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
2015-01-17 11:05:58	ga_ls8c_ard_3-0-0_108070_2015-01-17_final
2015-01-18 10:10:20	ga_ls8c_ard_3-0-0_099070_2015-01-18_final
2015-01-19 10:53:35	ga_ls8c_ard_3-0-0_106070_2015-01-19_final
2015-02-19 10:10:08	ga_ls8c_ard_3-0-0_099070_2015-02-19_final
2015-02-20 10:53:24	ga_ls8c_ard_3-0-0_106070_2015-02-20_final
2015-02-28 10:03:55	ga_ls8c_ard_3-0-0_098070_2015-02-28_final
2015-03-01 10:47:11	ga_ls8c_ard_3-0-0_105070_2015-03-01_final
2019-07-04 10:34:34	ga_ls8c_ard_3-1-0_103069_2019-07-04_final
2019-07-04 10:34:58	ga_ls8c_ard_3-1-0_103070_2019-07-04_final
2019-07-05 11:17:50	ga_ls8c_ard_3-1-0_110069_2019-07-05_final
2019-07-05 11:18:14	ga_ls8c_ard_3-1-0_110070_2019-07-05_final
2019-07-06 10:22:13	ga_ls8c_ard_3-1-0_101069_2019-07-06_final
2019-07-06 10:22:36	ga_ls8c_ard_3-1-0_101070_2019-07-06_final
2019-07-07 11:05:28	ga_ls8c_ard_3-1-0_108069_2019-07-07_final
2019-07-07 11:05:52	ga_ls8c_ard_3-1-0_108070_2019-07-07_final
2019-07-13 10:28:24	ga_ls8c_ard_3-1-0_102069_2019-07-13_final
2019-07-13 10:28:48	ga_ls8c_ard_3-1-0_102070_2019-07-13_final
2019-07-14 11:11:40	ga_ls8c_ard_3-1-0_109069_2019-07-14_final
2019-07-14 11:12:04	ga_ls8c_ard_3-1-0_109070_2019-07-14_final
2019-07-15 10:16:03	ga_ls8c_ard_3-1-0_100069_2019-07-15_final
2019-07-15 10:16:27	ga_ls8c_ard_3-1-0_100070_2019-07-15_final
2019-07-16 10:59:19	ga_ls8c_ard_3-1-0_107069_2019-07-16_final
2019-07-16 10:59:43	ga_ls8c_ard_3-1-0_107070_2019-07-16_final
2019-07-26 09:57:35	ga_ls8c_ard_3-1-0_097069_2019-07-26_final
2019-07-26 09:57:58	ga_ls8c_ard_3-1-0_097070_2019-07-26_final
2019-07-27 10:41:15	ga_ls8c_ard_3-1-0_104070_2019-07-27_final
2019-07-28 09:45:38	ga_ls8c_ard_3-1-0_095070_2019-07-28_final
2019-07-28 11:24:07	ga_ls8c_ard_3-1-0_111069_2019-07-28_final
2019-07-28 11:24:31	ga_ls8c_ard_3-1-0_111070_2019-07-28_final
2019-07-29 10:28:30	ga_ls8c_ard_3-1-0_102069_2019-07-29_final
2019-07-29 10:28:54	ga_ls8c_ard_3-1-0_102070_2019-07-29_final
2019-08-21 10:34:49	ga_ls8c_ard_3-1-0_103069_2019-08-21_final
2019-08-21 10:35:12	ga_ls8c_ard_3-1-0_103070_2019-08-21_final
2019-08-22 11:18:04	ga_ls8c_ard_3-1-0_110069_2019-08-22_final
2019-08-22 11:18:28	ga_ls8c_ard_3-1-0_110070_2019-08-22_final
2019-08-23 10:22:27	ga_ls8c_ard_3-1-0_101069_2019-08-23_final
2019-08-23 10:22:51	ga_ls8c_ard_3-1-0_101070_2019-08-23_final
2019-08-24 11:05:43	ga_ls8c_ard_3-1-0_108069_2019-08-24_final
2019-08-24 11:06:07	ga_ls8c_ard_3-1-0_108070_2019-08-24_final
2019-09-12 09:57:49	ga_ls8c_ard_3-1-0_097069_2019-09-12_final
2019-09-12 09:58:13	ga_ls8c_ard_3-1-0_097070_2019-09-12_final
2019-09-13 10:41:29	ga_ls8c_ard_3-1-0_104070_2019-09-13_final
2019-09-14 09:45:52	ga_ls8c_ard_3-1-0_095070_2019-09-14_final
2019-09-14 11:24:45	ga_ls8c_ard_3-1-0_111070_2019-09-14_final
2019-09-15 10:28:45	ga_ls8c_ard_3-1-0_102069_2019-09-15_final
2019-09-15 10:29:08	ga_ls8c_ard_3-1-0_102070_2019-09-15_final
2019-09-22 10:34:58	ga_ls8c_ard_3-1-0_103069_2019-09-22_final
2019-09-22 10:35:22	ga_ls8c_ard_3-1-0_103070_2019-09-22_final
2019-09-23 11:18:14	ga_ls8c_ard_3-1-0_110069_2019-09-23_final
2019-09-23 11:18:38	ga_ls8c_ard_3-1-0_110070_2019-09-23_final
2019-09-24 10:22:37	ga_ls8c_ard_3-1-0_101069_2019-09-24_final
2019-09-24 10:23:01	ga_ls8c_ard_3-1-0_101070_2019-09-24_final
2019-09-25 11:05:53	ga_ls8c_ard_3-1-0_108069_2019-09-25_final
2019-09-25 11:06:17	ga_ls8c_ard_3-1-0_108070_2019-09-25_final
2019-10-01 10:28:49	ga_ls8c_ard_3-1-0_102069_2019-10-01_final
2019-10-01 10:29:13	ga_ls8c_ard_3-1-0_102070_2019-10-01_final
2019-10-02 11:12:05	ga_ls8c_ard_3-1-0_109069_2019-10-02_final
2019-10-02 11:12:29	ga_ls8c_ard_3-1-0_109070_2019-10-02_final
2019-10-03 10:16:52	ga_ls8c_ard_3-1-0_100070_2019-10-03_final
2019-10-04 10:59:44	ga_ls8c_ard_3-1-0_107069_2019-10-04_final
2019-10-04 11:00:08	ga_ls8c_ard_3-1-0_107070_2019-10-04_final
2019-11-01 09:46:00	ga_ls8c_ard_3-1-0_095070_2019-11-01_final
2019-11-01 11:24:29	ga_ls8c_ard_3-1-0_111069_2019-11-01_final
2019-11-01 11:24:53	ga_ls8c_ard_3-1-0_111070_2019-11-01_final
2019-11-02 10:29:15	ga_ls8c_ard_3-1-0_102070_2019-11-02_final
2019-11-09 10:35:25	ga_ls8c_ard_3-1-0_103070_2019-11-09_final
2019-11-10 11:18:41	ga_ls8c_ard_3-1-0_110070_2019-11-10_final
2019-11-11 10:22:39	ga_ls8c_ard_3-1-0_101069_2019-11-11_final
2019-11-11 10:23:03	ga_ls8c_ard_3-1-0_101070_2019-11-11_final
2019-11-12 11:05:55	ga_ls8c_ard_3-1-0_108069_2019-11-12_final
2019-11-12 11:06:18	ga_ls8c_ard_3-1-0_108070_2019-11-12_final
2019-11-18 10:29:12	ga_ls8c_ard_3-1-0_102070_2019-11-18_final
2019-11-19 11:12:27	ga_ls8c_ard_3-1-0_109070_2019-11-19_final
2019-11-20 10:16:26	ga_ls8c_ard_3-1-0_100069_2019-11-20_final
2019-11-20 10:16:50	ga_ls8c_ard_3-1-0_100070_2019-11-20_final
2019-11-21 11:00:05	ga_ls8c_ard_3-1-0_107070_2019-11-21_final
2023-02-01 11:00:09	ga_ls8c_ard_3-2-1_107070_2023-02-01_final
2023-02-02 10:04:32	ga_ls8c_ard_3-2-1_098070_2023-02-02_final
2023-02-03 10:47:47	ga_ls8c_ard_3-2-1_105070_2023-02-03_final
2023-02-04 09:52:10	ga_ls8c_ard_3-2-1_096070_2023-02-04_final
2023-02-27 09:58:01	ga_ls8c_ard_3-2-1_097070_2023-02-27_final
2023-03-21 10:59:39	ga_ls8c_ard_3-2-1_107070_2023-03-21_final
2023-03-22 10:04:01	ga_ls8c_ard_3-2-1_098070_2023-03-22_final
2023-03-23 10:47:15	ga_ls8c_ard_3-2-1_105070_2023-03-23_final
2023-03-24 09:51:37	ga_ls8c_ard_3-2-1_096070_2023-03-24_final
2023-04-08 10:47:02	ga_ls8c_ard_3-2-1_105070_2023-04-08_final
2023-04-09 09:51:24	ga_ls8c_ard_3-2-1_096070_2023-04-09_final
2023-04-10 10:34:38	ga_ls8c_ard_3-2-1_103070_2023-04-10_final
2023-04-11 11:17:52	ga_ls8c_ard_3-2-1_110070_2023-04-11_final
2023-04-12 10:22:15	ga_ls8c_ard_3-2-1_101070_2023-04-12_final
2023-04-13 11:05:30	ga_ls8c_ard_3-2-1_108070_2023-04-13_final
2023-04-14 10:09:53	ga_ls8c_ard_3-2-1_099070_2023-04-14_final
2023-04-15 10:53:08	ga_ls8c_ard_3-2-1_106070_2023-04-15_final
2023-04-16 09:57:31	ga_ls8c_ard_3-2-1_097070_2023-04-16_final
2023-04-17 10:40:46	ga_ls8c_ard_3-2-1_104070_2023-04-17_final
2023-04-18 11:24:01	ga_ls8c_ard_3-2-1_111070_2023-04-18_final
2023-04-24 10:46:56	ga_ls8c_ard_3-2-1_105070_2023-04-24_final
2023-04-25 09:51:18	ga_ls8c_ard_3-2-1_096070_2023-04-25_final
2023-04-26 10:34:34	ga_ls8c_ard_3-2-1_103070_2023-04-26_final
2023-04-27 11:17:49	ga_ls8c_ard_3-2-1_110070_2023-04-27_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