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
2016-01-04 09:32:20	ga_ls8c_ard_3-0-0_092083_2016-01-04_final
2016-01-04 11:11:13	ga_ls8c_ard_3-0-0_108083_2016-01-04_final
2016-01-05 10:15:36	ga_ls8c_ard_3-0-0_099083_2016-01-05_final
2016-01-06 09:19:58	ga_ls8c_ard_3-0-0_090083_2016-01-05_final
2016-01-06 10:58:51	ga_ls8c_ard_3-0-0_106083_2016-01-06_final
2016-01-07 10:03:13	ga_ls8c_ard_3-0-0_097083_2016-01-07_final
2016-01-07 11:42:06	ga_ls8c_ard_3-0-0_113083_2016-01-07_final
2016-01-08 10:46:28	ga_ls8c_ard_3-0-0_104083_2016-01-08_final
2016-01-29 09:26:08	ga_ls8c_ard_3-0-0_091083_2016-01-28_final
2016-01-29 11:04:37	ga_ls8c_ard_3-1-0_107082_2016-01-29_final
2016-01-30 10:09:24	ga_ls8c_ard_3-0-0_098083_2016-01-30_final
2016-01-31 09:13:46	ga_ls8c_ard_3-0-0_089083_2016-01-30_final
2016-01-31 10:52:39	ga_ls8c_ard_3-0-0_105083_2016-01-31_final
2016-02-01 09:57:02	ga_ls8c_ard_3-0-0_096083_2016-02-01_final
2016-02-01 11:35:55	ga_ls8c_ard_3-0-0_112083_2016-02-01_final
2016-02-02 10:40:17	ga_ls8c_ard_3-0-0_103083_2016-02-02_final
2016-02-15 10:09:16	ga_ls8c_ard_3-0-0_098083_2016-02-15_final
2016-02-16 09:13:38	ga_ls8c_ard_3-0-0_089083_2016-02-15_final
2016-02-16 10:52:31	ga_ls8c_ard_3-0-0_105083_2016-02-16_final
2018-02-22 09:56:44	ga_ls8c_ard_3-0-0_096083_2018-02-22_final
2018-02-22 11:35:37	ga_ls8c_ard_3-0-0_112083_2018-02-22_final
2018-02-23 10:39:59	ga_ls8c_ard_3-0-0_103083_2018-02-23_final
2018-02-24 09:44:21	ga_ls8c_ard_3-0-0_094083_2018-02-24_final
2018-02-24 11:23:14	ga_ls8c_ard_3-0-0_110083_2018-02-24_final
2018-02-25 10:27:37	ga_ls8c_ard_3-0-0_101083_2018-02-25_final
2018-03-10 09:56:35	ga_ls8c_ard_3-0-0_096083_2018-03-10_final
2018-03-10 11:35:29	ga_ls8c_ard_3-0-0_112083_2018-03-10_final
2018-03-11 10:39:51	ga_ls8c_ard_3-0-0_103083_2018-03-11_final
2018-03-12 09:44:13	ga_ls8c_ard_3-0-0_094083_2018-03-12_final
2018-03-12 11:23:06	ga_ls8c_ard_3-0-0_110083_2018-03-12_final
2018-03-13 10:27:28	ga_ls8c_ard_3-0-0_101083_2018-03-13_final
2018-04-11 09:56:20	ga_ls8c_ard_3-0-0_096083_2018-04-11_final
2018-04-11 11:35:13	ga_ls8c_ard_3-0-0_112083_2018-04-11_final
2018-04-12 10:39:35	ga_ls8c_ard_3-0-0_103083_2018-04-12_final
2018-04-13 09:43:57	ga_ls8c_ard_3-0-0_094083_2018-04-13_final
2018-04-13 11:22:50	ga_ls8c_ard_3-0-0_110083_2018-04-13_final
2018-04-14 10:27:12	ga_ls8c_ard_3-0-0_101083_2018-04-14_final
2018-09-16 10:08:58	ga_ls8c_ard_3-0-0_098083_2018-09-16_final
2018-09-17 09:13:20	ga_ls8c_ard_3-0-0_089083_2018-09-16_final
2018-09-17 10:51:49	ga_ls8c_ard_3-0-0_105082_2018-09-17_final
2018-09-17 10:52:13	ga_ls8c_ard_3-0-0_105083_2018-09-17_final
2018-10-20 09:56:26	ga_ls8c_ard_3-0-0_096082_2018-10-20_final
2018-10-20 09:56:50	ga_ls8c_ard_3-0-0_096083_2018-10-20_final
2018-10-20 11:35:43	ga_ls8c_ard_3-0-0_112083_2018-10-20_final
2018-10-21 10:40:06	ga_ls8c_ard_3-0-0_103083_2018-10-21_final
2018-10-22 09:44:29	ga_ls8c_ard_3-0-0_094083_2018-10-22_final
2018-10-22 11:22:58	ga_ls8c_ard_3-0-0_110082_2018-10-22_final
2018-10-22 11:23:22	ga_ls8c_ard_3-0-0_110083_2018-10-22_final
2018-10-23 08:48:28	ga_ls8c_ard_3-2-1_085082_2018-10-22_final
2018-10-23 10:27:45	ga_ls8c_ard_3-0-0_101083_2018-10-23_final
2018-11-07 09:44:32	ga_ls8c_ard_3-0-0_094083_2018-11-07_final
2018-11-07 11:23:26	ga_ls8c_ard_3-0-0_110083_2018-11-07_final
2018-11-08 08:48:31	ga_ls8c_ard_3-2-1_085082_2018-11-07_final
2018-11-08 10:27:48	ga_ls8c_ard_3-0-0_101083_2018-11-08_final
2018-12-23 09:56:51	ga_ls8c_ard_3-0-0_096083_2018-12-23_final
2018-12-23 11:35:44	ga_ls8c_ard_3-0-0_112083_2018-12-23_final
2018-12-24 10:40:07	ga_ls8c_ard_3-0-0_103083_2018-12-24_final
2018-12-25 09:44:29	ga_ls8c_ard_3-0-0_094083_2018-12-25_final
2018-12-25 11:23:22	ga_ls8c_ard_3-0-0_110083_2018-12-25_final
2018-12-26 10:27:45	ga_ls8c_ard_3-0-0_101083_2018-12-26_final
2019-01-06 10:09:12	ga_ls8c_ard_3-0-0_098083_2019-01-06_final
2019-01-07 09:13:34	ga_ls8c_ard_3-0-0_089083_2019-01-06_final
2019-01-07 10:52:03	ga_ls8c_ard_3-0-0_105082_2019-01-07_final
2019-01-07 10:52:27	ga_ls8c_ard_3-0-0_105083_2019-01-07_final
2023-07-07 09:50:28	ga_ls8c_ard_3-2-1_095083_2023-07-07_final
2023-07-07 11:29:21	ga_ls8c_ard_3-2-1_111083_2023-07-07_final
2023-07-08 10:33:20	ga_ls8c_ard_3-2-1_102082_2023-07-08_final
2023-07-09 09:37:43	ga_ls8c_ard_3-2-1_093082_2023-07-09_final
2023-07-09 09:38:07	ga_ls8c_ard_3-2-1_093083_2023-07-09_final
2023-07-09 11:17:00	ga_ls8c_ard_3-2-1_109083_2023-07-09_final
2023-07-11 11:04:39	ga_ls8c_ard_3-2-1_107083_2023-07-11_final
2023-07-12 10:09:02	ga_ls8c_ard_3-2-1_098083_2023-07-12_final
2023-07-13 09:13:25	ga_ls8c_ard_3-2-1_089083_2023-07-12_final
2023-07-13 10:51:54	ga_ls8c_ard_3-2-1_105082_2023-07-13_final
2023-07-13 10:52:18	ga_ls8c_ard_3-2-1_105083_2023-07-13_final
2023-07-14 09:56:17	ga_ls8c_ard_3-2-1_096082_2023-07-14_final
2023-07-14 09:56:41	ga_ls8c_ard_3-2-1_096083_2023-07-14_final
2023-07-14 11:35:34	ga_ls8c_ard_3-2-1_112083_2023-07-14_final
2023-07-16 11:23:12	ga_ls8c_ard_3-2-1_110083_2023-07-16_final
2023-07-17 08:48:18	ga_ls8c_ard_3-2-1_085082_2023-07-16_final
2023-07-17 10:27:35	ga_ls8c_ard_3-2-1_101083_2023-07-17_final
2023-07-18 11:10:50	ga_ls8c_ard_3-2-1_108083_2023-07-18_final
2023-07-19 10:14:49	ga_ls8c_ard_3-2-1_099082_2023-07-19_final
2023-07-19 10:15:13	ga_ls8c_ard_3-2-1_099083_2023-07-19_final
2023-07-20 09:19:11	ga_ls8c_ard_3-2-1_090082_2023-07-19_final
2023-07-20 09:19:35	ga_ls8c_ard_3-2-1_090083_2023-07-19_final
2023-07-20 10:58:28	ga_ls8c_ard_3-2-1_106083_2023-07-20_final
2023-07-22 09:06:51	ga_ls8c_ard_3-2-1_088082_2023-07-21_final
2023-07-22 09:07:15	ga_ls8c_ard_3-2-1_088083_2023-07-21_final
2023-07-23 11:29:25	ga_ls8c_ard_3-2-1_111083_2023-07-23_final
2023-07-24 10:33:24	ga_ls8c_ard_3-2-1_102082_2023-07-24_final
2023-07-25 09:37:48	ga_ls8c_ard_3-2-1_093082_2023-07-25_final
2023-07-25 09:38:12	ga_ls8c_ard_3-2-1_093083_2023-07-25_final
2023-07-27 09:25:28	ga_ls8c_ard_3-2-1_091082_2023-07-26_final
2023-07-27 09:25:52	ga_ls8c_ard_3-2-1_091083_2023-07-26_final
2023-07-27 11:04:21	ga_ls8c_ard_3-2-1_107082_2023-07-27_final
2023-07-27 11:04:45	ga_ls8c_ard_3-2-1_107083_2023-07-27_final
2023-07-28 10:09:08	ga_ls8c_ard_3-2-1_098083_2023-07-28_final
2023-07-29 10:52:01	ga_ls8c_ard_3-2-1_105082_2023-07-29_final
2023-07-29 10:52:25	ga_ls8c_ard_3-2-1_105083_2023-07-29_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