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
2018-09-15 10:58:59	ga_ls8c_ard_3-0-0_107069_2018-09-15_final
2018-09-15 10:59:23	ga_ls8c_ard_3-0-0_107070_2018-09-15_final
2018-09-16 10:03:22	ga_ls8c_ard_3-0-0_098069_2018-09-16_final
2018-09-17 10:46:38	ga_ls8c_ard_3-0-0_105069_2018-09-17_final
2018-09-22 11:05:12	ga_ls8c_ard_3-0-0_108069_2018-09-22_final
2018-09-23 10:09:35	ga_ls8c_ard_3-0-0_099069_2018-09-23_final
2018-09-24 10:52:52	ga_ls8c_ard_3-0-0_106069_2018-09-24_final
2018-09-25 09:57:15	ga_ls8c_ard_3-0-0_097069_2018-09-25_final
2018-09-25 09:57:39	ga_ls8c_ard_3-0-0_097070_2018-09-25_final
2018-09-26 10:40:31	ga_ls8c_ard_3-0-0_104069_2018-09-26_final
2018-09-27 09:45:18	ga_ls8c_ard_3-0-0_095070_2018-09-27_final
2018-09-27 11:23:48	ga_ls8c_ard_3-0-0_111069_2018-09-27_final
2018-09-28 10:28:11	ga_ls8c_ard_3-0-0_102069_2018-09-28_final
2018-09-29 11:11:27	ga_ls8c_ard_3-0-0_109069_2018-09-29_final
2018-09-30 10:15:50	ga_ls8c_ard_3-0-0_100069_2018-09-30_final
2018-10-02 10:03:29	ga_ls8c_ard_3-0-0_098069_2018-10-02_final
2018-10-03 10:46:46	ga_ls8c_ard_3-0-0_105069_2018-10-03_final
2018-10-04 09:51:09	ga_ls8c_ard_3-0-0_096069_2018-10-04_final
2018-10-04 11:30:02	ga_ls8c_ard_3-0-0_112069_2018-10-04_final
2018-10-05 10:34:25	ga_ls8c_ard_3-0-0_103069_2018-10-05_final
2018-10-06 11:17:41	ga_ls8c_ard_3-0-0_110069_2018-10-06_final
2018-10-07 10:22:04	ga_ls8c_ard_3-0-0_101069_2018-10-07_final
2018-10-07 10:22:28	ga_ls8c_ard_3-0-0_101070_2018-10-07_final
2018-10-08 11:05:20	ga_ls8c_ard_3-0-0_108069_2018-10-08_final
2018-10-09 10:09:44	ga_ls8c_ard_3-0-0_099069_2018-10-09_final
2018-10-10 10:53:00	ga_ls8c_ard_3-0-0_106069_2018-10-10_final
2018-10-11 09:57:23	ga_ls8c_ard_3-0-0_097069_2018-10-11_final
2018-10-12 10:40:39	ga_ls8c_ard_3-0-0_104069_2018-10-12_final
2018-10-15 11:11:34	ga_ls8c_ard_3-0-0_109069_2018-10-15_final
2018-10-16 10:15:57	ga_ls8c_ard_3-0-0_100069_2018-10-16_final
2018-10-17 10:59:13	ga_ls8c_ard_3-0-0_107069_2018-10-17_final
2018-10-18 10:03:36	ga_ls8c_ard_3-0-0_098069_2018-10-18_final
2018-10-19 10:46:52	ga_ls8c_ard_3-0-0_105069_2018-10-19_final
2018-10-24 11:05:26	ga_ls8c_ard_3-0-0_108069_2018-10-24_final
2018-10-24 11:05:50	ga_ls8c_ard_3-0-0_108070_2018-10-24_final
2018-10-25 10:09:49	ga_ls8c_ard_3-0-0_099069_2018-10-25_final
2018-10-26 10:53:05	ga_ls8c_ard_3-0-0_106069_2018-10-26_final
2018-10-26 10:53:29	ga_ls8c_ard_3-0-0_106070_2018-10-26_final
2018-10-27 09:57:28	ga_ls8c_ard_3-0-0_097069_2018-10-27_final
2018-10-28 10:40:44	ga_ls8c_ard_3-0-0_104069_2018-10-28_final
2018-10-29 11:24:00	ga_ls8c_ard_3-0-0_111069_2018-10-29_final
2018-10-30 10:28:23	ga_ls8c_ard_3-0-0_102069_2018-10-30_final
2018-10-31 11:11:38	ga_ls8c_ard_3-0-0_109069_2018-10-31_final
2018-11-01 10:16:01	ga_ls8c_ard_3-0-0_100069_2018-11-01_final
2018-11-18 10:59:18	ga_ls8c_ard_3-0-0_107069_2018-11-18_final
2018-11-25 11:05:29	ga_ls8c_ard_3-0-0_108069_2018-11-25_final
2018-11-26 10:09:51	ga_ls8c_ard_3-0-0_099069_2018-11-26_final
2018-11-27 10:53:07	ga_ls8c_ard_3-0-0_106069_2018-11-27_final
2018-11-28 09:57:29	ga_ls8c_ard_3-0-0_097069_2018-11-28_final
2018-11-29 10:40:45	ga_ls8c_ard_3-0-0_104069_2018-11-29_final
2018-11-30 11:24:01	ga_ls8c_ard_3-0-0_111069_2018-11-30_final
2018-12-01 10:28:23	ga_ls8c_ard_3-0-0_102069_2018-12-01_final
2018-12-02 11:11:39	ga_ls8c_ard_3-0-0_109069_2018-12-02_final
2018-12-03 10:16:01	ga_ls8c_ard_3-0-0_100069_2018-12-03_final
2018-12-05 10:03:39	ga_ls8c_ard_3-0-0_098069_2018-12-05_final
2018-12-06 10:46:54	ga_ls8c_ard_3-0-0_105069_2018-12-06_final
2018-12-07 09:51:17	ga_ls8c_ard_3-0-0_096069_2018-12-07_final
2018-12-07 11:30:10	ga_ls8c_ard_3-0-0_112069_2018-12-07_final
2018-12-08 10:34:32	ga_ls8c_ard_3-0-0_103069_2018-12-08_final
2018-12-09 11:17:48	ga_ls8c_ard_3-0-0_110069_2018-12-09_final
2018-12-10 10:22:10	ga_ls8c_ard_3-0-0_101069_2018-12-10_final
2018-12-13 10:53:03	ga_ls8c_ard_3-0-0_106069_2018-12-13_final
2018-12-14 09:57:26	ga_ls8c_ard_3-0-0_097069_2018-12-14_final
2018-12-15 10:40:42	ga_ls8c_ard_3-0-0_104069_2018-12-15_final
2018-12-16 11:23:58	ga_ls8c_ard_3-0-0_111069_2018-12-16_final
2018-12-17 10:28:20	ga_ls8c_ard_3-0-0_102069_2018-12-17_final
2018-12-18 11:11:36	ga_ls8c_ard_3-0-0_109069_2018-12-18_final
2018-12-19 10:15:59	ga_ls8c_ard_3-0-0_100069_2018-12-19_final
2018-12-21 10:03:37	ga_ls8c_ard_3-0-0_098069_2018-12-21_final
2018-12-22 10:46:53	ga_ls8c_ard_3-0-0_105069_2018-12-22_final
2018-12-23 09:51:16	ga_ls8c_ard_3-0-0_096069_2018-12-23_final
2018-12-23 11:30:09	ga_ls8c_ard_3-0-0_112069_2018-12-23_final
2018-12-24 10:34:32	ga_ls8c_ard_3-0-0_103069_2018-12-24_final
2018-12-25 11:17:47	ga_ls8c_ard_3-0-0_110069_2018-12-25_final
2018-12-26 10:22:10	ga_ls8c_ard_3-0-0_101069_2018-12-26_final
2018-12-27 11:05:26	ga_ls8c_ard_3-0-0_108069_2018-12-27_final
2018-12-28 10:09:48	ga_ls8c_ard_3-0-0_099069_2018-12-28_final
2018-12-29 10:53:04	ga_ls8c_ard_3-0-0_106069_2018-12-29_final
2018-12-30 09:57:26	ga_ls8c_ard_3-0-0_097069_2018-12-30_final
2018-12-31 10:40:42	ga_ls8c_ard_3-0-0_104069_2018-12-31_final
2019-01-03 11:11:36	ga_ls8c_ard_3-0-0_109069_2019-01-03_final
2019-01-04 10:15:59	ga_ls8c_ard_3-0-0_100069_2019-01-04_final
2019-01-05 10:59:14	ga_ls8c_ard_3-0-0_107069_2019-01-05_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
2019-01-20 10:15:55	ga_ls8c_ard_3-0-0_100069_2019-01-20_final
2023-07-22 10:40:33	ga_ls8c_ard_3-2-1_104069_2023-07-22_final
2023-07-23 11:23:50	ga_ls8c_ard_3-2-1_111069_2023-07-23_final
2023-08-24 11:24:05	ga_ls8c_ard_3-2-1_111069_2023-08-24_final
2023-08-25 10:28:28	ga_ls8c_ard_3-2-1_102069_2023-08-25_final
2023-08-25 10:28:52	ga_ls8c_ard_3-2-1_102070_2023-08-25_final
2023-08-26 11:11:44	ga_ls8c_ard_3-2-1_109069_2023-08-26_final
2023-08-28 10:59:22	ga_ls8c_ard_3-2-1_107069_2023-08-28_final
2023-08-29 10:03:45	ga_ls8c_ard_3-2-1_098069_2023-08-29_final
2023-08-29 10:04:09	ga_ls8c_ard_3-2-1_098070_2023-08-29_final
2023-08-30 10:47:01	ga_ls8c_ard_3-2-1_105069_2023-08-30_final
2023-08-31 09:51:47	ga_ls8c_ard_3-2-1_096070_2023-08-31_final
2023-09-01 10:34:39	ga_ls8c_ard_3-2-1_103069_2023-09-01_final
2023-09-08 10:40:48	ga_ls8c_ard_3-2-1_104069_2023-09-08_final
2023-09-09 11:24:05	ga_ls8c_ard_3-2-1_111069_2023-09-09_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