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
2015-04-30 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
2015-05-14 09:49:48	ga_ls8c_ard_3-0-0_095083_2015-05-14_final
2015-05-14 11:28:41	ga_ls8c_ard_3-0-0_111083_2015-05-14_final
2015-05-15 10:32:39	ga_ls8c_ard_3-0-0_102082_2015-05-15_final
2015-05-15 10:33:03	ga_ls8c_ard_3-0-0_102083_2015-05-15_final
2015-05-16 09:37:03	ga_ls8c_ard_3-0-0_093082_2015-05-16_final
2015-05-16 09:37:27	ga_ls8c_ard_3-0-0_093083_2015-05-16_final
2015-05-16 11:15:56	ga_ls8c_ard_3-0-0_109082_2015-05-16_final
2015-05-16 11:16:20	ga_ls8c_ard_3-0-0_109083_2015-05-16_final
2015-05-17 10:20:19	ga_ls8c_ard_3-1-0_100082_2015-05-17_final
2015-05-17 10:20:43	ga_ls8c_ard_3-0-0_100083_2015-05-17_final
2015-07-26 09:43:49	ga_ls8c_ard_3-0-0_094082_2015-07-26_final
2015-07-26 09:44:13	ga_ls8c_ard_3-0-0_094083_2015-07-26_final
2015-07-26 11:22:42	ga_ls8c_ard_3-0-0_110082_2015-07-26_final
2015-07-26 11:23:06	ga_ls8c_ard_3-0-0_110083_2015-07-26_final
2015-07-27 10:27:05	ga_ls8c_ard_3-0-0_101082_2015-07-27_final
2015-07-27 10:27:29	ga_ls8c_ard_3-0-0_101083_2015-07-27_final
2015-08-02 09:50:01	ga_ls8c_ard_3-0-0_095082_2015-08-02_final
2015-08-02 09:50:25	ga_ls8c_ard_3-0-0_095083_2015-08-02_final
2015-08-02 11:28:54	ga_ls8c_ard_3-0-0_111082_2015-08-02_final
2015-08-02 11:29:18	ga_ls8c_ard_3-0-0_111083_2015-08-02_final
2015-08-03 10:33:17	ga_ls8c_ard_3-0-0_102082_2015-08-03_final
2015-08-03 10:33:41	ga_ls8c_ard_3-0-0_102083_2015-08-03_final
2015-08-04 09:37:39	ga_ls8c_ard_3-0-0_093082_2015-08-04_final
2015-08-04 09:38:03	ga_ls8c_ard_3-0-0_093083_2015-08-04_final
2015-08-04 11:16:32	ga_ls8c_ard_3-0-0_109082_2015-08-04_final
2015-08-04 11:16:56	ga_ls8c_ard_3-0-0_109083_2015-08-04_final
2015-08-05 10:20:55	ga_ls8c_ard_3-0-0_100082_2015-08-05_final
2015-08-05 10:21:19	ga_ls8c_ard_3-0-0_100083_2015-08-05_final
2018-09-16 10:08:34	ga_ls8c_ard_3-0-0_098082_2018-09-16_final
2018-09-16 10:08:58	ga_ls8c_ard_3-0-0_098083_2018-09-16_final
2018-09-17 09:12:56	ga_ls8c_ard_3-0-0_089082_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 09:56:20	ga_ls8c_ard_3-0-0_096082_2018-10-04_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 11:22:52	ga_ls8c_ard_3-0-0_110082_2018-10-06_final
2018-10-06 11:23:16	ga_ls8c_ard_3-0-0_110083_2018-10-06_final
2018-10-07 10:27:16	ga_ls8c_ard_3-0-0_101082_2018-10-07_final
2018-10-07 10:27:40	ga_ls8c_ard_3-0-0_101083_2018-10-07_final
2018-12-23 09:56:27	ga_ls8c_ard_3-0-0_096082_2018-12-23_final
2018-12-23 09:56:51	ga_ls8c_ard_3-0-0_096083_2018-12-23_final
2018-12-23 11:35:20	ga_ls8c_ard_3-0-0_112082_2018-12-23_final
2018-12-23 11:35:44	ga_ls8c_ard_3-0-0_112083_2018-12-23_final
2018-12-24 10:39:43	ga_ls8c_ard_3-0-0_103082_2018-12-24_final
2018-12-24 10:40:07	ga_ls8c_ard_3-0-0_103083_2018-12-24_final
2018-12-25 09:44:05	ga_ls8c_ard_3-0-0_094082_2018-12-25_final
2018-12-25 09:44:29	ga_ls8c_ard_3-0-0_094083_2018-12-25_final
2018-12-25 11:22:58	ga_ls8c_ard_3-0-0_110082_2018-12-25_final
2018-12-25 11:23:22	ga_ls8c_ard_3-0-0_110083_2018-12-25_final
2018-12-26 08:48:28	ga_ls8c_ard_3-2-1_085082_2018-12-25_final
2018-12-26 10:27:21	ga_ls8c_ard_3-0-0_101082_2018-12-26_final
2018-12-26 10:27:45	ga_ls8c_ard_3-0-0_101083_2018-12-26_final
2019-01-06 10:08:48	ga_ls8c_ard_3-0-0_098082_2019-01-06_final
2019-01-06 10:09:12	ga_ls8c_ard_3-0-0_098083_2019-01-06_final
2019-01-07 09:13:10	ga_ls8c_ard_3-0-0_089082_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
2023-03-01 11:29:20	ga_ls8c_ard_3-2-1_111082_2023-03-01_final
2023-03-01 11:29:44	ga_ls8c_ard_3-2-1_111083_2023-03-01_final
2023-03-02 10:33:42	ga_ls8c_ard_3-2-1_102082_2023-03-02_final
2023-03-03 11:16:58	ga_ls8c_ard_3-2-1_109082_2023-03-03_final
2023-03-03 11:17:22	ga_ls8c_ard_3-2-1_109083_2023-03-03_final
2023-03-04 08:42:27	ga_ls8c_ard_3-2-1_084082_2023-03-03_final
2023-03-04 10:21:44	ga_ls8c_ard_3-2-1_100083_2023-03-04_final
2023-03-05 09:26:06	ga_ls8c_ard_3-2-1_091083_2023-03-04_final
2023-08-14 10:52:06	ga_ls8c_ard_3-2-1_105082_2023-08-14_final
2023-08-14 10:52:30	ga_ls8c_ard_3-2-1_105083_2023-08-14_final
2023-08-15 09:56:29	ga_ls8c_ard_3-2-1_096082_2023-08-15_final
2023-08-15 09:56:53	ga_ls8c_ard_3-2-1_096083_2023-08-15_final
2023-08-15 11:35:22	ga_ls8c_ard_3-2-1_112082_2023-08-15_final
2023-08-15 11:35:46	ga_ls8c_ard_3-2-1_112083_2023-08-15_final
2023-08-16 10:39:46	ga_ls8c_ard_3-2-1_103082_2023-08-16_final
2023-08-17 09:44:09	ga_ls8c_ard_3-2-1_094082_2023-08-17_final
2023-08-17 09:44:33	ga_ls8c_ard_3-2-1_094083_2023-08-17_final
2023-08-17 11:23:02	ga_ls8c_ard_3-2-1_110082_2023-08-17_final
2023-08-17 11:23:26	ga_ls8c_ard_3-2-1_110083_2023-08-17_final
2023-08-24 11:29:40	ga_ls8c_ard_3-2-1_111083_2023-08-24_final
2023-08-25 10:33:39	ga_ls8c_ard_3-2-1_102082_2023-08-25_final
2023-08-26 09:38:02	ga_ls8c_ard_3-2-1_093082_2023-08-26_final
2023-08-26 09:38:26	ga_ls8c_ard_3-2-1_093083_2023-08-26_final
2023-08-26 11:16:55	ga_ls8c_ard_3-2-1_109082_2023-08-26_final
2023-08-26 11:17:19	ga_ls8c_ard_3-2-1_109083_2023-08-26_final
2023-08-28 09:26:04	ga_ls8c_ard_3-2-1_091083_2023-08-27_final
2023-08-28 11:04:33	ga_ls8c_ard_3-2-1_107082_2023-08-28_final
2023-08-28 11:04:57	ga_ls8c_ard_3-2-1_107083_2023-08-28_final
2023-08-31 09:56:34	ga_ls8c_ard_3-2-1_096082_2023-08-31_final
2023-08-31 09:56:58	ga_ls8c_ard_3-2-1_096083_2023-08-31_final
2023-08-31 11:35:27	ga_ls8c_ard_3-2-1_112082_2023-08-31_final
2023-08-31 11:35:51	ga_ls8c_ard_3-2-1_112083_2023-08-31_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