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
2018-09-16 10:04:58	ga_ls8c_ard_3-0-0_098073_2018-09-16_final
2018-09-16 10:05:22	ga_ls8c_ard_3-0-0_098074_2018-09-16_final
2018-09-16 11:44:15	ga_ls8c_ard_3-0-0_114074_2018-09-16_final
2018-09-17 09:09:45	ga_ls8c_ard_3-0-0_089074_2018-09-16_final
2018-09-17 10:48:14	ga_ls8c_ard_3-0-0_105073_2018-09-17_final
2018-09-17 10:48:38	ga_ls8c_ard_3-0-0_105074_2018-09-17_final
2018-10-04 09:52:45	ga_ls8c_ard_3-0-0_096073_2018-10-04_final
2018-10-04 09:53:09	ga_ls8c_ard_3-0-0_096074_2018-10-04_final
2018-10-04 11:31:38	ga_ls8c_ard_3-0-0_112073_2018-10-04_final
2018-10-04 11:32:02	ga_ls8c_ard_3-0-0_112074_2018-10-04_final
2018-10-05 10:36:01	ga_ls8c_ard_3-0-0_103073_2018-10-05_final
2018-10-05 10:36:25	ga_ls8c_ard_3-0-0_103074_2018-10-05_final
2018-10-06 09:40:24	ga_ls8c_ard_3-0-0_094073_2018-10-06_final
2018-10-06 09:40:48	ga_ls8c_ard_3-0-0_094074_2018-10-06_final
2018-10-06 11:19:17	ga_ls8c_ard_3-0-0_110073_2018-10-06_final
2018-10-06 11:19:41	ga_ls8c_ard_3-0-0_110074_2018-10-06_final
2018-10-07 10:23:40	ga_ls8c_ard_3-0-0_101073_2018-10-07_final
2018-10-07 10:24:04	ga_ls8c_ard_3-0-0_101074_2018-10-07_final
2018-12-23 09:52:52	ga_ls8c_ard_3-0-0_096073_2018-12-23_final
2018-12-23 09:53:15	ga_ls8c_ard_3-0-0_096074_2018-12-23_final
2018-12-23 11:31:45	ga_ls8c_ard_3-0-0_112073_2018-12-23_final
2018-12-23 11:32:09	ga_ls8c_ard_3-0-0_112074_2018-12-23_final
2018-12-24 10:36:07	ga_ls8c_ard_3-0-0_103073_2018-12-24_final
2018-12-24 10:36:31	ga_ls8c_ard_3-0-0_103074_2018-12-24_final
2018-12-25 09:40:30	ga_ls8c_ard_3-0-0_094073_2018-12-25_final
2018-12-25 09:40:54	ga_ls8c_ard_3-0-0_094074_2018-12-25_final
2018-12-25 11:19:23	ga_ls8c_ard_3-0-0_110073_2018-12-25_final
2018-12-25 11:19:47	ga_ls8c_ard_3-0-0_110074_2018-12-25_final
2018-12-26 10:23:46	ga_ls8c_ard_3-0-0_101073_2018-12-26_final
2018-12-26 10:24:10	ga_ls8c_ard_3-0-0_101074_2018-12-26_final
2019-01-06 10:05:12	ga_ls8c_ard_3-0-0_098073_2019-01-06_final
2019-01-06 10:05:36	ga_ls8c_ard_3-0-0_098074_2019-01-06_final
2019-01-06 11:44:29	ga_ls8c_ard_3-0-0_114074_2019-01-06_final
2019-01-07 09:09:59	ga_ls8c_ard_3-0-0_089074_2019-01-06_final
2019-01-07 10:48:28	ga_ls8c_ard_3-0-0_105073_2019-01-07_final
2022-11-23 11:38:35	ga_ls8c_ard_3-2-1_113073_2022-11-23_final
2022-11-23 11:38:59	ga_ls8c_ard_3-2-1_113074_2022-11-23_final
2022-11-24 10:42:58	ga_ls8c_ard_3-2-1_104073_2022-11-24_final
2022-11-24 10:43:22	ga_ls8c_ard_3-2-1_104074_2022-11-24_final
2022-11-25 09:47:21	ga_ls8c_ard_3-2-1_095073_2022-11-25_final
2022-11-25 09:47:45	ga_ls8c_ard_3-2-1_095074_2022-11-25_final
2022-11-30 10:05:54	ga_ls8c_ard_3-2-1_098073_2022-11-30_final
2022-11-30 10:06:18	ga_ls8c_ard_3-2-1_098074_2022-11-30_final
2022-11-30 11:45:11	ga_ls8c_ard_3-2-1_114074_2022-11-30_final
2022-12-01 09:10:41	ga_ls8c_ard_3-2-1_089074_2022-11-30_final
2022-12-02 11:32:26	ga_ls8c_ard_3-2-1_112073_2022-12-02_final
2022-12-02 11:32:50	ga_ls8c_ard_3-2-1_112074_2022-12-02_final
2022-12-03 10:36:48	ga_ls8c_ard_3-2-1_103073_2022-12-03_final
2022-12-03 10:37:12	ga_ls8c_ard_3-2-1_103074_2022-12-03_final
2022-12-04 09:41:11	ga_ls8c_ard_3-2-1_094073_2022-12-04_final
2022-12-04 09:41:35	ga_ls8c_ard_3-2-1_094074_2022-12-04_final
2023-01-05 11:19:55	ga_ls8c_ard_3-2-1_110073_2023-01-05_final
2023-01-05 11:20:19	ga_ls8c_ard_3-2-1_110074_2023-01-05_final
2023-01-11 10:42:48	ga_ls8c_ard_3-2-1_104073_2023-01-11_final
2023-01-11 10:43:12	ga_ls8c_ard_3-2-1_104074_2023-01-11_final
2023-01-12 09:47:10	ga_ls8c_ard_3-2-1_095073_2023-01-12_final
2023-01-12 09:47:34	ga_ls8c_ard_3-2-1_095074_2023-01-12_final
2023-01-12 11:26:03	ga_ls8c_ard_3-2-1_111073_2023-01-12_final
2023-01-12 11:26:27	ga_ls8c_ard_3-2-1_111074_2023-01-12_final
2023-03-02 10:30:07	ga_ls8c_ard_3-2-1_102073_2023-03-02_final
2023-03-03 09:34:29	ga_ls8c_ard_3-2-1_093073_2023-03-03_final
2023-03-03 09:34:53	ga_ls8c_ard_3-2-1_093074_2023-03-03_final
2023-03-03 11:13:22	ga_ls8c_ard_3-2-1_109073_2023-03-03_final
2023-03-04 10:17:44	ga_ls8c_ard_3-2-1_100073_2023-03-04_final
2023-03-04 10:18:08	ga_ls8c_ard_3-2-1_100074_2023-03-04_final
2023-03-30 10:54:35	ga_ls8c_ard_3-2-1_106073_2023-03-30_final
2023-03-31 09:58:57	ga_ls8c_ard_3-2-1_097073_2023-03-31_final
2023-03-31 09:59:21	ga_ls8c_ard_3-2-1_097074_2023-03-31_final
2023-03-31 11:37:50	ga_ls8c_ard_3-2-1_113073_2023-03-31_final
2023-04-01 10:42:12	ga_ls8c_ard_3-2-1_104073_2023-04-01_final
2023-04-02 09:46:34	ga_ls8c_ard_3-2-1_095073_2023-04-02_final
2023-04-04 11:13:03	ga_ls8c_ard_3-2-1_109073_2023-04-04_final
2023-04-04 11:13:27	ga_ls8c_ard_3-2-1_109074_2023-04-04_final
2023-04-13 09:27:49	ga_ls8c_ard_3-2-1_092073_2023-04-12_final
2023-04-13 11:06:42	ga_ls8c_ard_3-2-1_108073_2023-04-13_final
2023-04-14 10:11:05	ga_ls8c_ard_3-2-1_099073_2023-04-14_final
2023-04-14 10:11:29	ga_ls8c_ard_3-2-1_099074_2023-04-14_final
2023-04-15 10:54:20	ga_ls8c_ard_3-2-1_106073_2023-04-15_final
2023-04-15 10:54:44	ga_ls8c_ard_3-2-1_106074_2023-04-15_final
2023-05-25 10:04:39	ga_ls8c_ard_3-2-1_098073_2023-05-25_final
2023-05-25 10:05:03	ga_ls8c_ard_3-2-1_098074_2023-05-25_final
2023-05-25 11:43:56	ga_ls8c_ard_3-2-1_114074_2023-05-25_final
2023-05-26 09:09:26	ga_ls8c_ard_3-2-1_089074_2023-05-25_final
2023-05-26 10:47:55	ga_ls8c_ard_3-2-1_105073_2023-05-26_final
2023-05-26 10:48:19	ga_ls8c_ard_3-2-1_105074_2023-05-26_final
2023-05-29 09:39:56	ga_ls8c_ard_3-2-1_094073_2023-05-29_final
2023-05-29 09:40:20	ga_ls8c_ard_3-2-1_094074_2023-05-29_final
2023-05-29 11:18:49	ga_ls8c_ard_3-2-1_110073_2023-05-29_final
2023-05-29 11:19:13	ga_ls8c_ard_3-2-1_110074_2023-05-29_final
2023-05-30 10:23:12	ga_ls8c_ard_3-2-1_101073_2023-05-30_final
2023-05-30 10:23:36	ga_ls8c_ard_3-2-1_101074_2023-05-30_final
2023-05-31 09:27:34	ga_ls8c_ard_3-2-1_092073_2023-05-30_final
2023-05-31 09:27:58	ga_ls8c_ard_3-2-1_092074_2023-05-30_final
2023-05-31 11:06:27	ga_ls8c_ard_3-2-1_108073_2023-05-31_final
2023-05-31 11:06:51	ga_ls8c_ard_3-2-1_108074_2023-05-31_final
2023-06-01 10:10:50	ga_ls8c_ard_3-2-1_099073_2023-06-01_final
2023-06-01 10:11:14	ga_ls8c_ard_3-2-1_099074_2023-06-01_final
2023-06-01 11:50:07	ga_ls8c_ard_3-2-1_115074_2023-06-01_final
2023-06-02 09:15:36	ga_ls8c_ard_3-2-1_090074_2023-06-01_final
2023-06-02 10:54:06	ga_ls8c_ard_3-2-1_106073_2023-06-02_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