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
2016-01-12 11:57:28	ga_ls8c_ard_3-0-0_116075_2016-01-12_final
2016-01-12 11:57:52	ga_ls8c_ard_3-0-0_116076_2016-01-12_final
2016-01-12 11:58:16	ga_ls8c_ard_3-0-0_116077_2016-01-12_final
2016-01-12 11:58:39	ga_ls8c_ard_3-0-0_116078_2016-01-12_final
2016-01-23 11:42:31	ga_ls8c_ard_3-0-0_113084_2016-01-23_final
2016-01-28 11:57:03	ga_ls8c_ard_3-0-0_116074_2016-01-28_final
2016-01-28 11:57:27	ga_ls8c_ard_3-0-0_116075_2016-01-28_final
2016-01-28 11:57:51	ga_ls8c_ard_3-0-0_116076_2016-01-28_final
2016-01-28 11:58:15	ga_ls8c_ard_3-0-0_116077_2016-01-28_final
2016-01-28 11:58:39	ga_ls8c_ard_3-0-0_116078_2016-01-28_final
2016-02-06 11:52:02	ga_ls8c_ard_3-0-0_115077_2016-02-06_final
2016-02-06 11:52:25	ga_ls8c_ard_3-0-0_115078_2016-02-06_final
2016-02-06 11:52:49	ga_ls8c_ard_3-0-0_115079_2016-02-06_final
2016-02-06 11:53:13	ga_ls8c_ard_3-0-0_115080_2016-02-06_final
2016-02-13 11:56:57	ga_ls8c_ard_3-0-0_116074_2016-02-13_final
2016-02-13 11:57:21	ga_ls8c_ard_3-0-0_116075_2016-02-13_final
2016-02-13 11:57:45	ga_ls8c_ard_3-0-0_116076_2016-02-13_final
2016-02-13 11:58:09	ga_ls8c_ard_3-0-0_116077_2016-02-13_final
2016-02-13 11:58:32	ga_ls8c_ard_3-0-0_116078_2016-02-13_final
2016-02-29 11:56:53	ga_ls8c_ard_3-0-0_116074_2016-02-29_final
2016-02-29 11:57:17	ga_ls8c_ard_3-0-0_116075_2016-02-29_final
2016-02-29 11:57:41	ga_ls8c_ard_3-0-0_116076_2016-02-29_final
2016-02-29 11:58:05	ga_ls8c_ard_3-0-0_116077_2016-02-29_final
2016-02-29 11:58:29	ga_ls8c_ard_3-0-0_116078_2016-02-29_final
2016-04-01 11:56:38	ga_ls8c_ard_3-0-0_116074_2016-04-01_final
2016-04-01 11:57:02	ga_ls8c_ard_3-0-0_116075_2016-04-01_final
2016-04-01 11:57:26	ga_ls8c_ard_3-0-0_116076_2016-04-01_final
2016-04-01 11:57:50	ga_ls8c_ard_3-0-0_116077_2016-04-01_final
2016-04-01 11:58:14	ga_ls8c_ard_3-0-0_116078_2016-04-01_final
2016-04-17 11:56:33	ga_ls8c_ard_3-0-0_116074_2016-04-17_final
2016-04-17 11:56:57	ga_ls8c_ard_3-0-0_116075_2016-04-17_final
2016-04-17 11:57:21	ga_ls8c_ard_3-0-0_116076_2016-04-17_final
2016-04-17 11:57:45	ga_ls8c_ard_3-0-0_116077_2016-04-17_final
2016-04-17 11:58:09	ga_ls8c_ard_3-0-0_116078_2016-04-17_final
2018-10-02 11:47:10	ga_ls8c_ard_3-0-0_114081_2018-10-02_final
2018-10-18 11:47:16	ga_ls8c_ard_3-0-0_114081_2018-10-18_final
2018-11-28 11:42:22	ga_ls8c_ard_3-0-0_113084_2018-11-28_final
2018-12-05 11:47:19	ga_ls8c_ard_3-0-0_114081_2018-12-05_final
2018-12-21 11:47:18	ga_ls8c_ard_3-0-0_114081_2018-12-21_final
2018-12-28 11:51:53	ga_ls8c_ard_3-0-0_115077_2018-12-28_final
2018-12-28 11:52:17	ga_ls8c_ard_3-0-0_115078_2018-12-28_final
2018-12-28 11:52:41	ga_ls8c_ard_3-0-0_115079_2018-12-28_final
2018-12-28 11:53:05	ga_ls8c_ard_3-0-0_115080_2018-12-28_final
2018-12-30 11:42:19	ga_ls8c_ard_3-0-0_113084_2018-12-30_final
2019-04-26 11:56:22	ga_ls8c_ard_3-0-0_116074_2019-04-26_final
2019-04-26 11:56:46	ga_ls8c_ard_3-0-0_116075_2019-04-26_final
2019-04-26 11:57:10	ga_ls8c_ard_3-0-0_116076_2019-04-26_final
2019-04-26 11:57:34	ga_ls8c_ard_3-0-0_116077_2019-04-26_final
2019-04-26 11:57:58	ga_ls8c_ard_3-0-0_116078_2019-04-26_final
2019-11-06 11:47:48	ga_ls8c_ard_3-1-0_114081_2019-11-06_final
2019-12-15 11:52:18	ga_ls8c_ard_3-2-0_115077_2019-12-15_final
2019-12-15 11:52:42	ga_ls8c_ard_3-2-0_115078_2019-12-15_final
2019-12-15 11:53:06	ga_ls8c_ard_3-2-0_115079_2019-12-15_final
2019-12-15 11:53:30	ga_ls8c_ard_3-2-0_115080_2019-12-15_final
2019-12-17 11:42:44	ga_ls8c_ard_3-2-0_113084_2019-12-17_final
2019-12-22 11:57:15	ga_ls8c_ard_3-1-0_116074_2019-12-22_final
2019-12-22 11:57:39	ga_ls8c_ard_3-1-0_116075_2019-12-22_final
2019-12-22 11:58:03	ga_ls8c_ard_3-1-0_116076_2019-12-22_final
2019-12-22 11:58:27	ga_ls8c_ard_3-1-0_116077_2019-12-22_final
2019-12-22 11:58:51	ga_ls8c_ard_3-1-0_116078_2019-12-22_final
2022-05-29 11:51:33	ga_ls8c_ard_3-2-1_115076_2022-05-29_final
2022-05-29 11:51:57	ga_ls8c_ard_3-2-1_115077_2022-05-29_final
2022-05-29 11:52:21	ga_ls8c_ard_3-2-1_115078_2022-05-29_final
2022-05-29 11:52:45	ga_ls8c_ard_3-2-1_115079_2022-05-29_final
2022-05-29 11:53:09	ga_ls8c_ard_3-2-1_115080_2022-05-29_final
2022-08-08 11:57:52	ga_ls8c_ard_3-2-1_116075_2022-08-08_final
2022-08-08 11:58:16	ga_ls8c_ard_3-2-1_116076_2022-08-08_final
2022-08-08 11:58:40	ga_ls8c_ard_3-2-1_116077_2022-08-08_final
2022-08-17 11:52:08	ga_ls8c_ard_3-2-1_115076_2022-08-17_final
2022-08-17 11:52:32	ga_ls8c_ard_3-2-1_115077_2022-08-17_final
2022-08-17 11:52:56	ga_ls8c_ard_3-2-1_115078_2022-08-17_final
2022-08-17 11:53:20	ga_ls8c_ard_3-2-1_115079_2022-08-17_final
2022-08-17 11:53:44	ga_ls8c_ard_3-2-1_115080_2022-08-17_final
2022-08-26 11:47:57	ga_ls8c_ard_3-2-1_114081_2022-08-26_final
2022-09-09 11:57:59	ga_ls8c_ard_3-2-1_116075_2022-09-09_final
2022-09-09 11:58:22	ga_ls8c_ard_3-2-1_116076_2022-09-09_final
2022-09-09 11:58:46	ga_ls8c_ard_3-2-1_116077_2022-09-09_final
2023-01-31 11:57:46	ga_ls8c_ard_3-2-1_116075_2023-01-31_final
2023-01-31 11:58:10	ga_ls8c_ard_3-2-1_116076_2023-01-31_final
2023-01-31 11:58:34	ga_ls8c_ard_3-2-1_116077_2023-01-31_final
2023-02-02 11:47:48	ga_ls8c_ard_3-2-1_114081_2023-02-02_final
2023-06-01 11:52:07	ga_ls8c_ard_3-2-1_115079_2023-06-01_final
2023-06-01 11:52:30	ga_ls8c_ard_3-2-1_115080_2023-06-01_final
2023-07-05 11:42:05	ga_ls8c_ard_3-2-1_113084_2023-07-05_final
2023-07-10 11:57:05	ga_ls8c_ard_3-2-1_116075_2023-07-10_final
2023-07-10 11:57:29	ga_ls8c_ard_3-2-1_116076_2023-07-10_final
2023-07-10 11:57:52	ga_ls8c_ard_3-2-1_116077_2023-07-10_final
2023-07-10 11:58:16	ga_ls8c_ard_3-2-1_116078_2023-07-10_final
2023-07-12 11:47:07	ga_ls8c_ard_3-2-1_114081_2023-07-12_final
2023-10-16 11:47:35	ga_ls8c_ard_3-2-1_114081_2023-10-16_final
2024-03-22 11:57:31	ga_ls8c_ard_3-2-1_116076_2024-03-22_final
2024-03-22 11:57:55	ga_ls8c_ard_3-2-1_116077_2024-03-22_final
2024-03-22 11:58:19	ga_ls8c_ard_3-2-1_116078_2024-03-22_final
2024-03-24 11:47:06	ga_ls8c_ard_3-2-1_114081_2024-03-24_final
2024-03-31 11:51:37	ga_ls8c_ard_3-2-1_115077_2024-03-31_final
2024-03-31 11:52:01	ga_ls8c_ard_3-2-1_115078_2024-03-31_final
2024-03-31 11:52:25	ga_ls8c_ard_3-2-1_115079_2024-03-31_final
2024-03-31 11:52:48	ga_ls8c_ard_3-2-1_115080_2024-03-31_final
2024-04-23 11:57:15	ga_ls8c_ard_3-2-1_116076_2024-04-23_nrt
2024-04-23 11:57:39	ga_ls8c_ard_3-2-1_116077_2024-04-23_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