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
2018-08-17 09:56:01	ga_ls8c_ard_3-0-0_096082_2018-08-17_final
2018-08-17 09:56:25	ga_ls8c_ard_3-0-0_096083_2018-08-17_final
2018-08-17 11:34:54	ga_ls8c_ard_3-0-0_112082_2018-08-17_final
2018-08-17 11:35:18	ga_ls8c_ard_3-0-0_112083_2018-08-17_final
2018-08-18 10:39:17	ga_ls8c_ard_3-0-0_103082_2018-08-18_final
2018-08-18 10:39:41	ga_ls8c_ard_3-0-0_103083_2018-08-18_final
2018-08-19 09:43:41	ga_ls8c_ard_3-0-0_094082_2018-08-19_final
2018-08-19 09:44:04	ga_ls8c_ard_3-0-0_094083_2018-08-19_final
2018-08-19 11:22:34	ga_ls8c_ard_3-0-0_110082_2018-08-19_final
2018-08-19 11:22:58	ga_ls8c_ard_3-0-0_110083_2018-08-19_final
2018-08-20 10:26:57	ga_ls8c_ard_3-0-0_101082_2018-08-20_final
2018-08-20 10:27:21	ga_ls8c_ard_3-0-0_101083_2018-08-20_final
2018-09-02 09:56:08	ga_ls8c_ard_3-0-0_096082_2018-09-02_final
2018-09-02 09:56:32	ga_ls8c_ard_3-0-0_096083_2018-09-02_final
2018-09-02 11:35:01	ga_ls8c_ard_3-0-0_112082_2018-09-02_final
2018-09-02 11:35:25	ga_ls8c_ard_3-0-0_112083_2018-09-02_final
2018-09-03 10:39:24	ga_ls8c_ard_3-0-0_103082_2018-09-03_final
2018-09-03 10:39:48	ga_ls8c_ard_3-0-0_103083_2018-09-03_final
2018-09-04 09:43:47	ga_ls8c_ard_3-0-0_094082_2018-09-04_final
2018-09-04 09:44:11	ga_ls8c_ard_3-0-0_094083_2018-09-04_final
2018-09-04 11:22:40	ga_ls8c_ard_3-0-0_110082_2018-09-04_final
2018-09-04 11:23:04	ga_ls8c_ard_3-0-0_110083_2018-09-04_final
2018-09-05 10:27:03	ga_ls8c_ard_3-1-0_101082_2018-09-05_final
2018-09-05 10:27:27	ga_ls8c_ard_3-0-0_101083_2018-09-05_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
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
2023-03-23 10:52:02	ga_ls8c_ard_3-2-1_105082_2023-03-23_final
2023-03-23 10:52:26	ga_ls8c_ard_3-2-1_105083_2023-03-23_final
2023-03-24 09:56:24	ga_ls8c_ard_3-2-1_096082_2023-03-24_final
2023-03-24 09:56:48	ga_ls8c_ard_3-2-1_096083_2023-03-24_final
2023-03-24 11:35:17	ga_ls8c_ard_3-2-1_112082_2023-03-24_final
2023-03-24 11:35:41	ga_ls8c_ard_3-2-1_112083_2023-03-24_final
2023-03-25 10:39:40	ga_ls8c_ard_3-2-1_103082_2023-03-25_final
2023-03-26 09:44:03	ga_ls8c_ard_3-2-1_094082_2023-03-26_final
2023-03-26 09:44:26	ga_ls8c_ard_3-2-1_094083_2023-03-26_final
2023-03-26 11:22:56	ga_ls8c_ard_3-2-1_110082_2023-03-26_final
2023-03-26 11:23:20	ga_ls8c_ard_3-2-1_110083_2023-03-26_final
2023-03-29 10:14:55	ga_ls8c_ard_3-2-1_099082_2023-03-29_final
2023-03-29 10:15:19	ga_ls8c_ard_3-2-1_099083_2023-03-29_final
2023-03-30 09:19:18	ga_ls8c_ard_3-2-1_090082_2023-03-29_final
2023-03-30 09:19:42	ga_ls8c_ard_3-2-1_090083_2023-03-29_final
2023-03-31 10:02:33	ga_ls8c_ard_3-2-1_097082_2023-03-31_final
2023-03-31 10:02:57	ga_ls8c_ard_3-2-1_097083_2023-03-31_final
2023-03-31 11:41:26	ga_ls8c_ard_3-2-1_113082_2023-03-31_final
2023-03-31 11:41:50	ga_ls8c_ard_3-2-1_113083_2023-03-31_final
2023-04-04 09:37:45	ga_ls8c_ard_3-2-1_093082_2023-04-04_final
2023-04-04 09:38:09	ga_ls8c_ard_3-2-1_093083_2023-04-04_final
2023-04-04 11:16:38	ga_ls8c_ard_3-2-1_109082_2023-04-04_final
2023-04-04 11:17:02	ga_ls8c_ard_3-2-1_109083_2023-04-04_final
2023-04-06 09:25:21	ga_ls8c_ard_3-2-1_091082_2023-04-05_final
2023-04-06 09:25:45	ga_ls8c_ard_3-2-1_091083_2023-04-05_final
2023-04-06 11:04:14	ga_ls8c_ard_3-2-1_107082_2023-04-06_final
2023-04-06 11:04:38	ga_ls8c_ard_3-2-1_107083_2023-04-06_final
2023-04-08 10:51:50	ga_ls8c_ard_3-2-1_105082_2023-04-08_final
2023-04-08 10:52:14	ga_ls8c_ard_3-2-1_105083_2023-04-08_final
2023-04-09 09:56:11	ga_ls8c_ard_3-2-1_096082_2023-04-09_final
2023-04-09 09:56:35	ga_ls8c_ard_3-2-1_096083_2023-04-09_final
2023-04-14 10:14:40	ga_ls8c_ard_3-2-1_099082_2023-04-14_final
2023-04-14 10:15:04	ga_ls8c_ard_3-2-1_099083_2023-04-14_final
2023-04-15 09:19:03	ga_ls8c_ard_3-2-1_090082_2023-04-14_final
2023-04-15 09:19:27	ga_ls8c_ard_3-2-1_090083_2023-04-14_final
2023-04-15 10:57:56	ga_ls8c_ard_3-2-1_106082_2023-04-15_final
2023-04-15 10:58:20	ga_ls8c_ard_3-2-1_106083_2023-04-15_final
2023-04-20 11:16:25	ga_ls8c_ard_3-2-1_109082_2023-04-20_final
2023-04-20 11:16:49	ga_ls8c_ard_3-2-1_109083_2023-04-20_final
2023-04-21 08:41:55	ga_ls8c_ard_3-2-1_084082_2023-04-20_final
2023-04-21 10:20:48	ga_ls8c_ard_3-2-1_100082_2023-04-21_final
2023-04-21 10:21:12	ga_ls8c_ard_3-2-1_100083_2023-04-21_final
2023-04-24 09:12:50	ga_ls8c_ard_3-2-1_089082_2023-04-23_final
2023-04-24 09:13:14	ga_ls8c_ard_3-2-1_089083_2023-04-23_final
2023-04-24 10:51:43	ga_ls8c_ard_3-2-1_105082_2023-04-24_final
2023-04-24 10:52:07	ga_ls8c_ard_3-2-1_105083_2023-04-24_final
2023-04-25 09:56:05	ga_ls8c_ard_3-2-1_096082_2023-04-25_final
2023-04-25 09:56:29	ga_ls8c_ard_3-2-1_096083_2023-04-25_final
2023-04-27 11:22:36	ga_ls8c_ard_3-2-1_110082_2023-04-27_final
2023-04-27 11:23:00	ga_ls8c_ard_3-2-1_110083_2023-04-27_final
2023-04-28 08:48:06	ga_ls8c_ard_3-2-1_085082_2023-04-27_final
2023-05-01 10:57:51	ga_ls8c_ard_3-2-1_106082_2023-05-01_final
2023-05-01 10:58:15	ga_ls8c_ard_3-2-1_106083_2023-05-01_final
2023-05-02 10:02:13	ga_ls8c_ard_3-2-1_097082_2023-05-02_final
2023-05-02 10:02:37	ga_ls8c_ard_3-2-1_097083_2023-05-02_final
2023-05-02 11:41:06	ga_ls8c_ard_3-2-1_113082_2023-05-02_final
2023-05-02 11:41:30	ga_ls8c_ard_3-2-1_113083_2023-05-02_final
2023-05-08 09:25:03	ga_ls8c_ard_3-2-1_091082_2023-05-07_final
2023-05-08 09:25:27	ga_ls8c_ard_3-2-1_091083_2023-05-07_final
2023-07-25 11:17:05	ga_ls8c_ard_3-2-1_109083_2023-07-25_final
2023-07-26 08:42:11	ga_ls8c_ard_3-2-1_084082_2023-07-25_final
2023-07-26 10:21:04	ga_ls8c_ard_3-2-1_100082_2023-07-26_final
2023-07-26 10:21:28	ga_ls8c_ard_3-2-1_100083_2023-07-26_final
2023-07-27 09:25:28	ga_ls8c_ard_3-2-1_091082_2023-07-26_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