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
2018-05-26 10:58:38	ga_ls8c_ard_3-0-0_107070_2018-05-26_final
2018-06-04 10:52:22	ga_ls8c_ard_3-0-0_106070_2018-06-04_final
2018-06-05 09:56:21	ga_ls8c_ard_3-0-0_097069_2018-06-05_final
2018-06-05 09:56:44	ga_ls8c_ard_3-0-0_097070_2018-06-05_final
2018-06-06 10:40:00	ga_ls8c_ard_3-0-0_104070_2018-06-06_final
2018-09-06 11:05:08	ga_ls8c_ard_3-0-0_108069_2018-09-06_final
2018-09-06 11:05:32	ga_ls8c_ard_3-0-0_108070_2018-09-06_final
2018-09-07 10:09:31	ga_ls8c_ard_3-0-0_099069_2018-09-07_final
2018-09-07 10:09:55	ga_ls8c_ard_3-0-0_099070_2018-09-07_final
2018-09-08 10:53:11	ga_ls8c_ard_3-0-0_106070_2018-09-08_final
2018-09-09 09:57:10	ga_ls8c_ard_3-0-0_097069_2018-09-09_final
2018-09-09 09:57:34	ga_ls8c_ard_3-1-0_097070_2018-09-09_final
2018-09-10 10:40:50	ga_ls8c_ard_3-0-0_104070_2018-09-10_final
2018-09-16 10:03:46	ga_ls8c_ard_3-0-0_098070_2018-09-16_final
2018-09-17 10:47:02	ga_ls8c_ard_3-0-0_105070_2018-09-17_final
2019-01-06 10:03:37	ga_ls8c_ard_3-0-0_098069_2019-01-06_final
2019-01-06 10:04:01	ga_ls8c_ard_3-0-0_098070_2019-01-06_final
2019-01-07 10:47:16	ga_ls8c_ard_3-0-0_105070_2019-01-07_final
2022-10-28 11:00:24	ga_ls8c_ard_3-2-1_107070_2022-10-28_final
2022-10-29 10:04:47	ga_ls8c_ard_3-2-1_098070_2022-10-29_final
2022-10-30 10:48:03	ga_ls8c_ard_3-2-1_105070_2022-10-30_final
2022-10-31 09:52:26	ga_ls8c_ard_3-2-1_096070_2022-10-31_final
2022-11-01 10:35:42	ga_ls8c_ard_3-2-1_103070_2022-11-01_final
2022-11-02 11:18:57	ga_ls8c_ard_3-2-1_110070_2022-11-02_final
2022-11-03 10:23:20	ga_ls8c_ard_3-2-1_101070_2022-11-03_final
2022-11-04 11:06:35	ga_ls8c_ard_3-2-1_108070_2022-11-04_final
2022-11-05 10:10:58	ga_ls8c_ard_3-2-1_099070_2022-11-05_final
2022-11-06 10:54:13	ga_ls8c_ard_3-2-1_106070_2022-11-06_final
2022-11-07 09:58:36	ga_ls8c_ard_3-2-1_097070_2022-11-07_final
2022-11-08 10:41:51	ga_ls8c_ard_3-2-1_104070_2022-11-08_final
2022-11-15 10:47:57	ga_ls8c_ard_3-2-1_105070_2022-11-15_final
2022-11-16 09:52:19	ga_ls8c_ard_3-2-1_096070_2022-11-16_final
2022-11-17 10:35:34	ga_ls8c_ard_3-2-1_103070_2022-11-17_final
2022-11-18 11:18:49	ga_ls8c_ard_3-2-1_110070_2022-11-18_final
2022-11-19 10:23:12	ga_ls8c_ard_3-2-1_101070_2022-11-19_final
2022-11-20 11:06:28	ga_ls8c_ard_3-2-1_108070_2022-11-20_final
2022-11-21 10:10:51	ga_ls8c_ard_3-2-1_099070_2022-11-21_final
2022-11-24 10:41:47	ga_ls8c_ard_3-2-1_104070_2022-11-24_final
2022-11-25 11:25:02	ga_ls8c_ard_3-2-1_111070_2022-11-25_final
2022-11-26 10:29:25	ga_ls8c_ard_3-2-1_102070_2022-11-26_final
2022-11-27 11:12:41	ga_ls8c_ard_3-2-1_109070_2022-11-27_final
2022-11-29 11:00:20	ga_ls8c_ard_3-2-1_107070_2022-11-29_final
2022-11-30 10:04:43	ga_ls8c_ard_3-2-1_098070_2022-11-30_final
2022-12-01 10:47:58	ga_ls8c_ard_3-2-1_105070_2022-12-01_final
2022-12-02 09:52:21	ga_ls8c_ard_3-2-1_096070_2022-12-02_final
2022-12-04 11:18:52	ga_ls8c_ard_3-2-1_110070_2022-12-04_final
2022-12-05 10:23:15	ga_ls8c_ard_3-2-1_101070_2022-12-05_final
2022-12-06 11:06:30	ga_ls8c_ard_3-2-1_108070_2022-12-06_final
2022-12-07 10:10:53	ga_ls8c_ard_3-2-1_099070_2022-12-07_final
2022-12-10 10:41:46	ga_ls8c_ard_3-2-1_104070_2022-12-10_final
2022-12-16 10:04:37	ga_ls8c_ard_3-2-1_098070_2022-12-16_final
2022-12-17 10:47:52	ga_ls8c_ard_3-2-1_105070_2022-12-17_final
2022-12-18 09:52:14	ga_ls8c_ard_3-2-1_096070_2022-12-18_final
2022-12-19 10:35:29	ga_ls8c_ard_3-2-1_103070_2022-12-19_final
2022-12-20 11:18:43	ga_ls8c_ard_3-2-1_110070_2022-12-20_final
2022-12-21 10:23:05	ga_ls8c_ard_3-2-1_101070_2022-12-21_final
2022-12-22 11:06:20	ga_ls8c_ard_3-2-1_108070_2022-12-22_final
2022-12-23 10:10:42	ga_ls8c_ard_3-2-1_099070_2022-12-23_final
2022-12-25 09:58:21	ga_ls8c_ard_3-2-1_097070_2022-12-25_final
2022-12-26 10:41:37	ga_ls8c_ard_3-2-1_104070_2022-12-26_final
2022-12-27 11:24:54	ga_ls8c_ard_3-2-1_111070_2022-12-27_final
2022-12-28 10:29:16	ga_ls8c_ard_3-2-1_102070_2022-12-28_final
2022-12-29 11:12:32	ga_ls8c_ard_3-2-1_109070_2022-12-29_final
2022-12-31 11:00:11	ga_ls8c_ard_3-2-1_107070_2022-12-31_final
2023-01-01 10:04:34	ga_ls8c_ard_3-2-1_098070_2023-01-01_final
2023-01-02 10:47:49	ga_ls8c_ard_3-2-1_105070_2023-01-02_final
2023-01-03 09:52:12	ga_ls8c_ard_3-2-1_096070_2023-01-03_final
2023-02-17 11:00:00	ga_ls8c_ard_3-2-1_107070_2023-02-17_final
2023-02-21 10:35:12	ga_ls8c_ard_3-2-1_103070_2023-02-21_final
2023-02-22 11:18:26	ga_ls8c_ard_3-2-1_110070_2023-02-22_final
2023-02-25 10:10:23	ga_ls8c_ard_3-2-1_099070_2023-02-25_final
2023-02-27 09:58:01	ga_ls8c_ard_3-2-1_097070_2023-02-27_final
2023-02-28 10:41:17	ga_ls8c_ard_3-2-1_104070_2023-02-28_final
2023-07-25 11:11:54	ga_ls8c_ard_3-2-1_109070_2023-07-25_final
2023-07-28 10:03:33	ga_ls8c_ard_3-2-1_098069_2023-07-28_final
2023-07-28 10:03:57	ga_ls8c_ard_3-2-1_098070_2023-07-28_final
2023-07-29 10:46:49	ga_ls8c_ard_3-2-1_105069_2023-07-29_final
2023-07-29 10:47:13	ga_ls8c_ard_3-2-1_105070_2023-07-29_final
2023-07-30 09:51:37	ga_ls8c_ard_3-2-1_096070_2023-07-30_final
2023-07-31 10:34:53	ga_ls8c_ard_3-2-1_103070_2023-07-31_final
2023-08-01 11:17:45	ga_ls8c_ard_3-2-1_110069_2023-08-01_final
2023-08-01 11:18:09	ga_ls8c_ard_3-2-1_110070_2023-08-01_final
2023-08-02 10:22:32	ga_ls8c_ard_3-2-1_101070_2023-08-02_final
2023-08-03 11:05:48	ga_ls8c_ard_3-2-1_108070_2023-08-03_final
2023-08-04 10:10:11	ga_ls8c_ard_3-2-1_099070_2023-08-04_final
2023-08-05 10:53:27	ga_ls8c_ard_3-2-1_106070_2023-08-05_final
2023-08-06 09:57:26	ga_ls8c_ard_3-2-1_097069_2023-08-06_final
2023-08-06 09:57:50	ga_ls8c_ard_3-2-1_097070_2023-08-06_final
2023-08-07 10:41:05	ga_ls8c_ard_3-2-1_104070_2023-08-07_final
2023-08-08 11:23:57	ga_ls8c_ard_3-2-1_111069_2023-08-08_final
2023-08-08 11:24:21	ga_ls8c_ard_3-2-1_111070_2023-08-08_final
2023-08-09 10:28:43	ga_ls8c_ard_3-2-1_102070_2023-08-09_final
2023-08-10 11:11:59	ga_ls8c_ard_3-2-1_109070_2023-08-10_final
2023-08-12 10:59:14	ga_ls8c_ard_3-2-1_107069_2023-08-12_final
2023-08-12 10:59:38	ga_ls8c_ard_3-2-1_107070_2023-08-12_final
2023-08-13 10:03:38	ga_ls8c_ard_3-2-1_098069_2023-08-13_final
2023-08-13 10:04:02	ga_ls8c_ard_3-2-1_098070_2023-08-13_final
2023-08-14 10:46:55	ga_ls8c_ard_3-2-1_105069_2023-08-14_final
2023-08-14 10:47:18	ga_ls8c_ard_3-2-1_105070_2023-08-14_final
2023-08-15 09:51:42	ga_ls8c_ard_3-2-1_096070_2023-08-15_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