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
2018-06-14 09:55:51	ga_ls8c_ard_3-0-0_096083_2018-06-14_final
2018-06-14 09:56:15	ga_ls8c_ard_3-0-0_096084_2018-06-14_final
2018-06-14 11:34:44	ga_ls8c_ard_3-0-0_112083_2018-06-14_final
2018-06-14 11:35:08	ga_ls8c_ard_3-0-0_112084_2018-06-14_final
2018-06-15 10:39:07	ga_ls8c_ard_3-0-0_103083_2018-06-15_final
2018-06-16 09:43:31	ga_ls8c_ard_3-0-0_094083_2018-06-16_final
2018-06-16 09:43:55	ga_ls8c_ard_3-0-0_094084_2018-06-16_final
2018-06-16 11:22:24	ga_ls8c_ard_3-0-0_110083_2018-06-16_final
2018-06-16 11:22:48	ga_ls8c_ard_3-0-0_110084_2018-06-16_final
2018-06-17 10:26:47	ga_ls8c_ard_3-0-0_101083_2018-06-17_final
2018-06-17 10:27:11	ga_ls8c_ard_3-0-0_101084_2018-06-17_final
2018-06-30 09:56:01	ga_ls8c_ard_3-0-0_096083_2018-06-30_final
2018-06-30 09:56:25	ga_ls8c_ard_3-0-0_096084_2018-06-30_final
2018-06-30 11:34:54	ga_ls8c_ard_3-0-0_112083_2018-06-30_final
2018-06-30 11:35:18	ga_ls8c_ard_3-0-0_112084_2018-06-30_final
2018-07-01 10:39:17	ga_ls8c_ard_3-0-0_103083_2018-07-01_final
2018-07-02 09:43:41	ga_ls8c_ard_3-0-0_094083_2018-07-02_final
2018-07-02 09:44:05	ga_ls8c_ard_3-1-0_094084_2018-07-02_final
2018-07-02 11:22:34	ga_ls8c_ard_3-0-0_110083_2018-07-02_final
2018-07-02 11:22:58	ga_ls8c_ard_3-0-0_110084_2018-07-02_final
2018-07-03 10:26:57	ga_ls8c_ard_3-0-0_101083_2018-07-03_final
2018-07-03 10:27:21	ga_ls8c_ard_3-0-0_101084_2018-07-03_final
2018-08-17 09:56:25	ga_ls8c_ard_3-0-0_096083_2018-08-17_final
2018-08-17 09:56:49	ga_ls8c_ard_3-0-0_096084_2018-08-17_final
2018-08-18 10:39:41	ga_ls8c_ard_3-0-0_103083_2018-08-18_final
2018-08-19 09:44:04	ga_ls8c_ard_3-0-0_094083_2018-08-19_final
2018-08-19 09:44:28	ga_ls8c_ard_3-0-0_094084_2018-08-19_final
2018-08-19 11:22:58	ga_ls8c_ard_3-0-0_110083_2018-08-19_final
2018-08-19 11:23:22	ga_ls8c_ard_3-0-0_110084_2018-08-19_final
2018-08-20 10:27:21	ga_ls8c_ard_3-0-0_101083_2018-08-20_final
2018-08-20 10:27:45	ga_ls8c_ard_3-0-0_101084_2018-08-20_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 09:13:20	ga_ls8c_ard_3-0-0_089083_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
2018-10-20 09:56:50	ga_ls8c_ard_3-0-0_096083_2018-10-20_final
2018-10-20 09:57:14	ga_ls8c_ard_3-0-0_096084_2018-10-20_final
2018-10-20 11:36:07	ga_ls8c_ard_3-0-0_112084_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 09:44:53	ga_ls8c_ard_3-0-0_094084_2018-10-22_final
2018-10-22 11:23:46	ga_ls8c_ard_3-0-0_110084_2018-10-22_final
2018-10-23 10:27:45	ga_ls8c_ard_3-0-0_101083_2018-10-23_final
2018-10-23 10:28:09	ga_ls8c_ard_3-0-0_101084_2018-10-23_final
2018-11-07 09:44:56	ga_ls8c_ard_3-0-0_094084_2018-11-07_final
2018-11-07 11:23:26	ga_ls8c_ard_3-0-0_110083_2018-11-07_final
2018-11-07 11:23:49	ga_ls8c_ard_3-0-0_110084_2018-11-07_final
2018-11-08 10:27:48	ga_ls8c_ard_3-0-0_101083_2018-11-08_final
2018-11-08 10:28:12	ga_ls8c_ard_3-0-0_101084_2018-11-08_final
2018-12-23 09:57:15	ga_ls8c_ard_3-0-0_096084_2018-12-23_final
2018-12-23 11:35:44	ga_ls8c_ard_3-0-0_112083_2018-12-23_final
2018-12-23 11:36:08	ga_ls8c_ard_3-0-0_112084_2018-12-23_final
2018-12-25 09:44:29	ga_ls8c_ard_3-0-0_094083_2018-12-25_final
2018-12-25 09:44:53	ga_ls8c_ard_3-0-0_094084_2018-12-25_final
2018-12-25 11:23:22	ga_ls8c_ard_3-0-0_110083_2018-12-25_final
2018-12-25 11:23:46	ga_ls8c_ard_3-0-0_110084_2018-12-25_final
2018-12-26 10:27:45	ga_ls8c_ard_3-0-0_101083_2018-12-26_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
2023-08-21 09:19:52	ga_ls8c_ard_3-2-1_090083_2023-08-20_final
2023-08-21 09:20:16	ga_ls8c_ard_3-2-1_090084_2023-08-20_final
2023-08-21 10:58:45	ga_ls8c_ard_3-2-1_106083_2023-08-21_final
2023-08-24 09:50:47	ga_ls8c_ard_3-2-1_095083_2023-08-24_final
2023-08-24 09:51:11	ga_ls8c_ard_3-2-1_095084_2023-08-24_final
2023-08-24 11:30:04	ga_ls8c_ard_3-2-1_111084_2023-08-24_final
2023-08-26 09:38:26	ga_ls8c_ard_3-2-1_093083_2023-08-26_final
2023-08-26 09:38:50	ga_ls8c_ard_3-2-1_093084_2023-08-26_final
2023-08-26 11:17:19	ga_ls8c_ard_3-2-1_109083_2023-08-26_final
2023-08-26 11:17:43	ga_ls8c_ard_3-2-1_109084_2023-08-26_final
2023-08-27 10:21:42	ga_ls8c_ard_3-2-1_100083_2023-08-27_final
2023-08-27 10:22:06	ga_ls8c_ard_3-2-1_100084_2023-08-27_final
2023-08-28 09:26:28	ga_ls8c_ard_3-2-1_091084_2023-08-27_final
2023-08-28 11:04:57	ga_ls8c_ard_3-2-1_107083_2023-08-28_final
2023-08-28 11:05:21	ga_ls8c_ard_3-2-1_107084_2023-08-28_final
2023-08-29 10:09:44	ga_ls8c_ard_3-2-1_098084_2023-08-29_final
2023-08-30 09:13:43	ga_ls8c_ard_3-2-1_089083_2023-08-29_final
2023-08-30 09:14:07	ga_ls8c_ard_3-2-1_089084_2023-08-29_final
2023-08-30 10:52:36	ga_ls8c_ard_3-2-1_105083_2023-08-30_final
2023-08-31 11:36:15	ga_ls8c_ard_3-2-1_112084_2023-08-31_final
2023-09-02 09:44:36	ga_ls8c_ard_3-2-1_094083_2023-09-02_final
2023-09-02 09:45:00	ga_ls8c_ard_3-2-1_094084_2023-09-02_final
2023-09-02 11:23:29	ga_ls8c_ard_3-2-1_110083_2023-09-02_final
2023-09-02 11:23:53	ga_ls8c_ard_3-2-1_110084_2023-09-02_final
2023-09-03 10:27:52	ga_ls8c_ard_3-2-1_101083_2023-09-03_final
2023-09-04 11:11:07	ga_ls8c_ard_3-2-1_108083_2023-09-04_final
2023-09-04 11:11:31	ga_ls8c_ard_3-2-1_108084_2023-09-04_final
2023-09-07 10:03:07	ga_ls8c_ard_3-2-1_097083_2023-09-07_final
2023-09-07 10:03:31	ga_ls8c_ard_3-2-1_097084_2023-09-07_final
2023-09-07 11:42:00	ga_ls8c_ard_3-2-1_113083_2023-09-07_final
2023-09-07 11:42:24	ga_ls8c_ard_3-2-1_113084_2023-09-07_final
2023-09-08 09:07:31	ga_ls8c_ard_3-2-1_088083_2023-09-07_final
2023-09-09 09:50:47	ga_ls8c_ard_3-2-1_095083_2023-09-09_final
2023-09-09 09:51:11	ga_ls8c_ard_3-2-1_095084_2023-09-09_final
2023-09-09 11:29:40	ga_ls8c_ard_3-2-1_111083_2023-09-09_final
2023-09-09 11:30:04	ga_ls8c_ard_3-2-1_111084_2023-09-09_final
2023-09-11 11:17:20	ga_ls8c_ard_3-2-1_109083_2023-09-11_final
2023-09-11 11:17:44	ga_ls8c_ard_3-2-1_109084_2023-09-11_final
2023-09-12 10:21:43	ga_ls8c_ard_3-2-1_100083_2023-09-12_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