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
2013-07-21 10:25:26	ga_ls8c_ard_3-1-0_101072_2013-07-21_final
2015-04-22 10:22:50	ga_ls8c_ard_3-1-0_101072_2015-04-22_final
2015-07-11 10:23:00	ga_ls8c_ard_3-1-0_101072_2015-07-11_final
2016-07-29 10:23:30	ga_ls8c_ard_3-1-0_101072_2016-07-29_final
2017-05-13 10:22:53	ga_ls8c_ard_3-1-0_101072_2017-05-13_final
2017-06-30 10:23:15	ga_ls8c_ard_3-1-0_101072_2017-06-30_final
2019-03-07 10:30:54	ga_ls8c_ard_3-1-0_102076_2019-03-07_final
2019-03-07 10:31:42	ga_ls8c_ard_3-1-0_102078_2019-03-07_final
2019-03-12 10:50:37	ga_ls8c_ard_3-1-0_105079_2019-03-12_final
2019-03-16 10:26:16	ga_ls8c_ard_3-1-0_101080_2019-03-16_final
2019-03-17 11:08:44	ga_ls8c_ard_3-1-0_108078_2019-03-17_final
2019-03-22 09:47:35	ga_ls8c_ard_3-1-0_095076_2019-03-22_final
2019-03-29 11:33:49	ga_ls8c_ard_3-1-0_112079_2019-03-29_final
2019-04-08 10:31:10	ga_ls8c_ard_3-1-0_102077_2019-04-08_final
2019-04-08 10:31:58	ga_ls8c_ard_3-1-0_102079_2019-04-08_final
2019-04-14 09:53:15	ga_ls8c_ard_3-1-0_096075_2019-04-14_final
2019-04-14 09:53:39	ga_ls8c_ard_3-1-0_096076_2019-04-14_final
2019-06-17 11:34:30	ga_ls8c_ard_3-1-0_112080_2019-06-17_final
2019-06-26 11:27:10	ga_ls8c_ard_3-1-0_111077_2019-06-26_final
2019-06-29 11:58:05	ga_ls8c_ard_3-1-0_116077_2019-06-29_final
2019-07-03 11:32:35	ga_ls8c_ard_3-1-0_112075_2019-07-03_final
2019-07-12 09:47:56	ga_ls8c_ard_3-1-0_095076_2019-07-12_final
2019-07-16 09:24:01	ga_ls8c_ard_3-1-0_091078_2019-07-15_final
2019-07-18 10:50:09	ga_ls8c_ard_3-1-0_105077_2019-07-18_final
2019-07-28 09:48:01	ga_ls8c_ard_3-1-0_095076_2019-07-28_final
2019-08-08 11:10:02	ga_ls8c_ard_3-1-0_108080_2019-08-08_final
2019-08-13 11:25:01	ga_ls8c_ard_3-1-0_111071_2019-08-13_final
2019-08-14 10:32:59	ga_ls8c_ard_3-1-0_102080_2019-08-14_final
2019-08-19 10:50:45	ga_ls8c_ard_3-1-0_105078_2019-08-19_final
2019-08-20 11:34:49	ga_ls8c_ard_3-1-0_112080_2019-08-20_final
2019-08-29 09:48:11	ga_ls8c_ard_3-1-0_095076_2019-08-29_final
2019-08-30 10:33:03	ga_ls8c_ard_3-1-0_102080_2019-08-30_final
2019-09-05 09:53:11	ga_ls8c_ard_3-1-0_096073_2019-09-05_final
2019-09-05 09:55:35	ga_ls8c_ard_3-1-0_096079_2019-09-05_final
2019-09-05 11:32:52	ga_ls8c_ard_3-1-0_112075_2019-09-05_final
2019-09-14 09:48:16	ga_ls8c_ard_3-1-0_095076_2019-09-14_final
2019-09-20 10:51:42	ga_ls8c_ard_3-1-0_105080_2019-09-20_final
2019-10-01 10:32:25	ga_ls8c_ard_3-1-0_102078_2019-10-01_final
2019-10-06 10:51:22	ga_ls8c_ard_3-1-0_105079_2019-10-06_final
2019-10-10 10:27:03	ga_ls8c_ard_3-1-0_101080_2019-10-10_final
2019-10-16 11:27:40	ga_ls8c_ard_3-1-0_111077_2019-10-16_final
2019-10-16 11:28:52	ga_ls8c_ard_3-1-0_111080_2019-10-16_final
2019-10-17 10:32:27	ga_ls8c_ard_3-1-0_102078_2019-10-17_final
2019-11-04 11:58:34	ga_ls8c_ard_3-1-0_116077_2019-11-04_final
2019-11-11 10:27:02	ga_ls8c_ard_3-1-0_101080_2019-11-11_final
2019-11-17 09:48:44	ga_ls8c_ard_3-1-0_095077_2019-11-17_final
2019-11-17 11:28:25	ga_ls8c_ard_3-1-0_111079_2019-11-17_final
2019-11-23 10:50:55	ga_ls8c_ard_3-1-0_105078_2019-11-23_final
2019-12-03 09:48:43	ga_ls8c_ard_3-1-0_095077_2019-12-03_final
2019-12-10 09:54:05	ga_ls8c_ard_3-1-0_096075_2019-12-10_final
2020-01-04 09:48:36	ga_ls8c_ard_3-1-0_095077_2020-01-04_final
2020-01-04 09:49:24	ga_ls8c_ard_3-1-0_095079_2020-01-04_final
2020-01-31 11:09:14	ga_ls8c_ard_3-1-0_108078_2020-01-31_final
2020-02-15 10:26:43	ga_ls8c_ard_3-1-0_101080_2020-02-15_final
2020-02-28 09:54:09	ga_ls8c_ard_3-1-0_096076_2020-02-28_final
2020-02-28 11:33:02	ga_ls8c_ard_3-1-0_112076_2020-02-28_final
2020-03-09 10:31:58	ga_ls8c_ard_3-1-0_102078_2020-03-09_final
2020-03-15 09:54:26	ga_ls8c_ard_3-1-0_096077_2020-03-15_final
2020-03-24 11:27:28	ga_ls8c_ard_3-1-0_111078_2020-03-24_final
2020-03-31 09:53:29	ga_ls8c_ard_3-1-0_096075_2020-03-31_final
2020-04-04 11:06:25	ga_ls8c_ard_3-1-0_108072_2020-04-04_final
2020-04-09 11:26:55	ga_ls8c_ard_3-1-0_111077_2020-04-09_final
2020-04-16 09:54:34	ga_ls8c_ard_3-1-0_096078_2020-04-16_final
2020-04-26 10:31:34	ga_ls8c_ard_3-1-0_102078_2020-04-26_final
2020-05-06 11:06:10	ga_ls8c_ard_3-1-0_108072_2020-05-06_final
2022-03-30 09:49:20	ga_ls8c_ard_3-2-1_095080_2022-03-30_final
2022-03-31 10:31:48	ga_ls8c_ard_3-2-1_102078_2022-03-31_final
2022-04-01 09:36:34	ga_ls8c_ard_3-2-1_093079_2022-04-01_final
2022-04-06 09:55:09	ga_ls8c_ard_3-2-1_096079_2022-04-06_final
2022-04-06 11:32:26	ga_ls8c_ard_3-2-1_112075_2022-04-06_final
2022-04-07 10:36:26	ga_ls8c_ard_3-2-1_103074_2022-04-07_final
2022-04-07 10:37:13	ga_ls8c_ard_3-2-1_103076_2022-04-07_final
2022-04-08 09:43:12	ga_ls8c_ard_3-2-1_094080_2022-04-08_final
2022-04-10 11:06:33	ga_ls8c_ard_3-2-1_108072_2022-04-10_final
2022-04-11 10:11:44	ga_ls8c_ard_3-2-1_099074_2022-04-11_final
2022-04-13 11:38:41	ga_ls8c_ard_3-2-1_113075_2022-04-13_final
2022-04-14 10:43:27	ga_ls8c_ard_3-2-1_104076_2022-04-14_final
2022-04-17 09:36:40	ga_ls8c_ard_3-2-1_093079_2022-04-17_final
2022-04-19 11:04:23	ga_ls8c_ard_3-2-1_107082_2022-04-19_final
2022-04-20 10:05:58	ga_ls8c_ard_3-2-1_098075_2022-04-20_final
2022-04-22 09:55:11	ga_ls8c_ard_3-2-1_096079_2022-04-22_final
2022-04-23 10:38:27	ga_ls8c_ard_3-2-1_103079_2022-04-23_final
2022-04-29 09:59:43	ga_ls8c_ard_3-2-1_097075_2022-04-29_final
2022-04-30 10:42:59	ga_ls8c_ard_3-2-1_104075_2022-04-30_final
2022-04-30 10:43:23	ga_ls8c_ard_3-2-1_104076_2022-04-30_final
2022-05-03 11:15:08	ga_ls8c_ard_3-2-1_109078_2022-05-03_final
2022-05-07 10:50:28	ga_ls8c_ard_3-2-1_105078_2022-05-07_final
2022-05-08 09:55:15	ga_ls8c_ard_3-2-1_096079_2022-05-08_final
2022-05-08 09:55:39	ga_ls8c_ard_3-2-1_096080_2022-05-08_final
2022-05-10 11:21:23	ga_ls8c_ard_3-2-1_110078_2022-05-10_final
2022-05-12 11:06:39	ga_ls8c_ard_3-2-1_108072_2022-05-12_final
2022-05-15 10:00:41	ga_ls8c_ard_3-2-1_097077_2022-05-15_final
2022-05-15 10:02:41	ga_ls8c_ard_3-2-1_097082_2022-05-15_final
2022-05-16 10:43:57	ga_ls8c_ard_3-2-1_104077_2022-05-16_final
2022-05-16 10:44:45	ga_ls8c_ard_3-2-1_104079_2022-05-16_final
2022-05-16 10:45:09	ga_ls8c_ard_3-2-1_104080_2022-05-16_final
2022-05-24 11:33:48	ga_ls8c_ard_3-2-1_112078_2022-05-24_final
2022-06-02 09:49:12	ga_ls8c_ard_3-2-1_095079_2022-06-02_final
2022-06-02 11:27:17	ga_ls8c_ard_3-2-1_111077_2022-06-02_final
2022-06-04 11:15:45	ga_ls8c_ard_3-2-1_109079_2022-06-04_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