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
2013-08-06 10:25:30	ga_ls8c_ard_3-1-0_101072_2013-08-06_final
2015-05-24 10:22:33	ga_ls8c_ard_3-1-0_101072_2015-05-24_final
2015-06-09 10:22:43	ga_ls8c_ard_3-1-0_101072_2015-06-09_final
2016-07-29 10:23:30	ga_ls8c_ard_3-1-0_101072_2016-07-29_final
2016-08-09 10:08:58	ga_ls8c_ard_3-1-0_098082_2016-08-09_final
2017-05-29 10:23:04	ga_ls8c_ard_3-1-0_101072_2017-05-29_final
2018-02-25 10:23:13	ga_ls8c_ard_3-1-0_101072_2018-02-25_final
2019-03-12 10:49:49	ga_ls8c_ard_3-1-0_105077_2019-03-12_final
2019-03-13 09:53:23	ga_ls8c_ard_3-1-0_096075_2019-03-13_final
2019-03-25 11:56:57	ga_ls8c_ard_3-1-0_116075_2019-03-25_final
2019-03-25 11:57:21	ga_ls8c_ard_3-1-0_116076_2019-03-25_final
2019-03-25 11:57:45	ga_ls8c_ard_3-1-0_116077_2019-03-25_final
2019-03-28 10:50:33	ga_ls8c_ard_3-1-0_105079_2019-03-28_final
2019-03-28 10:50:57	ga_ls8c_ard_3-1-0_105080_2019-03-28_final
2019-03-29 09:56:32	ga_ls8c_ard_3-1-0_096083_2019-03-29_final
2019-04-01 10:24:37	ga_ls8c_ard_3-1-0_101076_2019-04-01_final
2019-04-08 10:32:22	ga_ls8c_ard_3-1-0_102080_2019-04-08_final
2019-04-11 09:25:10	ga_ls8c_ard_3-1-0_091082_2019-04-10_final
2019-04-14 09:52:03	ga_ls8c_ard_3-1-0_096072_2019-04-14_final
2019-04-14 09:54:03	ga_ls8c_ard_3-1-0_096077_2019-04-14_final
2019-06-14 09:24:18	ga_ls8c_ard_3-1-0_091079_2019-06-13_final
2019-06-16 10:47:14	ga_ls8c_ard_3-1-0_105070_2019-06-16_final
2019-06-16 10:51:38	ga_ls8c_ard_3-1-0_105081_2019-06-16_final
2019-07-02 10:50:06	ga_ls8c_ard_3-1-0_105077_2019-07-02_final
2019-07-02 10:51:42	ga_ls8c_ard_3-1-0_105081_2019-07-02_final
2019-07-06 10:26:12	ga_ls8c_ard_3-1-0_101079_2019-07-06_final
2019-07-29 10:31:41	ga_ls8c_ard_3-1-0_102077_2019-07-29_final
2019-08-18 10:05:29	ga_ls8c_ard_3-1-0_098073_2019-08-18_final
2019-08-30 10:33:03	ga_ls8c_ard_3-1-0_102080_2019-08-30_final
2019-09-04 10:47:37	ga_ls8c_ard_3-1-0_105070_2019-09-04_final
2019-09-04 10:51:12	ga_ls8c_ard_3-1-0_105079_2019-09-04_final
2019-09-04 10:51:36	ga_ls8c_ard_3-1-0_105080_2019-09-04_final
2019-09-15 10:32:44	ga_ls8c_ard_3-1-0_102079_2019-09-15_final
2019-09-18 09:24:22	ga_ls8c_ard_3-1-0_091078_2019-09-17_final
2019-09-19 10:05:38	ga_ls8c_ard_3-1-0_098073_2019-09-19_final
2019-09-20 10:51:42	ga_ls8c_ard_3-1-0_105080_2019-09-20_final
2019-09-21 11:34:58	ga_ls8c_ard_3-1-0_112080_2019-09-21_final
2019-09-24 10:27:00	ga_ls8c_ard_3-1-0_101080_2019-09-24_final
2019-10-01 10:33:13	ga_ls8c_ard_3-1-0_102080_2019-10-01_final
2019-10-06 10:51:22	ga_ls8c_ard_3-1-0_105079_2019-10-06_final
2019-10-06 10:52:58	ga_ls8c_ard_3-1-0_105083_2019-10-06_final
2019-10-22 10:51:24	ga_ls8c_ard_3-1-0_105079_2019-10-22_final
2019-10-23 09:55:46	ga_ls8c_ard_3-1-0_096079_2019-10-23_final
2019-11-01 09:49:11	ga_ls8c_ard_3-1-0_095078_2019-11-01_final
2019-11-08 09:55:45	ga_ls8c_ard_3-1-0_096079_2019-11-08_final
2019-11-11 10:23:03	ga_ls8c_ard_3-1-0_101070_2019-11-11_final
2019-11-21 09:25:59	ga_ls8c_ard_3-1-0_091082_2019-11-20_final
2019-11-24 09:55:42	ga_ls8c_ard_3-1-0_096079_2019-11-24_final
2019-11-24 11:32:59	ga_ls8c_ard_3-1-0_112075_2019-11-24_final
2019-12-29 10:26:31	ga_ls8c_ard_3-1-0_101079_2019-12-29_final
2020-01-04 09:49:48	ga_ls8c_ard_3-1-0_095080_2020-01-04_final
2020-01-30 10:26:23	ga_ls8c_ard_3-1-0_101079_2020-01-30_final
2020-02-21 09:51:36	ga_ls8c_ard_3-1-0_095085_2020-02-21_final
2020-02-22 10:31:16	ga_ls8c_ard_3-1-0_102076_2020-02-22_final
2020-02-28 09:53:45	ga_ls8c_ard_3-1-0_096075_2020-02-28_final
2020-02-28 11:34:38	ga_ls8c_ard_3-1-0_112080_2020-02-28_final
2020-03-15 11:33:43	ga_ls8c_ard_3-1-0_112078_2020-03-15_final
2020-03-18 10:24:55	ga_ls8c_ard_3-1-0_101076_2020-03-18_final
2020-03-24 11:27:28	ga_ls8c_ard_3-1-0_111078_2020-03-24_final
2020-03-27 11:57:08	ga_ls8c_ard_3-1-0_116075_2020-03-27_final
2020-03-31 09:54:41	ga_ls8c_ard_3-1-0_096078_2020-03-31_final
2020-04-03 10:23:09	ga_ls8c_ard_3-1-0_101072_2020-04-03_final
2020-04-09 11:27:19	ga_ls8c_ard_3-1-0_111078_2020-04-09_final
2020-04-12 11:57:24	ga_ls8c_ard_3-1-0_116076_2020-04-12_final
2020-04-12 11:57:48	ga_ls8c_ard_3-1-0_116077_2020-04-12_final
2020-04-16 09:51:47	ga_ls8c_ard_3-1-0_096071_2020-04-16_final
2020-04-25 09:48:43	ga_ls8c_ard_3-1-0_095079_2020-04-25_final
2020-04-28 11:57:41	ga_ls8c_ard_3-1-0_116077_2020-04-28_final
2022-03-29 10:41:46	ga_ls8c_ard_3-2-1_104072_2022-03-29_final
2022-04-05 10:48:22	ga_ls8c_ard_3-2-1_105073_2022-04-05_final
2022-04-08 11:22:06	ga_ls8c_ard_3-2-1_110080_2022-04-08_final
2022-04-09 10:26:05	ga_ls8c_ard_3-2-1_101079_2022-04-09_final
2022-04-11 10:11:20	ga_ls8c_ard_3-2-1_099073_2022-04-11_final
2022-04-14 10:41:52	ga_ls8c_ard_3-2-1_104072_2022-04-14_final
2022-04-14 10:44:15	ga_ls8c_ard_3-2-1_104078_2022-04-14_final
2022-04-15 09:49:26	ga_ls8c_ard_3-2-1_095080_2022-04-15_final
2022-04-16 10:29:30	ga_ls8c_ard_3-2-1_102072_2022-04-16_final
2022-04-17 09:36:40	ga_ls8c_ard_3-2-1_093079_2022-04-17_final
2022-04-17 09:38:40	ga_ls8c_ard_3-2-1_093084_2022-04-17_final
2022-04-26 11:06:31	ga_ls8c_ard_3-2-1_108072_2022-04-26_final
2022-04-27 10:11:41	ga_ls8c_ard_3-2-1_099074_2022-04-27_final
2022-05-06 10:05:12	ga_ls8c_ard_3-2-1_098073_2022-05-06_final
2022-05-06 10:05:35	ga_ls8c_ard_3-2-1_098074_2022-05-06_final
2022-05-09 10:35:20	ga_ls8c_ard_3-2-1_103071_2022-05-09_final
2022-05-09 10:36:31	ga_ls8c_ard_3-2-1_103074_2022-05-09_final
2022-05-11 10:24:35	ga_ls8c_ard_3-2-1_101075_2022-05-11_final
2022-05-12 11:06:39	ga_ls8c_ard_3-2-1_108072_2022-05-12_final
2022-05-15 11:40:22	ga_ls8c_ard_3-2-1_113079_2022-05-15_final
2022-05-16 10:41:57	ga_ls8c_ard_3-2-1_104072_2022-05-16_final
2022-05-16 10:45:09	ga_ls8c_ard_3-2-1_104080_2022-05-16_final
2022-05-24 09:55:43	ga_ls8c_ard_3-2-1_096080_2022-05-24_final
2022-05-26 09:41:21	ga_ls8c_ard_3-2-1_094075_2022-05-26_final
2022-05-30 10:56:44	ga_ls8c_ard_3-2-1_106078_2022-05-30_final
2022-06-03 10:29:41	ga_ls8c_ard_3-2-1_102072_2022-06-03_final
2022-06-07 10:05:49	ga_ls8c_ard_3-2-1_098074_2022-06-07_final
2022-06-17 10:44:36	ga_ls8c_ard_3-2-1_104078_2022-06-17_final
2022-06-18 09:49:23	ga_ls8c_ard_3-2-1_095079_2022-06-18_final
2022-06-19 10:29:52	ga_ls8c_ard_3-2-1_102072_2022-06-19_final
2022-06-19 10:31:28	ga_ls8c_ard_3-2-1_102076_2022-06-19_final
2022-06-22 09:24:18	ga_ls8c_ard_3-2-1_091078_2022-06-21_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