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
2015-04-21 09:43:59	ga_ls8c_ard_3-0-0_094083_2015-04-21_final
2015-04-21 11:22:52	ga_ls8c_ard_3-0-0_110083_2015-04-21_final
2015-04-22 10:27:14	ga_ls8c_ard_3-0-0_101083_2015-04-22_final
2015-04-23 09:31:36	ga_ls8c_ard_3-0-0_092083_2015-04-23_final
2015-04-23 11:10:29	ga_ls8c_ard_3-0-0_108083_2015-04-23_final
2015-04-24 10:14:51	ga_ls8c_ard_3-0-0_099083_2015-04-24_final
2015-04-28 09:50:04	ga_ls8c_ard_3-0-0_095083_2015-04-28_final
2015-04-28 11:28:57	ga_ls8c_ard_3-0-0_111083_2015-04-28_final
2015-04-29 10:33:19	ga_ls8c_ard_3-0-0_102083_2015-04-29_final
2015-04-30 09:37:41	ga_ls8c_ard_3-0-0_093083_2015-04-30_final
2015-04-30 11:16:34	ga_ls8c_ard_3-0-0_109083_2015-04-30_final
2015-05-01 10:20:55	ga_ls8c_ard_3-0-0_100083_2015-05-01_final
2015-06-15 09:49:41	ga_ls8c_ard_3-0-0_095082_2015-06-15_final
2015-06-15 09:50:05	ga_ls8c_ard_3-0-0_095083_2015-06-15_final
2015-06-15 11:28:58	ga_ls8c_ard_3-0-0_111083_2015-06-15_final
2015-06-16 10:33:21	ga_ls8c_ard_3-0-0_102083_2015-06-16_final
2015-06-17 09:37:20	ga_ls8c_ard_3-0-0_093082_2015-06-17_final
2015-06-17 09:37:44	ga_ls8c_ard_3-0-0_093083_2015-06-17_final
2015-06-17 11:16:37	ga_ls8c_ard_3-0-0_109083_2015-06-17_final
2015-06-18 10:21:00	ga_ls8c_ard_3-0-0_100083_2015-06-18_final
2015-08-20 09:37:47	ga_ls8c_ard_3-0-0_093082_2015-08-20_final
2015-08-20 09:38:11	ga_ls8c_ard_3-0-0_093083_2015-08-20_final
2015-08-20 11:17:04	ga_ls8c_ard_3-0-0_109083_2015-08-20_final
2015-08-21 10:21:27	ga_ls8c_ard_3-0-0_100083_2015-08-21_final
2016-12-17 09:57:14	ga_ls8c_ard_3-0-0_096083_2016-12-17_final
2016-12-17 11:36:07	ga_ls8c_ard_3-0-0_112083_2016-12-17_final
2016-12-18 10:40:29	ga_ls8c_ard_3-0-0_103083_2016-12-18_final
2016-12-19 09:44:52	ga_ls8c_ard_3-0-0_094083_2016-12-19_final
2016-12-19 11:23:45	ga_ls8c_ard_3-0-0_110083_2016-12-19_final
2016-12-20 10:28:07	ga_ls8c_ard_3-0-0_101083_2016-12-20_final
2017-03-07 09:56:47	ga_ls8c_ard_3-0-0_096083_2017-03-07_final
2017-03-07 11:35:40	ga_ls8c_ard_3-0-0_112083_2017-03-07_final
2017-03-08 10:40:02	ga_ls8c_ard_3-0-0_103083_2017-03-08_final
2017-03-09 09:44:24	ga_ls8c_ard_3-0-0_094083_2017-03-09_final
2017-03-09 11:23:17	ga_ls8c_ard_3-0-0_110083_2017-03-09_final
2017-03-10 10:27:39	ga_ls8c_ard_3-0-0_101083_2017-03-10_final
2018-06-07 09:49:35	ga_ls8c_ard_3-0-0_095083_2018-06-07_final
2018-06-07 11:28:28	ga_ls8c_ard_3-0-0_111083_2018-06-07_final
2018-06-08 10:32:51	ga_ls8c_ard_3-0-0_102083_2018-06-08_final
2018-06-09 09:37:15	ga_ls8c_ard_3-0-0_093083_2018-06-09_final
2018-06-09 11:16:08	ga_ls8c_ard_3-0-0_109083_2018-06-09_final
2018-06-10 10:20:07	ga_ls8c_ard_3-0-0_100082_2018-06-10_final
2018-06-10 10:20:31	ga_ls8c_ard_3-0-0_100083_2018-06-10_final
2018-06-23 09:49:22	ga_ls8c_ard_3-0-0_095082_2018-06-23_final
2018-06-23 09:49:46	ga_ls8c_ard_3-0-0_095083_2018-06-23_final
2018-06-23 11:28:39	ga_ls8c_ard_3-0-0_111083_2018-06-23_final
2018-06-24 10:33:03	ga_ls8c_ard_3-0-0_102083_2018-06-24_final
2018-06-25 09:37:02	ga_ls8c_ard_3-0-0_093082_2018-06-25_final
2018-06-25 09:37:26	ga_ls8c_ard_3-0-0_093083_2018-06-25_final
2018-06-25 11:15:55	ga_ls8c_ard_3-0-0_109082_2018-06-25_final
2018-06-25 11:16:19	ga_ls8c_ard_3-0-0_109083_2018-06-25_final
2018-06-26 10:20:42	ga_ls8c_ard_3-0-0_100083_2018-06-26_final
2018-07-09 09:49:55	ga_ls8c_ard_3-0-0_095083_2018-07-09_final
2018-07-09 11:28:24	ga_ls8c_ard_3-0-0_111082_2018-07-09_final
2018-07-09 11:28:48	ga_ls8c_ard_3-0-0_111083_2018-07-09_final
2018-07-10 10:32:47	ga_ls8c_ard_3-0-0_102082_2018-07-10_final
2018-07-10 10:33:11	ga_ls8c_ard_3-0-0_102083_2018-07-10_final
2018-07-11 09:37:34	ga_ls8c_ard_3-0-0_093083_2018-07-11_final
2018-07-11 11:16:03	ga_ls8c_ard_3-0-0_109082_2018-07-11_final
2018-07-11 11:16:27	ga_ls8c_ard_3-0-0_109083_2018-07-11_final
2018-07-12 10:20:50	ga_ls8c_ard_3-0-0_100083_2018-07-12_final
2018-08-10 09:49:47	ga_ls8c_ard_3-0-0_095082_2018-08-10_final
2018-08-10 09:50:11	ga_ls8c_ard_3-0-0_095083_2018-08-10_final
2018-08-10 11:29:04	ga_ls8c_ard_3-0-0_111083_2018-08-10_final
2018-08-11 10:33:03	ga_ls8c_ard_3-0-0_102082_2018-08-11_final
2018-08-11 10:33:27	ga_ls8c_ard_3-0-0_102083_2018-08-11_final
2018-08-12 09:37:26	ga_ls8c_ard_3-0-0_093082_2018-08-12_final
2018-08-12 09:37:50	ga_ls8c_ard_3-0-0_093083_2018-08-12_final
2018-08-12 11:16:19	ga_ls8c_ard_3-0-0_109082_2018-08-12_final
2018-08-12 11:16:43	ga_ls8c_ard_3-0-0_109083_2018-08-12_final
2018-08-13 10:20:42	ga_ls8c_ard_3-0-0_100082_2018-08-13_final
2018-08-13 10:21:06	ga_ls8c_ard_3-0-0_100083_2018-08-13_final
2018-08-26 09:50:18	ga_ls8c_ard_3-0-0_095083_2018-08-26_final
2018-08-26 11:29:12	ga_ls8c_ard_3-0-0_111083_2018-08-26_final
2018-08-27 10:33:35	ga_ls8c_ard_3-0-0_102083_2018-08-27_final
2018-08-28 09:37:58	ga_ls8c_ard_3-0-0_093083_2018-08-28_final
2018-08-28 11:16:51	ga_ls8c_ard_3-0-0_109083_2018-08-28_final
2018-08-29 10:21:14	ga_ls8c_ard_3-0-0_100083_2018-08-29_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
2018-10-04 09:56:44	ga_ls8c_ard_3-0-0_096083_2018-10-04_final
2018-10-04 11:35:13	ga_ls8c_ard_3-0-0_112082_2018-10-04_final
2018-10-04 11:35:37	ga_ls8c_ard_3-0-0_112083_2018-10-04_final
2018-10-05 10:39:36	ga_ls8c_ard_3-0-0_103082_2018-10-05_final
2018-10-05 10:40:00	ga_ls8c_ard_3-0-0_103083_2018-10-05_final
2018-10-06 09:43:59	ga_ls8c_ard_3-0-0_094082_2018-10-06_final
2018-10-06 09:44:23	ga_ls8c_ard_3-0-0_094083_2018-10-06_final
2018-10-06 11:23:16	ga_ls8c_ard_3-0-0_110083_2018-10-06_final
2018-10-07 10:27:40	ga_ls8c_ard_3-0-0_101083_2018-10-07_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
2023-09-13 09:26:07	ga_ls8c_ard_3-2-1_091083_2023-09-12_final
2023-09-13 11:05:00	ga_ls8c_ard_3-2-1_107083_2023-09-13_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