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
2018-07-04 11:04:38	ga_ls8c_ard_3-0-0_108069_2018-07-04_final
2018-07-05 10:09:01	ga_ls8c_ard_3-0-0_099069_2018-07-05_final
2018-07-05 10:09:25	ga_ls8c_ard_3-0-0_099070_2018-07-05_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
2018-07-07 09:56:40	ga_ls8c_ard_3-0-0_097069_2018-07-07_final
2018-07-07 09:57:04	ga_ls8c_ard_3-0-0_097070_2018-07-07_final
2018-07-08 10:39:57	ga_ls8c_ard_3-0-0_104069_2018-07-08_final
2018-07-08 10:40:20	ga_ls8c_ard_3-0-0_104070_2018-07-08_final
2018-07-22 10:52:24	ga_ls8c_ard_3-0-0_106069_2018-07-22_final
2018-07-23 09:56:47	ga_ls8c_ard_3-0-0_097069_2018-07-23_final
2018-07-24 10:40:03	ga_ls8c_ard_3-0-0_104069_2018-07-24_final
2018-07-24 10:40:27	ga_ls8c_ard_3-0-0_104070_2018-07-24_final
2018-08-05 11:04:53	ga_ls8c_ard_3-0-0_108069_2018-08-05_final
2018-08-05 11:05:17	ga_ls8c_ard_3-0-0_108070_2018-08-05_final
2018-08-06 10:09:16	ga_ls8c_ard_3-0-0_099069_2018-08-06_final
2018-08-06 10:09:40	ga_ls8c_ard_3-0-0_099070_2018-08-06_final
2018-09-16 10:03:22	ga_ls8c_ard_3-0-0_098069_2018-09-16_final
2018-09-16 10:03:46	ga_ls8c_ard_3-0-0_098070_2018-09-16_final
2018-09-17 10:46:38	ga_ls8c_ard_3-0-0_105069_2018-09-17_final
2019-01-06 10:03:37	ga_ls8c_ard_3-0-0_098069_2019-01-06_final
2019-01-07 10:46:52	ga_ls8c_ard_3-0-0_105069_2019-01-07_final
2022-08-19 09:58:06	ga_ls8c_ard_3-2-1_097069_2022-08-19_final
2022-08-19 09:58:30	ga_ls8c_ard_3-2-1_097070_2022-08-19_final
2022-08-21 11:24:38	ga_ls8c_ard_3-2-1_111069_2022-08-21_final
2022-08-22 10:29:00	ga_ls8c_ard_3-2-1_102069_2022-08-22_final
2022-08-23 11:12:16	ga_ls8c_ard_3-2-1_109069_2022-08-23_final
2022-08-25 10:59:54	ga_ls8c_ard_3-2-1_107069_2022-08-25_final
2022-08-25 11:00:18	ga_ls8c_ard_3-2-1_107070_2022-08-25_final
2022-08-26 10:04:17	ga_ls8c_ard_3-2-1_098069_2022-08-26_final
2022-08-26 10:04:41	ga_ls8c_ard_3-2-1_098070_2022-08-26_final
2022-08-29 10:35:11	ga_ls8c_ard_3-2-1_103069_2022-08-29_final
2022-08-29 10:35:35	ga_ls8c_ard_3-2-1_103070_2022-08-29_final
2022-08-30 11:18:27	ga_ls8c_ard_3-2-1_110069_2022-08-30_final
2022-08-31 10:22:49	ga_ls8c_ard_3-2-1_101069_2022-08-31_final
2022-08-31 10:23:13	ga_ls8c_ard_3-2-1_101070_2022-08-31_final
2022-09-01 11:06:05	ga_ls8c_ard_3-2-1_108069_2022-09-01_final
2022-09-02 10:10:27	ga_ls8c_ard_3-2-1_099069_2022-09-02_final
2022-09-02 10:10:51	ga_ls8c_ard_3-2-1_099070_2022-09-02_final
2022-09-03 10:53:43	ga_ls8c_ard_3-2-1_106069_2022-09-03_final
2022-09-03 10:54:07	ga_ls8c_ard_3-2-1_106070_2022-09-03_final
2022-09-04 09:58:06	ga_ls8c_ard_3-2-1_097069_2022-09-04_final
2022-09-05 10:41:23	ga_ls8c_ard_3-2-1_104069_2022-09-05_final
2022-09-08 11:12:19	ga_ls8c_ard_3-2-1_109069_2022-09-08_final
2022-09-08 11:12:43	ga_ls8c_ard_3-2-1_109070_2022-09-08_final
2022-09-26 11:00:01	ga_ls8c_ard_3-2-1_107069_2022-09-26_final
2022-09-27 10:04:24	ga_ls8c_ard_3-2-1_098069_2022-09-27_final
2022-09-27 10:04:48	ga_ls8c_ard_3-2-1_098070_2022-09-27_final
2022-09-28 10:47:39	ga_ls8c_ard_3-2-1_105069_2022-09-28_final
2022-09-29 09:52:26	ga_ls8c_ard_3-2-1_096070_2022-09-29_final
2022-09-30 10:35:17	ga_ls8c_ard_3-2-1_103069_2022-09-30_final
2022-10-01 11:18:33	ga_ls8c_ard_3-2-1_110069_2022-10-01_final
2022-10-02 10:22:55	ga_ls8c_ard_3-2-1_101069_2022-10-02_final
2022-10-03 11:06:10	ga_ls8c_ard_3-2-1_108069_2022-10-03_final
2022-10-04 10:10:33	ga_ls8c_ard_3-2-1_099069_2022-10-04_final
2022-10-04 10:10:57	ga_ls8c_ard_3-2-1_099070_2022-10-04_final
2022-10-05 10:53:48	ga_ls8c_ard_3-2-1_106069_2022-10-05_final
2022-10-06 09:58:10	ga_ls8c_ard_3-2-1_097069_2022-10-06_final
2022-10-09 10:29:02	ga_ls8c_ard_3-2-1_102069_2022-10-09_final
2022-10-09 10:29:26	ga_ls8c_ard_3-2-1_102070_2022-10-09_final
2022-10-10 11:12:17	ga_ls8c_ard_3-2-1_109069_2022-10-10_final
2022-10-10 11:12:41	ga_ls8c_ard_3-2-1_109070_2022-10-10_final
2022-11-09 11:24:42	ga_ls8c_ard_3-2-1_111069_2022-11-09_final
2022-11-10 10:29:05	ga_ls8c_ard_3-2-1_102069_2022-11-10_final
2022-11-10 10:29:28	ga_ls8c_ard_3-2-1_102070_2022-11-10_final
2022-11-11 11:12:20	ga_ls8c_ard_3-2-1_109069_2022-11-11_final
2022-11-11 11:12:44	ga_ls8c_ard_3-2-1_109070_2022-11-11_final
2022-11-13 10:59:57	ga_ls8c_ard_3-2-1_107069_2022-11-13_final
2022-11-14 10:04:19	ga_ls8c_ard_3-2-1_098069_2022-11-14_final
2022-11-15 10:47:33	ga_ls8c_ard_3-2-1_105069_2022-11-15_final
2022-11-17 10:35:10	ga_ls8c_ard_3-2-1_103069_2022-11-17_final
2022-11-18 11:18:25	ga_ls8c_ard_3-2-1_110069_2022-11-18_final
2022-11-19 10:22:48	ga_ls8c_ard_3-2-1_101069_2022-11-19_final
2022-11-20 11:06:04	ga_ls8c_ard_3-2-1_108069_2022-11-20_final
2022-11-20 11:06:28	ga_ls8c_ard_3-2-1_108070_2022-11-20_final
2022-11-21 10:10:28	ga_ls8c_ard_3-2-1_099069_2022-11-21_final
2023-04-14 10:09:29	ga_ls8c_ard_3-2-1_099069_2023-04-14_final
2023-04-15 10:52:44	ga_ls8c_ard_3-2-1_106069_2023-04-15_final
2023-07-18 11:05:15	ga_ls8c_ard_3-2-1_108069_2023-07-18_final
2023-07-18 11:05:39	ga_ls8c_ard_3-2-1_108070_2023-07-18_final
2023-07-19 10:09:38	ga_ls8c_ard_3-2-1_099069_2023-07-19_final
2023-07-19 10:10:02	ga_ls8c_ard_3-2-1_099070_2023-07-19_final
2023-07-22 10:40:33	ga_ls8c_ard_3-2-1_104069_2023-07-22_final
2023-07-22 10:40:57	ga_ls8c_ard_3-2-1_104070_2023-07-22_final
2023-07-23 11:23:50	ga_ls8c_ard_3-2-1_111069_2023-07-23_final
2023-07-23 11:24:13	ga_ls8c_ard_3-2-1_111070_2023-07-23_final
2023-09-02 11:17:54	ga_ls8c_ard_3-2-1_110069_2023-09-02_final
2023-09-03 10:22:16	ga_ls8c_ard_3-2-1_101069_2023-09-03_final
2023-09-04 11:05:32	ga_ls8c_ard_3-2-1_108069_2023-09-04_final
2023-09-09 11:24:05	ga_ls8c_ard_3-2-1_111069_2023-09-09_final
2023-09-09 11:24:29	ga_ls8c_ard_3-2-1_111070_2023-09-09_final
2023-09-10 10:28:28	ga_ls8c_ard_3-2-1_102069_2023-09-10_final
2023-09-10 10:28:52	ga_ls8c_ard_3-2-1_102070_2023-09-10_final
2023-09-13 10:59:25	ga_ls8c_ard_3-2-1_107069_2023-09-13_final
2023-10-11 11:24:15	ga_ls8c_ard_3-2-1_111069_2023-10-11_final
2023-10-11 11:24:39	ga_ls8c_ard_3-2-1_111070_2023-10-11_final
2023-10-12 10:28:38	ga_ls8c_ard_3-2-1_102069_2023-10-12_final
2023-10-13 11:11:54	ga_ls8c_ard_3-2-1_109069_2023-10-13_final
2023-10-13 11:12:18	ga_ls8c_ard_3-2-1_109070_2023-10-13_final
2023-10-15 10:59:32	ga_ls8c_ard_3-2-1_107069_2023-10-15_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