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
2022-01-24 10:42:35	ga_ls8c_ard_3-2-1_104073_2022-01-24_final
2022-02-07 09:18:25	ga_ls8c_ard_3-2-1_090079_2022-02-06_final
2022-02-07 10:56:54	ga_ls8c_ard_3-2-1_106078_2022-02-07_final
2022-02-24 09:59:11	ga_ls8c_ard_3-2-1_097073_2022-02-24_final
2022-02-24 10:01:35	ga_ls8c_ard_3-2-1_097079_2022-02-24_final
2022-03-03 10:05:21	ga_ls8c_ard_3-2-1_098073_2022-03-03_final
2022-03-23 09:45:15	ga_ls8c_ard_3-2-1_094085_2022-03-23_final
2022-03-25 11:06:33	ga_ls8c_ard_3-2-1_108072_2022-03-25_final
2022-04-06 11:35:38	ga_ls8c_ard_3-2-1_112083_2022-04-06_final
2022-04-21 09:12:20	ga_ls8c_ard_3-2-1_089080_2022-04-20_final
2022-04-22 11:35:16	ga_ls8c_ard_3-2-1_112082_2022-04-22_final
2022-04-29 09:59:19	ga_ls8c_ard_3-2-1_097074_2022-04-29_final
2022-05-11 10:23:47	ga_ls8c_ard_3-2-1_101073_2022-05-11_final
2022-05-12 11:06:15	ga_ls8c_ard_3-2-1_108071_2022-05-12_final
2022-05-13 10:15:26	ga_ls8c_ard_3-2-1_099083_2022-05-13_final
2022-05-16 10:40:46	ga_ls8c_ard_3-2-1_104069_2022-05-16_final
2022-05-27 10:23:48	ga_ls8c_ard_3-2-1_101073_2022-05-27_final
2022-06-04 09:40:28	ga_ls8c_ard_3-2-1_093088_2022-06-04_final
2022-06-04 11:17:21	ga_ls8c_ard_3-2-1_109083_2022-06-04_final
2022-06-11 11:21:38	ga_ls8c_ard_3-2-1_110078_2022-06-11_final
2022-06-29 11:06:35	ga_ls8c_ard_3-2-1_108071_2022-06-29_final
2022-07-03 10:40:40	ga_ls8c_ard_3-2-1_104068_2022-07-03_final
2022-07-17 10:54:37	ga_ls8c_ard_3-2-1_106072_2022-07-17_final
2022-08-01 10:15:32	ga_ls8c_ard_3-2-1_099082_2022-08-01_final
2022-08-13 10:36:45	ga_ls8c_ard_3-2-1_103073_2022-08-13_final
2022-08-16 11:06:52	ga_ls8c_ard_3-2-1_108071_2022-08-16_final
2022-08-19 10:02:05	ga_ls8c_ard_3-2-1_097079_2022-08-19_final
2022-08-23 09:35:23	ga_ls8c_ard_3-2-1_093074_2022-08-23_final
2022-08-23 11:17:03	ga_ls8c_ard_3-2-1_109081_2022-08-23_final
2022-08-28 09:55:55	ga_ls8c_ard_3-2-1_096079_2022-08-28_final
2022-09-12 09:15:31	ga_ls8c_ard_3-2-1_089086_2022-09-11_final
2022-09-15 09:43:15	ga_ls8c_ard_3-2-1_094078_2022-09-15_final
2022-09-16 10:25:43	ga_ls8c_ard_3-2-1_101076_2022-09-16_final
2022-09-30 10:39:41	ga_ls8c_ard_3-2-1_103080_2022-09-30_final
2022-10-14 09:15:24	ga_ls8c_ard_3-2-1_089086_2022-10-13_final
2022-10-16 10:38:22	ga_ls8c_ard_3-2-1_103077_2022-10-16_final
2022-10-17 11:19:15	ga_ls8c_ard_3-2-1_110071_2022-10-17_final
2022-10-23 10:41:26	ga_ls8c_ard_3-2-1_104069_2022-10-23_final
2022-11-12 10:19:29	ga_ls8c_ard_3-2-1_100076_2022-11-12_final
2022-11-14 10:08:42	ga_ls8c_ard_3-2-1_098080_2022-11-14_final
2022-11-23 11:42:59	ga_ls8c_ard_3-2-1_113084_2022-11-23_final
2022-12-02 11:36:25	ga_ls8c_ard_3-2-1_112083_2022-12-02_final
2022-12-18 09:55:49	ga_ls8c_ard_3-2-1_096079_2022-12-18_final
2022-12-20 11:23:31	ga_ls8c_ard_3-2-1_110082_2022-12-20_final
2023-01-19 09:57:16	ga_ls8c_ard_3-2-1_096083_2023-01-19_final
2023-01-25 09:23:03	ga_ls8c_ard_3-2-1_090090_2023-01-24_final
2023-01-30 09:36:01	ga_ls8c_ard_3-2-1_093076_2023-01-30_final
2023-01-31 11:58:58	ga_ls8c_ard_3-2-1_116078_2023-01-31_final
2023-02-04 11:33:03	ga_ls8c_ard_3-2-1_112075_2023-02-04_final
2023-02-05 10:39:25	ga_ls8c_ard_3-2-1_103080_2023-02-05_final
2023-02-10 09:23:01	ga_ls8c_ard_3-2-1_090090_2023-02-09_final
2023-02-21 10:38:23	ga_ls8c_ard_3-2-1_103078_2023-02-21_final
2023-03-19 11:15:14	ga_ls8c_ard_3-2-1_109078_2023-03-19_final
2023-03-24 09:53:13	ga_ls8c_ard_3-2-1_096074_2023-03-24_final
2023-04-07 10:05:24	ga_ls8c_ard_3-2-1_098074_2023-04-07_final
2023-04-14 11:50:22	ga_ls8c_ard_3-2-1_115074_2023-04-14_final
2023-04-19 10:31:10	ga_ls8c_ard_3-2-1_102077_2023-04-19_final
2023-04-20 11:17:13	ga_ls8c_ard_3-2-1_109084_2023-04-20_final
2023-05-13 09:45:06	ga_ls8c_ard_3-2-1_094086_2023-05-13_final
2023-05-13 11:23:35	ga_ls8c_ard_3-2-1_110085_2023-05-13_final
2023-05-22 09:32:56	ga_ls8c_ard_3-2-1_093071_2023-05-22_final
2023-05-23 11:57:53	ga_ls8c_ard_3-2-1_116078_2023-05-23_final
2023-05-31 11:09:39	ga_ls8c_ard_3-2-1_108081_2023-05-31_final
2023-06-06 10:32:14	ga_ls8c_ard_3-2-1_102080_2023-06-06_final
2023-06-16 11:09:48	ga_ls8c_ard_3-2-1_108081_2023-06-16_final
2023-06-22 10:31:08	ga_ls8c_ard_3-2-1_102077_2023-06-22_final
2023-06-26 11:45:45	ga_ls8c_ard_3-2-1_114078_2023-06-26_final
2023-06-29 10:34:14	ga_ls8c_ard_3-2-1_103069_2023-06-29_final
2023-06-29 10:37:49	ga_ls8c_ard_3-2-1_103078_2023-06-29_final
2023-07-12 10:09:50	ga_ls8c_ard_3-2-1_098085_2023-07-12_final
2023-07-16 09:45:31	ga_ls8c_ard_3-2-1_094086_2023-07-16_final
2023-07-23 09:46:56	ga_ls8c_ard_3-2-1_095074_2023-07-23_final
2023-07-23 09:47:44	ga_ls8c_ard_3-2-1_095076_2023-07-23_final
2023-07-26 10:20:17	ga_ls8c_ard_3-2-1_100080_2023-07-26_final
2023-07-27 11:00:22	ga_ls8c_ard_3-2-1_107072_2023-07-27_final
2023-07-29 10:52:01	ga_ls8c_ard_3-2-1_105082_2023-07-29_final
2023-08-05 09:18:57	ga_ls8c_ard_3-2-1_090081_2023-08-04_final
2023-08-11 11:57:14	ga_ls8c_ard_3-2-1_116075_2023-08-11_final
2023-08-24 09:46:24	ga_ls8c_ard_3-2-1_095072_2023-08-24_final
2023-08-27 10:21:18	ga_ls8c_ard_3-2-1_100082_2023-08-27_final
2023-09-08 10:41:12	ga_ls8c_ard_3-2-1_104070_2023-09-08_final
2023-09-11 11:12:33	ga_ls8c_ard_3-2-1_109071_2023-09-11_final
2023-09-27 11:12:38	ga_ls8c_ard_3-2-1_109071_2023-09-27_final
2023-10-01 10:46:20	ga_ls8c_ard_3-2-1_105067_2023-10-01_final
2023-10-09 10:02:30	ga_ls8c_ard_3-2-1_097081_2023-10-09_final
2023-11-17 11:45:14	ga_ls8c_ard_3-2-1_114075_2023-11-17_final
2023-11-26 10:01:48	ga_ls8c_ard_3-2-1_097079_2023-11-26_final
2023-11-30 11:16:44	ga_ls8c_ard_3-2-1_109081_2023-11-30_final
2023-12-11 09:18:26	ga_ls8c_ard_3-2-1_090079_2023-12-10_final
2023-12-20 10:52:01	ga_ls8c_ard_3-2-1_105081_2023-12-20_final
2023-12-24 10:25:18	ga_ls8c_ard_3-2-1_101076_2023-12-24_final
2024-01-01 11:12:15	ga_ls8c_ard_3-2-1_109070_2024-01-01_final
2024-01-02 11:57:54	ga_ls8c_ard_3-2-1_116076_2024-01-02_final
2024-01-03 09:28:10	ga_ls8c_ard_3-2-1_091088_2024-01-02_final
2024-01-04 11:45:30	ga_ls8c_ard_3-2-1_114076_2024-01-04_final
2024-01-21 10:51:53	ga_ls8c_ard_3-2-1_105081_2024-01-21_final
2024-01-24 09:43:03	ga_ls8c_ard_3-2-1_094079_2024-01-24_final
2024-02-06 10:50:18	ga_ls8c_ard_3-2-1_105077_2024-02-06_final
2024-02-11 11:09:38	ga_ls8c_ard_3-2-1_108079_2024-02-11_final
2024-03-03 11:23:38	ga_ls8c_ard_3-2-1_111068_2024-03-03_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