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
2023-02-04 11:34:14	ga_ls8c_ard_3-2-1_112078_2023-02-04_final
2023-03-15 10:00:43	ga_ls8c_ard_3-2-1_097077_2023-03-15_final
2023-03-17 09:49:08	ga_ls8c_ard_3-2-1_095079_2023-03-17_final
2023-03-19 09:35:57	ga_ls8c_ard_3-2-1_093077_2023-03-19_final
2023-04-03 10:32:36	ga_ls8c_ard_3-2-1_102080_2023-04-03_final
2023-04-20 09:37:32	ga_ls8c_ard_3-2-1_093082_2023-04-20_final
2023-04-24 10:49:43	ga_ls8c_ard_3-2-1_105077_2023-04-24_final
2023-04-26 10:36:33	ga_ls8c_ard_3-2-1_103075_2023-04-26_final
2023-04-27 09:41:20	ga_ls8c_ard_3-2-1_094076_2023-04-27_final
2023-04-27 09:42:55	ga_ls8c_ard_3-2-1_094080_2023-04-27_final
2023-04-27 11:21:48	ga_ls8c_ard_3-2-1_110080_2023-04-27_final
2023-04-28 10:26:11	ga_ls8c_ard_3-2-1_101080_2023-04-28_final
2023-04-28 10:26:35	ga_ls8c_ard_3-2-1_101081_2023-04-28_final
2023-04-29 11:09:26	ga_ls8c_ard_3-2-1_108080_2023-04-29_final
2023-05-03 10:43:28	ga_ls8c_ard_3-2-1_104077_2023-05-03_final
2023-05-03 10:43:52	ga_ls8c_ard_3-2-1_104078_2023-05-03_final
2023-05-04 11:27:07	ga_ls8c_ard_3-2-1_111078_2023-05-04_final
2023-05-06 11:14:44	ga_ls8c_ard_3-2-1_109078_2023-05-06_final
2023-05-08 11:02:44	ga_ls8c_ard_3-2-1_107079_2023-05-08_final
2023-05-09 10:08:18	ga_ls8c_ard_3-2-1_098082_2023-05-09_final
2023-05-19 10:42:53	ga_ls8c_ard_3-2-1_104076_2023-05-19_final
2023-05-20 11:28:09	ga_ls8c_ard_3-2-1_111081_2023-05-20_final
2023-05-21 10:31:21	ga_ls8c_ard_3-2-1_102078_2023-05-21_final
2023-05-22 11:14:37	ga_ls8c_ard_3-2-1_109078_2023-05-22_final
2023-06-03 10:02:05	ga_ls8c_ard_3-2-1_097082_2023-06-03_final
2023-06-03 11:39:22	ga_ls8c_ard_3-2-1_113078_2023-06-03_final
2023-06-03 11:39:46	ga_ls8c_ard_3-2-1_113079_2023-06-03_final
2023-06-04 10:44:10	ga_ls8c_ard_3-2-1_104079_2023-06-04_final
2023-06-04 10:44:57	ga_ls8c_ard_3-2-1_104081_2023-06-04_final
2023-06-05 09:49:21	ga_ls8c_ard_3-2-1_095081_2023-06-05_final
2023-06-06 10:30:38	ga_ls8c_ard_3-2-1_102076_2023-06-06_final
2023-06-09 11:02:46	ga_ls8c_ard_3-2-1_107079_2023-06-09_final
2023-06-12 09:53:13	ga_ls8c_ard_3-2-1_096075_2023-06-12_final
2023-06-12 11:32:06	ga_ls8c_ard_3-2-1_112075_2023-06-12_final
2023-06-19 11:39:31	ga_ls8c_ard_3-2-1_113078_2023-06-19_final
2023-06-23 09:35:54	ga_ls8c_ard_3-2-1_093078_2023-06-23_final
2023-06-23 09:36:18	ga_ls8c_ard_3-2-1_093079_2023-06-23_final
2023-06-30 09:41:49	ga_ls8c_ard_3-2-1_094077_2023-06-30_final
2023-07-02 09:29:53	ga_ls8c_ard_3-2-1_092078_2023-07-01_final
2023-07-03 10:15:57	ga_ls8c_ard_3-2-1_099085_2023-07-03_final
2023-07-04 10:56:25	ga_ls8c_ard_3-2-1_106078_2023-07-04_final
2023-07-06 10:44:53	ga_ls8c_ard_3-2-1_104080_2023-07-06_final
2023-07-07 11:28:33	ga_ls8c_ard_3-2-1_111081_2023-07-07_final
2023-07-11 11:05:03	ga_ls8c_ard_3-2-1_107084_2023-07-11_final
2023-07-14 09:55:05	ga_ls8c_ard_3-2-1_096079_2023-07-14_final
2023-07-14 09:55:29	ga_ls8c_ard_3-2-1_096080_2023-07-14_final
2023-07-21 11:40:08	ga_ls8c_ard_3-2-1_113079_2023-07-21_final
2023-07-23 11:27:25	ga_ls8c_ard_3-2-1_111078_2023-07-23_final
2023-08-07 10:44:17	ga_ls8c_ard_3-2-1_104078_2023-08-07_final
2023-08-09 10:31:55	ga_ls8c_ard_3-2-1_102078_2023-08-09_final
2023-08-17 11:21:03	ga_ls8c_ard_3-2-1_110077_2023-08-17_final
2023-08-17 11:21:26	ga_ls8c_ard_3-2-1_110078_2023-08-17_final
2023-08-19 09:30:37	ga_ls8c_ard_3-2-1_092079_2023-08-19_final
2023-08-19 11:08:18	ga_ls8c_ard_3-2-1_108076_2023-08-19_final
2023-08-19 11:10:42	ga_ls8c_ard_3-2-1_108082_2023-08-19_final
2023-08-23 10:43:37	ga_ls8c_ard_3-2-1_104076_2023-08-23_final
2023-08-26 09:36:26	ga_ls8c_ard_3-2-1_093078_2023-08-26_final
2023-08-28 11:02:34	ga_ls8c_ard_3-2-1_107077_2023-08-28_final
2023-08-30 10:51:24	ga_ls8c_ard_3-2-1_105080_2023-08-30_final
2023-08-31 09:53:47	ga_ls8c_ard_3-2-1_096075_2023-08-31_final
2023-08-31 09:55:22	ga_ls8c_ard_3-2-1_096079_2023-08-31_final
2023-08-31 11:33:52	ga_ls8c_ard_3-2-1_112078_2023-08-31_final
2023-09-01 10:37:02	ga_ls8c_ard_3-2-1_103075_2023-09-01_final
2023-09-04 11:10:43	ga_ls8c_ard_3-2-1_108082_2023-09-04_final
2023-09-08 10:43:36	ga_ls8c_ard_3-2-1_104076_2023-09-08_final
2023-09-08 10:44:00	ga_ls8c_ard_3-2-1_104077_2023-09-08_final
2023-09-09 09:49:35	ga_ls8c_ard_3-2-1_095080_2023-09-09_final
2023-09-09 11:27:17	ga_ls8c_ard_3-2-1_111077_2023-09-09_final
2023-09-10 10:31:16	ga_ls8c_ard_3-2-1_102076_2023-09-10_final
2023-09-14 10:08:59	ga_ls8c_ard_3-2-1_098082_2023-09-14_final
2023-09-18 11:21:34	ga_ls8c_ard_3-2-1_110078_2023-09-18_final
2023-09-19 10:26:45	ga_ls8c_ard_3-2-1_101080_2023-09-19_final
2023-09-25 09:48:06	ga_ls8c_ard_3-2-1_095076_2023-09-25_final
2023-10-02 09:53:54	ga_ls8c_ard_3-2-1_096075_2023-10-02_final
2023-10-02 09:55:30	ga_ls8c_ard_3-2-1_096079_2023-10-02_final
2023-10-04 09:42:20	ga_ls8c_ard_3-2-1_094077_2023-10-04_final
2023-10-08 10:56:31	ga_ls8c_ard_3-2-1_106077_2023-10-08_final
2023-10-09 11:39:24	ga_ls8c_ard_3-2-1_113076_2023-10-09_final
2023-10-11 11:27:27	ga_ls8c_ard_3-2-1_111077_2023-10-11_final
2023-10-14 11:57:57	ga_ls8c_ard_3-2-1_116076_2023-10-14_final
2023-10-15 11:02:44	ga_ls8c_ard_3-2-1_107077_2023-10-15_final
2023-10-20 09:42:21	ga_ls8c_ard_3-2-1_094077_2023-10-20_final
2023-10-20 11:21:38	ga_ls8c_ard_3-2-1_110078_2023-10-20_final
2023-10-22 11:09:18	ga_ls8c_ard_3-2-1_108078_2023-10-22_final
2023-10-27 09:48:36	ga_ls8c_ard_3-2-1_095077_2023-10-27_final
2023-10-27 11:27:29	ga_ls8c_ard_3-2-1_111077_2023-10-27_final
2023-10-29 09:37:27	ga_ls8c_ard_3-2-1_093080_2023-10-29_final
2023-10-29 09:38:15	ga_ls8c_ard_3-2-1_093082_2023-10-29_final
2023-10-29 11:16:20	ga_ls8c_ard_3-2-1_109080_2023-10-29_final
2023-11-01 10:09:09	ga_ls8c_ard_3-2-1_098082_2023-11-01_final
2023-11-03 11:34:28	ga_ls8c_ard_3-2-1_112079_2023-11-03_final
2023-11-12 11:27:50	ga_ls8c_ard_3-2-1_111078_2023-11-12_final
2023-11-14 11:15:54	ga_ls8c_ard_3-2-1_109079_2023-11-14_final
2023-11-19 11:34:29	ga_ls8c_ard_3-2-1_112079_2023-11-19_final
2023-11-21 09:42:28	ga_ls8c_ard_3-2-1_094077_2023-11-21_final
2023-11-21 11:21:45	ga_ls8c_ard_3-2-1_110078_2023-11-21_final
2023-11-23 09:35:18	ga_ls8c_ard_3-2-1_092090_2023-11-23_final
2023-11-28 09:49:26	ga_ls8c_ard_3-2-1_095079_2023-11-28_nrt
2023-11-28 11:28:43	ga_ls8c_ard_3-2-1_111080_2023-11-28_nrt
2023-12-05 09:53:54	ga_ls8c_ard_3-2-1_096075_2023-12-05_nrt

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