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
2019-03-29 09:56:32	ga_ls8c_ard_3-1-0_096083_2019-03-29_final
2019-03-29 09:57:20	ga_ls8c_ard_3-1-0_096085_2019-03-29_final
2019-04-02 11:09:29	ga_ls8c_ard_3-1-0_108080_2019-04-02_final
2019-04-13 10:47:17	ga_ls8c_ard_3-1-0_105071_2019-04-13_final
2019-04-14 09:56:03	ga_ls8c_ard_3-1-0_096082_2019-04-14_final
2019-06-17 09:52:49	ga_ls8c_ard_3-1-0_096073_2019-06-17_final
2019-06-17 09:53:37	ga_ls8c_ard_3-1-0_096075_2019-06-17_final
2019-06-26 09:47:53	ga_ls8c_ard_3-1-0_095076_2019-06-26_final
2019-07-02 10:46:07	ga_ls8c_ard_3-1-0_105067_2019-07-02_final
2019-07-18 10:50:33	ga_ls8c_ard_3-1-0_105078_2019-07-18_final
2019-08-03 10:50:40	ga_ls8c_ard_3-1-0_105078_2019-08-03_final
2019-08-03 10:51:04	ga_ls8c_ard_3-1-0_105079_2019-08-03_final
2019-08-13 09:48:07	ga_ls8c_ard_3-1-0_095076_2019-08-13_final
2019-08-17 09:24:13	ga_ls8c_ard_3-1-0_091078_2019-08-16_final
2019-09-04 10:51:36	ga_ls8c_ard_3-1-0_105080_2019-09-04_final
2019-09-09 11:05:47	ga_ls8c_ard_3-1-0_108069_2019-09-09_final
2019-09-09 11:08:59	ga_ls8c_ard_3-1-0_108077_2019-09-09_final
2019-09-30 09:47:57	ga_ls8c_ard_3-1-0_095075_2019-09-30_final
2019-10-04 09:24:50	ga_ls8c_ard_3-1-0_091079_2019-10-03_final
2019-10-20 09:24:52	ga_ls8c_ard_3-1-0_091079_2019-10-19_final
2019-10-23 09:55:46	ga_ls8c_ard_3-1-0_096079_2019-10-23_final
2019-11-01 09:48:47	ga_ls8c_ard_3-1-0_095077_2019-11-01_final
2019-11-01 09:49:11	ga_ls8c_ard_3-1-0_095078_2019-11-01_final
2019-11-05 09:24:51	ga_ls8c_ard_3-1-0_091079_2019-11-04_final
2019-11-08 09:55:21	ga_ls8c_ard_3-1-0_096078_2019-11-08_final
2019-11-12 11:05:55	ga_ls8c_ard_3-1-0_108069_2019-11-12_final
2019-11-17 11:28:01	ga_ls8c_ard_3-1-0_111078_2019-11-17_final
2019-11-21 09:24:48	ga_ls8c_ard_3-1-0_091079_2019-11-20_final
2019-11-24 09:55:18	ga_ls8c_ard_3-1-0_096078_2019-11-24_final
2019-12-07 09:24:47	ga_ls8c_ard_3-1-0_091079_2019-12-06_final
2019-12-09 10:51:18	ga_ls8c_ard_3-1-0_105079_2019-12-09_final
2019-12-10 09:54:05	ga_ls8c_ard_3-1-0_096075_2019-12-10_final
2019-12-26 09:54:02	ga_ls8c_ard_3-1-0_096075_2019-12-26_final
2020-01-04 09:49:24	ga_ls8c_ard_3-1-0_095079_2020-01-04_final
2020-01-04 09:49:48	ga_ls8c_ard_3-1-0_095080_2020-01-04_final
2020-01-08 09:24:40	ga_ls8c_ard_3-1-0_091079_2020-01-07_final
2020-01-11 09:53:58	ga_ls8c_ard_3-1-0_096075_2020-01-11_final
2020-01-11 09:54:46	ga_ls8c_ard_3-1-0_096077_2020-01-11_final
2020-01-15 11:09:19	ga_ls8c_ard_3-1-0_108078_2020-01-15_final
2020-01-24 09:28:12	ga_ls8c_ard_3-1-0_091088_2020-01-23_final
2020-02-05 09:48:27	ga_ls8c_ard_3-1-0_095077_2020-02-05_final
2020-02-11 10:51:03	ga_ls8c_ard_3-1-0_105079_2020-02-11_final
2020-02-12 09:54:37	ga_ls8c_ard_3-1-0_096077_2020-02-12_final
2020-02-27 10:50:59	ga_ls8c_ard_3-1-0_105079_2020-02-27_final
2020-02-28 09:54:33	ga_ls8c_ard_3-1-0_096077_2020-02-28_final
2020-03-03 11:09:53	ga_ls8c_ard_3-1-0_108080_2020-03-03_final
2020-03-08 11:27:36	ga_ls8c_ard_3-1-0_111078_2020-03-08_final
2020-03-15 09:53:38	ga_ls8c_ard_3-1-0_096075_2020-03-15_final
2020-03-19 11:06:34	ga_ls8c_ard_3-1-0_108072_2020-03-19_final
2020-05-01 10:47:16	ga_ls8c_ard_3-1-0_105071_2020-05-01_final
2020-05-01 10:50:04	ga_ls8c_ard_3-1-0_105078_2020-05-01_final
2020-05-02 09:52:50	ga_ls8c_ard_3-1-0_096074_2020-05-02_final
2020-05-02 09:53:14	ga_ls8c_ard_3-1-0_096075_2020-05-02_final
2022-03-29 10:43:46	ga_ls8c_ard_3-2-1_104077_2022-03-29_final
2022-04-01 09:36:34	ga_ls8c_ard_3-2-1_093079_2022-04-01_final
2022-04-03 11:02:42	ga_ls8c_ard_3-2-1_107078_2022-04-03_final
2022-04-04 10:05:05	ga_ls8c_ard_3-2-1_098073_2022-04-04_final
2022-04-04 10:05:29	ga_ls8c_ard_3-2-1_098074_2022-04-04_final
2022-04-04 10:06:17	ga_ls8c_ard_3-2-1_098076_2022-04-04_final
2022-04-06 09:53:33	ga_ls8c_ard_3-2-1_096075_2022-04-06_final
2022-04-06 11:33:38	ga_ls8c_ard_3-2-1_112078_2022-04-06_final
2022-04-07 10:35:14	ga_ls8c_ard_3-2-1_103071_2022-04-07_final
2022-04-07 10:36:26	ga_ls8c_ard_3-2-1_103074_2022-04-07_final
2022-04-07 10:36:50	ga_ls8c_ard_3-2-1_103075_2022-04-07_final
2022-04-08 09:42:25	ga_ls8c_ard_3-2-1_094078_2022-04-08_final
2022-04-13 10:02:35	ga_ls8c_ard_3-2-1_097082_2022-04-13_final
2022-04-13 10:02:59	ga_ls8c_ard_3-2-1_097083_2022-04-13_final
2022-04-13 11:38:41	ga_ls8c_ard_3-2-1_113075_2022-04-13_final
2022-04-14 10:41:52	ga_ls8c_ard_3-2-1_104072_2022-04-14_final
2022-04-14 10:43:51	ga_ls8c_ard_3-2-1_104077_2022-04-14_final
2022-04-15 11:27:07	ga_ls8c_ard_3-2-1_111077_2022-04-15_final
2022-04-16 10:32:18	ga_ls8c_ard_3-2-1_102079_2022-04-16_final
2022-04-19 11:02:47	ga_ls8c_ard_3-2-1_107078_2022-04-19_final
2022-04-20 11:45:15	ga_ls8c_ard_3-2-1_114076_2022-04-20_final
2022-04-21 10:50:25	ga_ls8c_ard_3-2-1_105078_2022-04-21_final
2022-04-22 11:34:28	ga_ls8c_ard_3-2-1_112080_2022-04-22_final
2022-04-23 10:37:15	ga_ls8c_ard_3-2-1_103076_2022-04-23_final
2022-04-23 10:38:27	ga_ls8c_ard_3-2-1_103079_2022-04-23_final
2022-04-24 11:22:06	ga_ls8c_ard_3-2-1_110080_2022-04-24_final
2022-04-28 09:18:27	ga_ls8c_ard_3-2-1_090080_2022-04-27_final
2022-04-29 10:00:07	ga_ls8c_ard_3-2-1_097076_2022-04-29_final
2022-04-29 11:39:00	ga_ls8c_ard_3-2-1_113076_2022-04-29_final
2022-05-01 11:28:16	ga_ls8c_ard_3-2-1_111080_2022-05-01_final
2022-05-06 10:05:35	ga_ls8c_ard_3-2-1_098074_2022-05-06_final
2022-05-06 10:06:23	ga_ls8c_ard_3-2-1_098076_2022-05-06_final
2022-05-08 09:54:51	ga_ls8c_ard_3-2-1_096078_2022-05-08_final
2022-05-09 10:35:20	ga_ls8c_ard_3-2-1_103071_2022-05-09_final
2022-05-13 10:12:14	ga_ls8c_ard_3-2-1_099075_2022-05-13_final
2022-05-15 09:59:53	ga_ls8c_ard_3-2-1_097075_2022-05-15_final
2022-05-15 10:03:05	ga_ls8c_ard_3-2-1_097083_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
2022-05-19 11:12:04	ga_ls8c_ard_3-2-1_109070_2022-05-19_final
2022-06-02 09:48:48	ga_ls8c_ard_3-2-1_095078_2022-06-02_final
2022-06-13 11:08:54	ga_ls8c_ard_3-2-1_108077_2022-06-13_final
2022-06-16 10:00:08	ga_ls8c_ard_3-2-1_097075_2022-06-16_final
2022-06-16 10:00:32	ga_ls8c_ard_3-2-1_097076_2022-06-16_final
2022-06-17 10:44:36	ga_ls8c_ard_3-2-1_104078_2022-06-17_final
2022-06-18 09:49:47	ga_ls8c_ard_3-2-1_095080_2022-06-18_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