02-09_final
2019-02-10 10:36:00	ga_ls8c_ard_3-0-0_103073_2019-02-10_final
2019-02-11 09:40:22	ga_ls8c_ard_3-0-0_094073_2019-02-11_final
2019-02-11 11:19:15	ga_ls8c_ard_3-0-0_110073_2019-02-11_final
2019-02-17 10:42:10	ga_ls8c_ard_3-0-0_104073_2019-02-17_final
2019-02-18 09:46:32	ga_ls8c_ard_3-0-0_095073_2019-02-18_final
2019-02-18 11:25:25	ga_ls8c_ard_3-0-0_111073_2019-02-18_final
2019-02-19 10:29:48	ga_ls8c_ard_3-0-0_102073_2019-02-19_final
2019-03-14 10:35:51	ga_ls8c_ard_3-1-0_103073_2019-03-14_final
2019-03-15 09:40:13	ga_ls8c_ard_3-1-0_094073_2019-03-15_final
2019-03-15 11:19:06	ga_ls8c_ard_3-1-0_110073_2019-03-15_final
2019-03-16 10:23:29	ga_ls8c_ard_3-1-0_101073_2019-03-16_final
2019-05-01 10:35:40	ga_ls8c_ard_3-0-0_103073_2019-05-01_final
2019-05-02 09:39:39	ga_ls8c_ard_3-0-0_094072_2019-05-02_final
2019-05-02 09:40:03	ga_ls8c_ard_3-0-0_094073_2019-05-02_final
2019-05-02 11:18:32	ga_ls8c_ard_3-0-0_110072_2019-05-02_final
2019-05-02 11:18:56	ga_ls8c_ard_3-0-0_110073_2019-05-02_final
2019-05-03 10:23:19	ga_ls8c_ard_3-0-0_101073_2019-05-03_final
2019-06-18 10:36:05	ga_ls8c_ard_3-1-0_103073_2019-06-18_final
2019-06-19 09:40:28	ga_ls8c_ard_3-1-0_094073_2019-06-19_final
2019-06-19 11:18:57	ga_ls8c_ard_3-1-0_110072_2019-06-19_final
2019-06-19 11:19:21	ga_ls8c_ard_3-1-0_110073_2019-06-19_final
2019-06-20 10:23:44	ga_ls8c_ard_3-1-0_101073_2019-06-20_final
2020-10-17 10:42:22	ga_ls8c_ard_3-1-0_104072_2020-10-17_final
2020-10-17 10:42:46	ga_ls8c_ard_3-1-0_104073_2020-10-17_final
2020-10-18 09:47:08	ga_ls8c_ard_3-1-0_095073_2020-10-18_final
2020-10-18 11:25:37	ga_ls8c_ard_3-1-0_111072_2020-10-18_final
2020-10-18 11:26:01	ga_ls8c_ard_3-1-0_111073_2020-10-18_final
2020-10-19 10:30:24	ga_ls8c_ard_3-1-0_102073_2020-10-19_final
2020-10-24 10:48:32	ga_ls8c_ard_3-1-0_105072_2020-10-24_final
2020-10-24 10:48:56	ga_ls8c_ard_3-1-0_105073_2020-10-24_final
2020-10-25 09:53:19	ga_ls8c_ard_3-1-0_096073_2020-10-25_final
2020-11-27 10:36:35	ga_ls8c_ard_3-1-0_103073_2020-11-27_final
2020-11-28 09:40:58	ga_ls8c_ard_3-1-0_094073_2020-11-28_final
2020-11-28 11:19:51	ga_ls8c_ard_3-1-0_110073_2020-11-28_final
2020-11-29 10:24:14	ga_ls8c_ard_3-1-0_101073_2020-11-29_final
2022-09-17 11:07:47	ga_ls8c_ard_3-2-1_108073_2022-09-17_final
2022-09-18 10:12:10	ga_ls8c_ard_3-2-1_099073_2022-09-18_final
2022-09-19 10:55:26	ga_ls8c_ard_3-2-1_106073_2022-09-19_final
2022-09-20 09:59:49	ga_ls8c_ard_3-2-1_097073_2022-09-20_final
2022-09-20 11:38:42	ga_ls8c_ard_3-2-1_113073_2022-09-20_final
2022-09-21 10:43:04	ga_ls8c_ard_3-2-1_104073_2022-09-21_final
2022-09-22 09:47:27	ga_ls8c_ard_3-2-1_095073_2022-09-22_final
2022-09-22 11:26:20	ga_ls8c_ard_3-2-1_111073_2022-09-22_final
2022-09-23 10:30:43	ga_ls8c_ard_3-2-1_102073_2022-09-23_final
2022-09-24 09:34:42	ga_ls8c_ard_3-2-1_093072_2022-09-24_final
2022-09-24 09:35:06	ga_ls8c_ard_3-2-1_093073_2022-09-24_final
2022-09-24 11:13:59	ga_ls8c_ard_3-2-1_109073_2022-09-24_final
2022-09-25 10:18:21	ga_ls8c_ard_3-2-1_100073_2022-09-25_final
2022-09-26 09:22:20	ga_ls8c_ard_3-2-1_091072_2022-09-25_final
2022-09-26 09:22:44	ga_ls8c_ard_3-2-1_091073_2022-09-25_final
2022-09-26 11:01:37	ga_ls8c_ard_3-2-1_107073_2022-09-26_final
2022-09-27 10:05:36	ga_ls8c_ard_3-2-1_098072_2022-09-27_final
2022-09-27 10:05:59	ga_ls8c_ard_3-2-1_098073_2022-09-27_final
2022-09-28 10:49:15	ga_ls8c_ard_3-2-1_105073_2022-09-28_final
2022-09-29 09:53:38	ga_ls8c_ard_3-2-1_096073_2022-09-29_final
2022-09-29 11:32:31	ga_ls8c_ard_3-2-1_112073_2022-09-29_final
2022-09-30 10:36:53	ga_ls8c_ard_3-2-1_103073_2022-09-30_final
2022-10-01 09:41:15	ga_ls8c_ard_3-2-1_094073_2022-10-01_final
2022-10-01 11:20:08	ga_ls8c_ard_3-2-1_110073_2022-10-01_final
2022-10-26 09:35:04	ga_ls8c_ard_3-2-1_093073_2022-10-26_final
2022-10-26 11:13:57	ga_ls8c_ard_3-2-1_109073_2022-10-26_final
2022-10-27 10:18:20	ga_ls8c_ard_3-2-1_100073_2022-10-27_final
2022-11-15 10:49:09	ga_ls8c_ard_3-2-1_105073_2022-11-15_final
2022-11-16 09:53:31	ga_ls8c_ard_3-2-1_096073_2022-11-16_final
2022-11-16 11:32:24	ga_ls8c_ard_3-2-1_112073_2022-11-16_final
2022-11-17 10:36:46	ga_ls8c_ard_3-2-1_103073_2022-11-17_final
2022-11-18 09:40:44	ga_ls8c_ard_3-2-1_094072_2022-11-18_final
2022-11-18 09:41:08	ga_ls8c_ard_3-2-1_094073_2022-11-18_final
2022-11-18 11:20:01	ga_ls8c_ard_3-2-1_110073_2022-11-18_final
2022-11-19 10:24:24	ga_ls8c_ard_3-2-1_101073_2022-11-19_final
2022-11-20 09:28:47	ga_ls8c_ard_3-2-1_092073_2022-11-19_final
2022-11-20 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-11-20_final
2022-11-21 10:12:03	ga_ls8c_ard_3-2-1_099073_2022-11-21_final
2022-11-23 11:38:35	ga_ls8c_ard_3-2-1_113073_2022-11-23_final
2022-11-24 10:42:58	ga_ls8c_ard_3-2-1_104073_2022-11-24_final
2022-11-25 09:47:21	ga_ls8c_ard_3-2-1_095073_2022-11-25_final
2022-12-02 11:32:26	ga_ls8c_ard_3-2-1_112073_2022-12-02_final
2022-12-03 10:36:48	ga_ls8c_ard_3-2-1_103073_2022-12-03_final
2022-12-04 09:41:11	ga_ls8c_ard_3-2-1_094073_2022-12-04_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