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
2021-10-20 10:45:39	ga_ls8c_ard_3-2-0_104080_2021-10-20_final
2021-10-25 11:04:59	ga_ls8c_ard_3-2-0_107082_2021-10-25_final
2021-10-26 11:46:15	ga_ls8c_ard_3-2-0_114077_2021-10-26_final
2021-10-28 09:53:49	ga_ls8c_ard_3-2-0_096074_2021-10-28_final
2021-10-30 09:42:15	ga_ls8c_ard_3-2-0_094076_2021-10-30_final
2021-11-08 09:38:50	ga_ls8c_ard_3-2-0_093083_2021-11-08_final
2021-11-08 09:39:14	ga_ls8c_ard_3-2-0_093084_2021-11-08_final
2021-11-14 10:37:00	ga_ls8c_ard_3-2-0_103074_2021-11-14_final
2021-11-16 10:24:38	ga_ls8c_ard_3-2-0_101074_2021-11-16_final
2021-11-18 10:11:51	ga_ls8c_ard_3-2-0_099073_2021-11-18_final
2021-11-26 11:03:19	ga_ls8c_ard_3-2-0_107078_2021-11-26_final
2021-11-28 10:52:57	ga_ls8c_ard_3-2-0_105083_2021-11-28_final
2021-11-30 10:37:00	ga_ls8c_ard_3-2-0_103074_2021-11-30_final
2021-11-30 10:37:24	ga_ls8c_ard_3-2-0_103075_2021-11-30_final
2021-12-06 10:00:43	ga_ls8c_ard_3-2-1_097076_2021-12-06_final
2021-12-09 10:32:49	ga_ls8c_ard_3-2-1_102079_2021-12-09_final
2021-12-26 09:38:43	ga_ls8c_ard_3-2-1_093083_2021-12-26_final
2022-01-02 11:18:33	ga_ls8c_ard_3-2-1_110070_2022-01-02_final
2022-01-06 09:20:08	ga_ls8c_ard_3-2-1_090083_2022-01-05_final
2022-01-09 09:49:50	ga_ls8c_ard_3-2-1_095080_2022-01-09_final
2022-01-11 11:16:21	ga_ls8c_ard_3-2-1_109080_2022-01-11_final
2022-01-20 11:10:08	ga_ls8c_ard_3-2-1_108080_2022-01-20_final
2022-02-05 09:31:35	ga_ls8c_ard_3-2-1_092081_2022-02-05_final
2022-02-16 10:51:28	ga_ls8c_ard_3-2-1_105080_2022-02-16_final
2022-02-19 09:46:15	ga_ls8c_ard_3-2-1_094087_2022-02-19_final
2022-02-23 10:58:24	ga_ls8c_ard_3-2-1_106082_2022-02-23_final
2022-02-27 10:30:53	ga_ls8c_ard_3-2-1_102075_2022-02-27_final
2022-03-11 10:57:09	ga_ls8c_ard_3-2-1_106079_2022-03-11_final
2022-03-11 10:58:21	ga_ls8c_ard_3-2-1_106082_2022-03-11_final
2022-03-16 09:36:22	ga_ls8c_ard_3-2-1_093078_2022-03-16_final
2022-03-25 09:29:40	ga_ls8c_ard_3-2-1_092077_2022-03-24_final
2022-03-27 10:56:57	ga_ls8c_ard_3-2-1_106079_2022-03-27_final
2022-04-03 11:04:17	ga_ls8c_ard_3-2-1_107082_2022-04-03_final
2022-04-07 10:38:49	ga_ls8c_ard_3-2-1_103080_2022-04-07_final
2022-04-09 10:23:17	ga_ls8c_ard_3-2-1_101072_2022-04-09_final
2022-04-22 09:56:23	ga_ls8c_ard_3-2-1_096082_2022-04-22_final
2022-04-23 10:36:51	ga_ls8c_ard_3-2-1_103075_2022-04-23_final
2022-04-24 11:22:30	ga_ls8c_ard_3-2-1_110081_2022-04-24_final
2022-05-01 11:29:52	ga_ls8c_ard_3-2-1_111084_2022-05-01_final
2022-05-03 09:35:51	ga_ls8c_ard_3-2-1_093077_2022-05-03_final
2022-05-04 11:58:01	ga_ls8c_ard_3-2-1_116077_2022-05-04_final
2022-05-07 09:12:46	ga_ls8c_ard_3-2-1_089081_2022-05-06_final
2022-05-09 10:38:55	ga_ls8c_ard_3-2-1_103080_2022-05-09_final
2022-05-13 10:15:02	ga_ls8c_ard_3-2-1_099082_2022-05-13_final
2022-05-14 09:19:25	ga_ls8c_ard_3-2-1_090082_2022-05-13_final
2022-05-19 09:36:23	ga_ls8c_ard_3-2-1_093078_2022-05-19_final
2022-05-26 09:41:21	ga_ls8c_ard_3-2-1_094075_2022-05-26_final
2022-06-08 10:51:05	ga_ls8c_ard_3-2-1_105079_2022-06-08_final
2022-06-09 09:53:53	ga_ls8c_ard_3-2-1_096075_2022-06-09_final
2022-06-15 10:58:09	ga_ls8c_ard_3-2-1_106081_2022-06-15_final
2022-06-19 10:29:52	ga_ls8c_ard_3-2-1_102072_2022-06-19_final
2022-07-01 10:56:37	ga_ls8c_ard_3-2-1_106077_2022-07-01_final
2022-07-11 09:56:24	ga_ls8c_ard_3-2-1_096081_2022-07-11_final
2022-07-13 11:22:55	ga_ls8c_ard_3-2-1_110081_2022-07-13_final
2022-07-15 09:30:04	ga_ls8c_ard_3-2-1_092077_2022-07-15_final
2022-07-15 09:30:28	ga_ls8c_ard_3-2-1_092078_2022-07-15_final
2022-07-17 10:56:37	ga_ls8c_ard_3-2-1_106077_2022-07-17_final
2022-07-26 10:48:58	ga_ls8c_ard_3-2-1_105073_2022-07-26_final
2022-07-26 10:51:22	ga_ls8c_ard_3-2-1_105079_2022-07-26_final
2022-07-26 10:51:45	ga_ls8c_ard_3-2-1_105080_2022-07-26_final
2022-07-28 10:35:50	ga_ls8c_ard_3-2-1_103071_2022-07-28_final
2022-07-30 10:25:29	ga_ls8c_ard_3-2-1_101076_2022-07-30_final
2022-08-05 11:30:32	ga_ls8c_ard_3-2-1_111084_2022-08-05_final
2022-08-11 09:14:13	ga_ls8c_ard_3-2-1_089083_2022-08-10_final
2022-08-12 09:56:17	ga_ls8c_ard_3-2-1_096080_2022-08-12_final
2022-08-13 10:35:58	ga_ls8c_ard_3-2-1_103071_2022-08-13_final
2022-08-16 09:30:47	ga_ls8c_ard_3-2-1_092078_2022-08-16_final
2022-08-16 09:31:11	ga_ls8c_ard_3-2-1_092079_2022-08-16_final
2022-08-26 10:07:05	ga_ls8c_ard_3-2-1_098076_2022-08-26_final
2022-08-27 10:51:56	ga_ls8c_ard_3-2-1_105080_2022-08-27_final
2022-09-01 11:10:28	ga_ls8c_ard_3-2-1_108080_2022-09-01_final
2022-09-12 10:52:01	ga_ls8c_ard_3-2-1_105080_2022-09-12_final
2022-09-13 09:55:36	ga_ls8c_ard_3-2-1_096078_2022-09-13_final
2022-09-19 10:57:49	ga_ls8c_ard_3-2-1_106079_2022-09-19_final
2022-09-20 11:39:30	ga_ls8c_ard_3-2-1_113075_2022-09-20_final
2022-09-21 10:45:52	ga_ls8c_ard_3-2-1_104080_2022-09-21_final
2022-09-26 11:03:37	ga_ls8c_ard_3-2-1_107078_2022-09-26_final
2022-09-26 11:04:01	ga_ls8c_ard_3-2-1_107079_2022-09-26_final
2022-09-28 10:50:51	ga_ls8c_ard_3-2-1_105077_2022-09-28_final
2022-09-29 09:55:37	ga_ls8c_ard_3-2-1_096078_2022-09-29_final
2022-09-29 09:57:13	ga_ls8c_ard_3-2-1_096082_2022-09-29_final
2022-10-02 10:26:30	ga_ls8c_ard_3-2-1_101078_2022-10-02_final
2022-10-05 09:18:54	ga_ls8c_ard_3-2-1_090079_2022-10-04_final
2022-10-17 11:24:02	ga_ls8c_ard_3-2-1_110083_2022-10-17_final
2022-11-16 11:35:36	ga_ls8c_ard_3-2-1_112081_2022-11-16_final
2022-11-21 10:12:51	ga_ls8c_ard_3-2-1_099075_2022-11-21_final
2022-11-26 10:33:25	ga_ls8c_ard_3-2-1_102080_2022-11-26_final
2022-12-02 11:34:25	ga_ls8c_ard_3-2-1_112078_2022-12-02_final
2022-12-09 10:01:18	ga_ls8c_ard_3-2-1_097077_2022-12-09_final
2022-12-11 09:49:43	ga_ls8c_ard_3-2-1_095079_2022-12-11_final
2022-12-11 11:27:25	ga_ls8c_ard_3-2-1_111076_2022-12-11_final
2022-12-27 09:49:36	ga_ls8c_ard_3-2-1_095079_2022-12-27_final
2022-12-28 10:32:52	ga_ls8c_ard_3-2-1_102079_2022-12-28_final
2023-01-08 11:53:36	ga_ls8c_ard_3-2-1_115080_2023-01-08_final
2023-01-19 11:35:21	ga_ls8c_ard_3-2-1_112081_2023-01-19_final
2023-01-26 11:39:37	ga_ls8c_ard_3-2-1_113076_2023-01-26_final
2023-02-12 10:45:07	ga_ls8c_ard_3-2-1_104079_2023-02-12_final
2023-02-22 09:43:33	ga_ls8c_ard_3-2-1_094080_2023-02-22_final
2023-02-24 09:30:20	ga_ls8c_ard_3-2-1_092078_2023-02-24_final
2023-03-01 11:29:44	ga_ls8c_ard_3-2-1_111083_2023-03-01_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