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
2018-02-03 09:26:20	ga_ls8c_ard_3-0-0_091084_2018-02-02_final
2018-02-03 11:05:13	ga_ls8c_ard_3-0-0_107084_2018-02-03_final
2018-02-19 09:26:15	ga_ls8c_ard_3-0-0_091084_2018-02-18_final
2018-02-19 11:05:08	ga_ls8c_ard_3-0-0_107084_2018-02-19_final
2018-03-07 09:26:07	ga_ls8c_ard_3-0-0_091084_2018-03-06_final
2018-03-07 11:05:00	ga_ls8c_ard_3-0-0_107084_2018-03-07_final
2018-04-08 09:25:51	ga_ls8c_ard_3-0-0_091084_2018-04-07_final
2018-04-08 11:04:44	ga_ls8c_ard_3-0-0_107084_2018-04-08_final
2018-09-16 10:08:58	ga_ls8c_ard_3-0-0_098083_2018-09-16_final
2018-09-16 10:09:21	ga_ls8c_ard_3-0-0_098084_2018-09-16_final
2018-09-17 09:13:44	ga_ls8c_ard_3-0-0_089084_2018-09-16_final
2018-09-17 10:52:13	ga_ls8c_ard_3-0-0_105083_2018-09-17_final
2018-10-04 09:57:08	ga_ls8c_ard_3-0-0_096084_2018-10-04_final
2018-10-04 11:36:01	ga_ls8c_ard_3-0-0_112084_2018-10-04_final
2018-10-06 09:44:47	ga_ls8c_ard_3-0-0_094084_2018-10-06_final
2018-10-06 11:23:16	ga_ls8c_ard_3-0-0_110083_2018-10-06_final
2018-10-06 11:23:40	ga_ls8c_ard_3-0-0_110084_2018-10-06_final
2018-10-07 10:28:03	ga_ls8c_ard_3-0-0_101084_2018-10-07_final
2018-12-23 09:57:15	ga_ls8c_ard_3-0-0_096084_2018-12-23_final
2018-12-23 11:36:08	ga_ls8c_ard_3-0-0_112084_2018-12-23_final
2018-12-25 09:44:53	ga_ls8c_ard_3-0-0_094084_2018-12-25_final
2018-12-25 11:23:46	ga_ls8c_ard_3-0-0_110084_2018-12-25_final
2018-12-26 10:28:09	ga_ls8c_ard_3-0-0_101084_2018-12-26_final
2019-01-06 10:09:36	ga_ls8c_ard_3-0-0_098084_2019-01-06_final
2019-01-07 09:13:58	ga_ls8c_ard_3-0-0_089084_2019-01-06_final
2019-07-05 09:44:32	ga_ls8c_ard_3-1-0_094083_2019-07-05_final
2019-07-05 09:44:56	ga_ls8c_ard_3-1-0_094084_2019-07-05_final
2019-07-05 11:23:25	ga_ls8c_ard_3-1-0_110083_2019-07-05_final
2019-07-05 11:23:49	ga_ls8c_ard_3-1-0_110084_2019-07-05_final
2019-07-06 10:27:48	ga_ls8c_ard_3-1-0_101083_2019-07-06_final
2019-07-06 10:28:12	ga_ls8c_ard_3-1-0_101084_2019-07-06_final
2019-07-07 09:32:34	ga_ls8c_ard_3-1-0_092084_2019-07-07_final
2019-07-07 11:11:28	ga_ls8c_ard_3-1-0_108084_2019-07-07_final
2019-07-17 10:09:41	ga_ls8c_ard_3-1-0_098084_2019-07-17_final
2019-07-18 09:13:40	ga_ls8c_ard_3-1-0_089083_2019-07-17_final
2019-07-18 09:14:04	ga_ls8c_ard_3-1-0_089084_2019-07-17_final
2019-07-18 10:52:33	ga_ls8c_ard_3-1-0_105083_2019-07-18_final
2019-07-23 09:32:14	ga_ls8c_ard_3-1-0_092083_2019-07-23_final
2019-07-23 09:32:38	ga_ls8c_ard_3-1-0_092084_2019-07-23_final
2019-07-23 11:11:07	ga_ls8c_ard_3-1-0_108083_2019-07-23_final
2019-07-23 11:11:31	ga_ls8c_ard_3-1-0_108084_2019-07-23_final
2019-07-24 10:15:30	ga_ls8c_ard_3-1-0_099083_2019-07-24_final
2019-07-24 10:15:54	ga_ls8c_ard_3-1-0_099084_2019-07-24_final
2019-07-25 09:20:18	ga_ls8c_ard_3-1-0_090084_2019-07-24_final
2019-07-25 10:58:47	ga_ls8c_ard_3-1-0_106083_2019-07-25_final
2019-07-25 10:59:11	ga_ls8c_ard_3-1-0_106084_2019-07-25_final
2019-07-26 10:03:34	ga_ls8c_ard_3-1-0_097084_2019-07-26_final
2019-07-26 11:42:27	ga_ls8c_ard_3-1-0_113084_2019-07-26_final
2019-07-27 09:07:33	ga_ls8c_ard_3-1-0_088083_2019-07-26_final
2019-07-27 09:07:57	ga_ls8c_ard_3-1-0_088084_2019-07-26_final
2019-08-06 09:45:06	ga_ls8c_ard_3-1-0_094084_2019-08-06_final
2019-08-06 11:23:35	ga_ls8c_ard_3-1-0_110083_2019-08-06_final
2019-08-06 11:23:59	ga_ls8c_ard_3-1-0_110084_2019-08-06_final
2019-08-07 10:27:58	ga_ls8c_ard_3-1-0_101083_2019-08-07_final
2019-08-07 10:28:22	ga_ls8c_ard_3-1-0_101084_2019-08-07_final
2019-08-08 09:32:45	ga_ls8c_ard_3-1-0_092084_2019-08-08_final
2019-08-08 11:11:38	ga_ls8c_ard_3-1-0_108084_2019-08-08_final
2019-08-17 09:26:37	ga_ls8c_ard_3-1-0_091084_2019-08-16_final
2019-08-17 11:05:06	ga_ls8c_ard_3-1-0_107083_2019-08-17_final
2019-08-17 11:05:30	ga_ls8c_ard_3-1-0_107084_2019-08-17_final
2019-08-18 10:09:53	ga_ls8c_ard_3-1-0_098084_2019-08-18_final
2019-08-19 09:14:16	ga_ls8c_ard_3-1-0_089084_2019-08-18_final
2019-08-20 09:57:32	ga_ls8c_ard_3-1-0_096084_2019-08-20_final
2019-08-20 11:36:25	ga_ls8c_ard_3-1-0_112084_2019-08-20_final
2019-08-22 09:45:11	ga_ls8c_ard_3-1-0_094084_2019-08-22_final
2019-08-22 11:24:04	ga_ls8c_ard_3-1-0_110084_2019-08-22_final
2019-08-23 10:28:03	ga_ls8c_ard_3-1-0_101083_2019-08-23_final
2019-08-23 10:28:27	ga_ls8c_ard_3-1-0_101084_2019-08-23_final
2019-08-24 09:32:49	ga_ls8c_ard_3-1-0_092084_2019-08-24_final
2019-08-24 11:11:42	ga_ls8c_ard_3-1-0_108084_2019-08-24_final
2019-09-03 10:09:56	ga_ls8c_ard_3-1-0_098084_2019-09-03_final
2019-09-04 09:14:19	ga_ls8c_ard_3-1-0_089084_2019-09-03_final
2019-09-04 10:52:48	ga_ls8c_ard_3-1-0_105083_2019-09-04_final
2019-10-04 09:26:50	ga_ls8c_ard_3-1-0_091084_2019-10-03_final
2019-10-04 11:05:19	ga_ls8c_ard_3-1-0_107083_2019-10-04_final
2019-10-04 11:05:43	ga_ls8c_ard_3-1-0_107084_2019-10-04_final
2019-10-05 10:10:06	ga_ls8c_ard_3-1-0_098084_2019-10-05_final
2019-10-06 09:14:05	ga_ls8c_ard_3-1-0_089083_2019-10-05_final
2019-10-06 09:14:29	ga_ls8c_ard_3-1-0_089084_2019-10-05_final
2019-10-07 09:57:45	ga_ls8c_ard_3-1-0_096084_2019-10-07_final
2019-10-07 11:36:38	ga_ls8c_ard_3-1-0_112084_2019-10-07_final
2019-10-21 10:09:44	ga_ls8c_ard_3-1-0_098083_2019-10-21_final
2019-10-21 10:10:08	ga_ls8c_ard_3-1-0_098084_2019-10-21_final
2019-10-22 09:14:30	ga_ls8c_ard_3-1-0_089084_2019-10-21_final
2019-10-22 10:52:59	ga_ls8c_ard_3-1-0_105083_2019-10-22_final
2023-07-07 09:50:52	ga_ls8c_ard_3-2-1_095084_2023-07-07_final
2023-07-07 11:29:21	ga_ls8c_ard_3-2-1_111083_2023-07-07_final
2023-07-07 11:29:45	ga_ls8c_ard_3-2-1_111084_2023-07-07_final
2023-07-09 11:17:24	ga_ls8c_ard_3-2-1_109084_2023-07-09_final
2023-07-10 10:21:47	ga_ls8c_ard_3-2-1_100084_2023-07-10_final
2023-07-11 09:26:10	ga_ls8c_ard_3-2-1_091084_2023-07-10_final
2023-07-12 10:09:26	ga_ls8c_ard_3-2-1_098084_2023-07-12_final
2023-07-14 11:35:58	ga_ls8c_ard_3-2-1_112084_2023-07-14_final
2023-07-16 09:44:19	ga_ls8c_ard_3-2-1_094083_2023-07-16_final
2023-07-16 09:44:43	ga_ls8c_ard_3-2-1_094084_2023-07-16_final
2023-07-16 11:23:12	ga_ls8c_ard_3-2-1_110083_2023-07-16_final
2023-07-16 11:23:36	ga_ls8c_ard_3-2-1_110084_2023-07-16_final
2023-07-17 10:27:35	ga_ls8c_ard_3-2-1_101083_2023-07-17_final
2023-07-20 09:19:35	ga_ls8c_ard_3-2-1_090083_2023-07-19_final
2023-07-20 09:19:59	ga_ls8c_ard_3-2-1_090084_2023-07-19_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