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
2023-07-18 09:29:58	ga_ls8c_ard_3-2-1_092078_2023-07-17_final
2023-07-18 09:33:33	ga_ls8c_ard_3-2-1_092087_2023-07-18_final
2023-07-19 10:11:37	ga_ls8c_ard_3-2-1_099074_2023-07-19_final
2023-07-20 10:56:28	ga_ls8c_ard_3-2-1_106078_2023-07-20_final
2023-07-20 10:57:16	ga_ls8c_ard_3-2-1_106080_2023-07-20_final
2023-07-21 10:01:39	ga_ls8c_ard_3-2-1_097080_2023-07-21_final
2023-07-22 10:44:32	ga_ls8c_ard_3-2-1_104079_2023-07-22_final
2023-07-22 10:45:20	ga_ls8c_ard_3-2-1_104081_2023-07-22_final
2023-07-23 11:28:13	ga_ls8c_ard_3-2-1_111080_2023-07-23_final
2023-07-27 11:02:21	ga_ls8c_ard_3-2-1_107077_2023-07-27_final
2023-07-27 11:03:09	ga_ls8c_ard_3-2-1_107079_2023-07-27_final
2023-07-30 09:54:00	ga_ls8c_ard_3-2-1_096076_2023-07-30_final
2023-07-30 09:54:24	ga_ls8c_ard_3-2-1_096077_2023-07-30_final
2023-07-30 09:57:36	ga_ls8c_ard_3-2-1_096085_2023-07-30_final
2023-07-30 11:32:05	ga_ls8c_ard_3-2-1_112074_2023-07-30_final
2023-07-30 11:32:53	ga_ls8c_ard_3-2-1_112076_2023-07-30_final
2023-07-31 10:36:29	ga_ls8c_ard_3-2-1_103074_2023-07-31_final
2023-07-31 10:38:04	ga_ls8c_ard_3-2-1_103078_2023-07-31_final
2023-07-31 10:38:28	ga_ls8c_ard_3-2-1_103079_2023-07-31_final
2023-07-31 10:38:52	ga_ls8c_ard_3-2-1_103080_2023-07-31_final
2023-08-01 09:45:15	ga_ls8c_ard_3-2-1_094085_2023-08-01_final
2023-08-02 10:22:32	ga_ls8c_ard_3-2-1_101070_2023-08-02_final
2023-08-03 09:31:18	ga_ls8c_ard_3-2-1_092081_2023-08-03_final
2023-08-05 10:57:02	ga_ls8c_ard_3-2-1_106079_2023-08-05_final
2023-08-07 10:44:17	ga_ls8c_ard_3-2-1_104078_2023-08-07_final
2023-08-08 09:49:51	ga_ls8c_ard_3-2-1_095081_2023-08-08_final
2023-08-15 09:54:06	ga_ls8c_ard_3-2-1_096076_2023-08-15_final
2023-08-15 09:54:30	ga_ls8c_ard_3-2-1_096077_2023-08-15_final
2023-08-15 09:57:41	ga_ls8c_ard_3-2-1_096085_2023-08-15_final
2023-08-16 10:36:58	ga_ls8c_ard_3-2-1_103075_2023-08-16_final
2023-08-20 10:11:53	ga_ls8c_ard_3-2-1_099074_2023-08-20_final
2023-08-21 10:57:09	ga_ls8c_ard_3-2-1_106079_2023-08-21_final
2023-08-23 10:45:36	ga_ls8c_ard_3-2-1_104081_2023-08-23_final
2023-08-24 09:49:11	ga_ls8c_ard_3-2-1_095079_2023-08-24_final
2023-08-24 09:49:35	ga_ls8c_ard_3-2-1_095080_2023-08-24_final
2023-08-24 11:26:29	ga_ls8c_ard_3-2-1_111075_2023-08-24_final
2023-08-24 11:27:17	ga_ls8c_ard_3-2-1_111077_2023-08-24_final
2023-08-25 10:30:28	ga_ls8c_ard_3-2-1_102074_2023-08-25_final
2023-08-27 10:20:30	ga_ls8c_ard_3-2-1_100080_2023-08-27_final
2023-08-30 10:50:36	ga_ls8c_ard_3-2-1_105078_2023-08-30_final
2023-08-31 09:54:35	ga_ls8c_ard_3-2-1_096077_2023-08-31_final
2023-08-31 11:32:16	ga_ls8c_ard_3-2-1_112074_2023-08-31_final
2023-08-31 11:34:39	ga_ls8c_ard_3-2-1_112080_2023-08-31_final
2023-09-02 09:42:36	ga_ls8c_ard_3-2-1_094078_2023-09-02_final
2023-09-07 10:02:19	ga_ls8c_ard_3-2-1_097081_2023-09-07_final
2023-09-09 09:49:11	ga_ls8c_ard_3-2-1_095079_2023-09-09_final
2023-09-09 11:25:17	ga_ls8c_ard_3-2-1_111072_2023-09-09_final
2023-09-10 10:30:28	ga_ls8c_ard_3-2-1_102074_2023-09-10_final
2023-09-11 11:13:45	ga_ls8c_ard_3-2-1_109074_2023-09-11_final
2023-09-15 10:50:39	ga_ls8c_ard_3-2-1_105078_2023-09-15_final
2023-09-15 10:51:27	ga_ls8c_ard_3-2-1_105080_2023-09-15_final
2023-09-16 09:54:38	ga_ls8c_ard_3-2-1_096077_2023-09-16_final
2023-09-16 09:55:50	ga_ls8c_ard_3-2-1_096080_2023-09-16_final
2023-09-16 11:33:55	ga_ls8c_ard_3-2-1_112078_2023-09-16_final
2023-09-17 10:37:06	ga_ls8c_ard_3-2-1_103075_2023-09-17_final
2023-09-17 10:37:30	ga_ls8c_ard_3-2-1_103076_2023-09-17_final
2023-09-20 11:08:01	ga_ls8c_ard_3-2-1_108075_2023-09-20_final
2023-09-20 11:09:37	ga_ls8c_ard_3-2-1_108079_2023-09-20_final
2023-09-25 11:26:59	ga_ls8c_ard_3-2-1_111076_2023-09-25_final
2023-09-25 11:27:23	ga_ls8c_ard_3-2-1_111077_2023-09-25_final
2023-09-28 10:22:13	ga_ls8c_ard_3-2-1_100084_2023-09-28_final
2023-09-29 11:03:53	ga_ls8c_ard_3-2-1_107080_2023-09-29_final
2023-10-01 10:50:43	ga_ls8c_ard_3-2-1_105078_2023-10-01_final
2023-10-06 11:09:39	ga_ls8c_ard_3-2-1_108079_2023-10-06_final
2023-10-08 09:18:50	ga_ls8c_ard_3-2-1_090080_2023-10-07_final
2023-10-09 11:39:00	ga_ls8c_ard_3-2-1_113075_2023-10-09_final
2023-10-11 09:48:34	ga_ls8c_ard_3-2-1_095077_2023-10-11_final
2023-10-13 11:15:29	ga_ls8c_ard_3-2-1_109078_2023-10-13_final
2023-10-13 11:15:53	ga_ls8c_ard_3-2-1_109079_2023-10-13_final
2023-10-14 10:20:40	ga_ls8c_ard_3-2-1_100080_2023-10-14_final
2023-10-15 11:02:44	ga_ls8c_ard_3-2-1_107077_2023-10-15_final
2023-10-17 10:50:45	ga_ls8c_ard_3-2-1_105078_2023-10-17_final
2023-10-20 11:20:02	ga_ls8c_ard_3-2-1_110074_2023-10-20_final
2023-10-22 09:30:25	ga_ls8c_ard_3-2-1_092078_2023-10-22_final
2023-10-22 11:11:18	ga_ls8c_ard_3-2-1_108083_2023-10-22_final
2023-10-23 10:10:54	ga_ls8c_ard_3-2-1_099071_2023-10-23_final
2023-10-23 10:16:05	ga_ls8c_ard_3-2-1_099084_2023-10-23_final
2023-10-24 09:17:41	ga_ls8c_ard_3-2-1_090077_2023-10-23_final
2023-10-29 11:15:32	ga_ls8c_ard_3-2-1_109078_2023-10-29_final
2023-10-30 10:20:43	ga_ls8c_ard_3-2-1_100080_2023-10-30_final
2023-10-30 10:21:55	ga_ls8c_ard_3-2-1_100083_2023-10-30_final
2023-11-02 10:47:13	ga_ls8c_ard_3-2-1_105069_2023-11-02_final
2023-11-03 11:34:28	ga_ls8c_ard_3-2-1_112079_2023-11-03_final
2023-11-04 10:40:02	ga_ls8c_ard_3-2-1_103082_2023-11-04_final
2023-11-05 09:42:25	ga_ls8c_ard_3-2-1_094077_2023-11-05_final
2023-11-05 09:42:49	ga_ls8c_ard_3-2-1_094078_2023-11-05_final
2023-11-05 11:21:18	ga_ls8c_ard_3-2-1_110077_2023-11-05_final
2023-11-07 09:34:01	ga_ls8c_ard_3-2-1_092087_2023-11-07_final
2023-11-07 11:09:18	ga_ls8c_ard_3-2-1_108078_2023-11-07_final
2023-11-07 11:09:42	ga_ls8c_ard_3-2-1_108079_2023-11-07_final
2023-11-07 11:11:18	ga_ls8c_ard_3-2-1_108083_2023-11-07_final
2023-11-08 10:14:28	ga_ls8c_ard_3-2-1_099080_2023-11-08_final
2023-11-12 09:51:21	ga_ls8c_ard_3-2-1_095084_2023-11-12_final
2023-11-13 10:31:02	ga_ls8c_ard_3-2-1_102075_2023-11-13_final
2023-11-14 09:37:01	ga_ls8c_ard_3-2-1_093079_2023-11-14_final
2023-11-14 11:15:30	ga_ls8c_ard_3-2-1_109078_2023-11-14_final
2023-11-18 10:48:49	ga_ls8c_ard_3-2-1_105073_2023-11-18_final
2023-11-18 10:49:37	ga_ls8c_ard_3-2-1_105075_2023-11-18_final
2023-11-18 10:52:49	ga_ls8c_ard_3-2-1_105083_2023-11-18_final
2023-11-19 11:33:18	ga_ls8c_ard_3-2-1_112076_2023-11-19_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