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
2016-02-14 09:27:13	ga_ls8c_ard_3-1-0_091086_2016-02-13_final
2019-03-10 09:23:18	ga_ls8c_ard_3-1-0_091077_2019-03-09_final
2019-03-10 09:24:06	ga_ls8c_ard_3-1-0_091079_2019-03-09_final
2019-03-17 11:08:44	ga_ls8c_ard_3-1-0_108078_2019-03-17_final
2019-03-17 11:09:32	ga_ls8c_ard_3-1-0_108080_2019-03-17_final
2019-03-28 10:48:10	ga_ls8c_ard_3-1-0_105073_2019-03-28_final
2019-04-07 09:47:07	ga_ls8c_ard_3-1-0_095075_2019-04-07_final
2019-04-07 09:51:06	ga_ls8c_ard_3-1-0_095085_2019-04-07_final
2019-04-18 11:08:35	ga_ls8c_ard_3-1-0_108078_2019-04-18_final
2019-06-14 09:23:06	ga_ls8c_ard_3-1-0_091076_2019-06-13_final
2019-06-14 09:25:53	ga_ls8c_ard_3-1-0_091083_2019-06-13_final
2019-07-07 11:06:16	ga_ls8c_ard_3-1-0_108071_2019-07-07_final
2019-07-18 10:46:10	ga_ls8c_ard_3-1-0_105067_2019-07-18_final
2019-07-23 11:09:08	ga_ls8c_ard_3-1-0_108078_2019-07-23_final
2019-08-17 09:23:49	ga_ls8c_ard_3-1-0_091077_2019-08-16_final
2019-09-02 09:25:05	ga_ls8c_ard_3-1-0_091080_2019-09-01_final
2019-09-04 10:52:48	ga_ls8c_ard_3-1-0_105083_2019-09-04_final
2019-09-14 09:47:28	ga_ls8c_ard_3-1-0_095074_2019-09-14_final
2019-09-14 09:48:16	ga_ls8c_ard_3-1-0_095076_2019-09-14_final
2019-10-20 09:22:05	ga_ls8c_ard_3-1-0_091072_2019-10-19_final
2019-10-22 10:50:36	ga_ls8c_ard_3-1-0_105077_2019-10-22_final
2019-11-05 09:24:51	ga_ls8c_ard_3-1-0_091079_2019-11-04_final
2019-11-05 09:28:27	ga_ls8c_ard_3-1-0_091088_2019-11-04_final
2019-11-12 11:08:18	ga_ls8c_ard_3-1-0_108075_2019-11-12_final
2019-11-12 11:10:42	ga_ls8c_ard_3-1-0_108081_2019-11-12_final
2019-11-12 11:11:06	ga_ls8c_ard_3-1-0_108082_2019-11-12_final
2019-11-17 09:47:56	ga_ls8c_ard_3-1-0_095075_2019-11-17_final
2019-11-17 09:48:20	ga_ls8c_ard_3-1-0_095076_2019-11-17_final
2019-11-21 09:25:36	ga_ls8c_ard_3-1-0_091081_2019-11-20_final
2019-11-21 09:25:59	ga_ls8c_ard_3-1-0_091082_2019-11-20_final
2019-11-21 09:27:59	ga_ls8c_ard_3-1-0_091087_2019-11-20_final
2019-11-23 10:51:43	ga_ls8c_ard_3-1-0_105080_2019-11-23_final
2019-11-24 09:53:18	ga_ls8c_ard_3-1-0_096073_2019-11-24_final
2019-11-24 09:53:42	ga_ls8c_ard_3-1-0_096074_2019-11-24_final
2019-11-24 09:55:18	ga_ls8c_ard_3-1-0_096078_2019-11-24_final
2019-11-24 09:55:42	ga_ls8c_ard_3-1-0_096079_2019-11-24_final
2019-11-24 09:56:06	ga_ls8c_ard_3-1-0_096080_2019-11-24_final
2019-12-10 09:54:05	ga_ls8c_ard_3-1-0_096075_2019-12-10_final
2019-12-23 09:25:32	ga_ls8c_ard_3-1-0_091081_2019-12-22_final
2019-12-23 09:27:56	ga_ls8c_ard_3-1-0_091087_2019-12-22_final
2019-12-30 11:09:22	ga_ls8c_ard_3-1-0_108078_2019-12-30_final
2019-12-30 11:10:10	ga_ls8c_ard_3-1-0_108080_2019-12-30_final
2020-01-04 09:51:48	ga_ls8c_ard_3-1-0_095085_2020-01-04_final
2020-01-08 09:23:29	ga_ls8c_ard_3-1-0_091076_2020-01-07_final
2020-01-15 11:10:07	ga_ls8c_ard_3-1-0_108080_2020-01-15_final
2020-02-21 09:47:37	ga_ls8c_ard_3-1-0_095075_2020-02-21_final
2020-02-27 10:50:11	ga_ls8c_ard_3-1-0_105077_2020-02-27_final
2020-02-28 09:52:09	ga_ls8c_ard_3-1-0_096071_2020-02-28_final
2020-03-03 11:08:17	ga_ls8c_ard_3-1-0_108076_2020-03-03_final
2020-03-03 11:09:05	ga_ls8c_ard_3-1-0_108078_2020-03-03_final
2020-03-12 09:28:21	ga_ls8c_ard_3-1-0_091089_2020-03-11_final
2020-03-30 10:47:55	ga_ls8c_ard_3-1-0_105072_2020-03-30_final
2020-03-30 10:51:07	ga_ls8c_ard_3-1-0_105080_2020-03-30_final
2020-04-04 11:06:25	ga_ls8c_ard_3-1-0_108072_2020-04-04_final
2020-04-13 09:22:06	ga_ls8c_ard_3-1-0_091074_2020-04-12_final
2020-04-20 11:06:19	ga_ls8c_ard_3-1-0_108072_2020-04-20_final
2020-04-25 09:46:19	ga_ls8c_ard_3-1-0_095073_2020-04-25_final
2020-05-01 10:50:04	ga_ls8c_ard_3-1-0_105078_2020-05-01_final
2022-03-29 10:40:58	ga_ls8c_ard_3-2-1_104070_2022-03-29_final
2022-03-30 09:47:20	ga_ls8c_ard_3-2-1_095075_2022-03-30_final
2022-03-31 10:32:36	ga_ls8c_ard_3-2-1_102080_2022-03-31_final
2022-04-01 09:38:10	ga_ls8c_ard_3-2-1_093083_2022-04-01_final
2022-04-04 10:06:41	ga_ls8c_ard_3-2-1_098077_2022-04-04_final
2022-04-08 11:17:42	ga_ls8c_ard_3-2-1_110069_2022-04-08_final
2022-04-16 10:30:18	ga_ls8c_ard_3-2-1_102074_2022-04-16_final
2022-04-19 11:02:23	ga_ls8c_ard_3-2-1_107077_2022-04-19_final
2022-04-22 09:56:23	ga_ls8c_ard_3-2-1_096082_2022-04-22_final
2022-04-23 10:37:39	ga_ls8c_ard_3-2-1_103077_2022-04-23_final
2022-04-23 10:38:50	ga_ls8c_ard_3-2-1_103080_2022-04-23_final
2022-04-26 11:11:19	ga_ls8c_ard_3-2-1_108084_2022-04-26_final
2022-04-29 09:58:55	ga_ls8c_ard_3-2-1_097073_2022-04-29_final
2022-05-02 10:28:16	ga_ls8c_ard_3-2-1_102069_2022-05-02_final
2022-05-03 11:13:08	ga_ls8c_ard_3-2-1_109073_2022-05-03_final
2022-05-08 09:52:27	ga_ls8c_ard_3-2-1_096072_2022-05-08_final
2022-05-09 10:34:32	ga_ls8c_ard_3-2-1_103069_2022-05-09_final
2022-05-09 10:35:44	ga_ls8c_ard_3-2-1_103072_2022-05-09_final
2022-05-10 11:20:36	ga_ls8c_ard_3-2-1_110076_2022-05-10_final
2022-05-12 11:06:15	ga_ls8c_ard_3-2-1_108071_2022-05-12_final
2022-05-14 10:54:18	ga_ls8c_ard_3-2-1_106072_2022-05-14_final
2022-05-14 10:57:30	ga_ls8c_ard_3-2-1_106080_2022-05-14_final
2022-05-14 10:58:18	ga_ls8c_ard_3-2-1_106082_2022-05-14_final
2022-05-15 09:59:53	ga_ls8c_ard_3-2-1_097075_2022-05-15_final
2022-05-17 09:51:32	ga_ls8c_ard_3-2-1_095085_2022-05-17_final
2022-05-19 09:39:10	ga_ls8c_ard_3-2-1_093085_2022-05-19_final
2022-05-24 09:57:43	ga_ls8c_ard_3-2-1_096085_2022-05-24_final
2022-05-24 11:32:12	ga_ls8c_ard_3-2-1_112074_2022-05-24_final
2022-05-26 09:41:45	ga_ls8c_ard_3-2-1_094076_2022-05-26_final
2022-05-31 11:42:01	ga_ls8c_ard_3-2-1_113083_2022-05-31_final
2022-06-01 10:40:49	ga_ls8c_ard_3-2-1_104069_2022-06-01_final
2022-06-02 09:47:12	ga_ls8c_ard_3-2-1_095074_2022-06-02_final
2022-06-04 09:35:17	ga_ls8c_ard_3-2-1_093075_2022-06-04_final
2022-06-04 11:14:58	ga_ls8c_ard_3-2-1_109077_2022-06-04_final
2022-06-04 11:16:57	ga_ls8c_ard_3-2-1_109082_2022-06-04_final
2022-06-08 10:48:18	ga_ls8c_ard_3-2-1_105072_2022-06-08_final
2022-06-08 10:48:42	ga_ls8c_ard_3-2-1_105073_2022-06-08_final
2022-06-13 11:09:41	ga_ls8c_ard_3-2-1_108079_2022-06-13_final
2022-06-15 10:54:09	ga_ls8c_ard_3-2-1_106071_2022-06-15_final
2022-06-16 11:41:49	ga_ls8c_ard_3-2-1_113082_2022-06-16_final
2022-06-18 11:29:04	ga_ls8c_ard_3-2-1_111081_2022-06-18_final
2022-06-19 10:28:40	ga_ls8c_ard_3-2-1_102069_2022-06-19_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