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
2018-02-18 11:56:47	ga_ls8c_ard_3-0-0_116074_2018-02-18_final
2018-02-18 11:57:10	ga_ls8c_ard_3-0-0_116075_2018-02-18_final
2018-02-18 11:57:34	ga_ls8c_ard_3-0-0_116076_2018-02-18_final
2018-02-18 11:57:58	ga_ls8c_ard_3-0-0_116077_2018-02-18_final
2018-02-18 11:58:22	ga_ls8c_ard_3-0-0_116078_2018-02-18_final
2018-03-31 11:51:52	ga_ls8c_ard_3-0-0_115078_2018-03-31_final
2018-03-31 11:52:15	ga_ls8c_ard_3-0-0_115079_2018-03-31_final
2018-03-31 11:52:39	ga_ls8c_ard_3-0-0_115080_2018-03-31_final
2018-04-16 11:51:42	ga_ls8c_ard_3-0-0_115078_2018-04-16_final
2018-04-16 11:52:06	ga_ls8c_ard_3-0-0_115079_2018-04-16_final
2018-04-16 11:52:30	ga_ls8c_ard_3-0-0_115080_2018-04-16_final
2018-04-23 11:56:13	ga_ls8c_ard_3-0-0_116074_2018-04-23_final
2018-04-23 11:56:37	ga_ls8c_ard_3-0-0_116075_2018-04-23_final
2018-04-23 11:57:01	ga_ls8c_ard_3-0-0_116076_2018-04-23_final
2018-04-23 11:57:25	ga_ls8c_ard_3-0-0_116077_2018-04-23_final
2018-04-23 11:57:49	ga_ls8c_ard_3-0-0_116078_2018-04-23_final
2018-05-02 11:51:10	ga_ls8c_ard_3-0-0_115077_2018-05-02_final
2018-05-02 11:51:34	ga_ls8c_ard_3-0-0_115078_2018-05-02_final
2018-05-02 11:51:58	ga_ls8c_ard_3-0-0_115079_2018-05-02_final
2018-05-02 11:52:21	ga_ls8c_ard_3-0-0_115080_2018-05-02_final
2018-06-03 11:50:47	ga_ls8c_ard_3-0-0_115077_2018-06-03_final
2018-06-03 11:51:11	ga_ls8c_ard_3-0-0_115078_2018-06-03_final
2018-06-03 11:51:35	ga_ls8c_ard_3-0-0_115079_2018-06-03_final
2018-06-03 11:51:59	ga_ls8c_ard_3-0-0_115080_2018-06-03_final
2018-06-19 11:50:56	ga_ls8c_ard_3-0-0_115077_2018-06-19_final
2018-06-19 11:51:20	ga_ls8c_ard_3-0-0_115078_2018-06-19_final
2018-06-19 11:51:44	ga_ls8c_ard_3-0-0_115079_2018-06-19_final
2018-06-19 11:52:08	ga_ls8c_ard_3-0-0_115080_2018-06-19_final
2018-07-21 11:51:13	ga_ls8c_ard_3-0-0_115077_2018-07-21_final
2018-07-21 11:51:37	ga_ls8c_ard_3-0-0_115078_2018-07-21_final
2018-07-21 11:52:00	ga_ls8c_ard_3-0-0_115079_2018-07-21_final
2018-07-21 11:52:24	ga_ls8c_ard_3-0-0_115080_2018-07-21_final
2018-08-06 11:51:21	ga_ls8c_ard_3-0-0_115077_2018-08-06_final
2018-08-06 11:51:45	ga_ls8c_ard_3-0-0_115078_2018-08-06_final
2018-08-06 11:52:09	ga_ls8c_ard_3-0-0_115079_2018-08-06_final
2018-08-06 11:52:33	ga_ls8c_ard_3-0-0_115080_2018-08-06_final
2022-09-25 11:58:02	ga_ls8c_ard_3-2-1_116075_2022-09-25_final
2022-09-25 11:58:26	ga_ls8c_ard_3-2-1_116076_2022-09-25_final
2022-09-25 11:58:50	ga_ls8c_ard_3-2-1_116077_2022-09-25_final
2022-09-25 11:59:14	ga_ls8c_ard_3-2-1_116078_2022-09-25_final
2022-09-27 11:48:04	ga_ls8c_ard_3-2-1_114081_2022-09-27_final
2022-10-04 11:52:37	ga_ls8c_ard_3-2-1_115077_2022-10-04_final
2022-10-04 11:53:01	ga_ls8c_ard_3-2-1_115078_2022-10-04_final
2022-10-04 11:53:25	ga_ls8c_ard_3-2-1_115079_2022-10-04_final
2022-10-04 11:53:49	ga_ls8c_ard_3-2-1_115080_2022-10-04_final
2022-10-11 11:57:55	ga_ls8c_ard_3-2-1_116075_2022-10-11_final
2022-10-11 11:58:19	ga_ls8c_ard_3-2-1_116076_2022-10-11_final
2022-10-11 11:58:43	ga_ls8c_ard_3-2-1_116077_2022-10-11_final
2022-10-11 11:59:07	ga_ls8c_ard_3-2-1_116078_2022-10-11_final
2022-10-20 11:52:34	ga_ls8c_ard_3-2-1_115077_2022-10-20_final
2022-10-20 11:52:58	ga_ls8c_ard_3-2-1_115078_2022-10-20_final
2022-10-20 11:53:22	ga_ls8c_ard_3-2-1_115079_2022-10-20_final
2022-10-20 11:53:46	ga_ls8c_ard_3-2-1_115080_2022-10-20_final
2022-10-27 11:58:01	ga_ls8c_ard_3-2-1_116075_2022-10-27_final
2022-10-27 11:58:25	ga_ls8c_ard_3-2-1_116076_2022-10-27_final
2022-10-27 11:58:49	ga_ls8c_ard_3-2-1_116077_2022-10-27_final
2022-10-27 11:59:13	ga_ls8c_ard_3-2-1_116078_2022-10-27_final
2022-10-29 11:48:03	ga_ls8c_ard_3-2-1_114081_2022-10-29_final
2023-01-08 11:52:24	ga_ls8c_ard_3-2-1_115077_2023-01-08_final
2023-01-08 11:52:48	ga_ls8c_ard_3-2-1_115078_2023-01-08_final
2023-01-08 11:53:12	ga_ls8c_ard_3-2-1_115079_2023-01-08_final
2023-01-08 11:53:36	ga_ls8c_ard_3-2-1_115080_2023-01-08_final
2023-01-15 11:57:42	ga_ls8c_ard_3-2-1_116075_2023-01-15_final
2023-01-15 11:58:06	ga_ls8c_ard_3-2-1_116076_2023-01-15_final
2023-01-15 11:58:30	ga_ls8c_ard_3-2-1_116077_2023-01-15_final
2023-01-15 11:58:54	ga_ls8c_ard_3-2-1_116078_2023-01-15_final
2023-01-24 11:52:22	ga_ls8c_ard_3-2-1_115077_2023-01-24_final
2023-01-24 11:52:45	ga_ls8c_ard_3-2-1_115078_2023-01-24_final
2023-01-24 11:53:09	ga_ls8c_ard_3-2-1_115079_2023-01-24_final
2023-01-24 11:53:33	ga_ls8c_ard_3-2-1_115080_2023-01-24_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
2023-01-31 11:58:58	ga_ls8c_ard_3-2-1_116078_2023-01-31_final
2023-02-09 11:52:21	ga_ls8c_ard_3-2-1_115077_2023-02-09_final
2023-02-09 11:52:45	ga_ls8c_ard_3-2-1_115078_2023-02-09_final
2023-02-09 11:53:09	ga_ls8c_ard_3-2-1_115079_2023-02-09_final
2023-02-09 11:53:33	ga_ls8c_ard_3-2-1_115080_2023-02-09_final
2023-02-16 11:57:38	ga_ls8c_ard_3-2-1_116075_2023-02-16_final
2023-02-16 11:58:02	ga_ls8c_ard_3-2-1_116076_2023-02-16_final
2023-02-16 11:58:26	ga_ls8c_ard_3-2-1_116077_2023-02-16_final
2023-02-16 11:58:50	ga_ls8c_ard_3-2-1_116078_2023-02-16_final
2023-03-13 11:51:59	ga_ls8c_ard_3-2-1_115077_2023-03-13_final
2023-03-13 11:52:23	ga_ls8c_ard_3-2-1_115078_2023-03-13_final
2023-03-13 11:52:47	ga_ls8c_ard_3-2-1_115079_2023-03-13_final
2023-03-13 11:53:10	ga_ls8c_ard_3-2-1_115080_2023-03-13_final
2023-04-05 11:57:05	ga_ls8c_ard_3-2-1_116075_2023-04-05_final
2023-04-05 11:57:29	ga_ls8c_ard_3-2-1_116076_2023-04-05_final
2023-04-05 11:57:53	ga_ls8c_ard_3-2-1_116077_2023-04-05_final
2023-04-05 11:58:17	ga_ls8c_ard_3-2-1_116078_2023-04-05_final
2023-04-14 11:51:57	ga_ls8c_ard_3-2-1_115078_2023-04-14_final
2023-04-14 11:52:21	ga_ls8c_ard_3-2-1_115079_2023-04-14_final
2023-04-14 11:52:45	ga_ls8c_ard_3-2-1_115080_2023-04-14_final
2023-05-16 11:51:16	ga_ls8c_ard_3-2-1_115077_2023-05-16_final
2023-05-16 11:51:40	ga_ls8c_ard_3-2-1_115078_2023-05-16_final
2023-05-16 11:52:04	ga_ls8c_ard_3-2-1_115079_2023-05-16_final
2023-05-16 11:52:28	ga_ls8c_ard_3-2-1_115080_2023-05-16_final
2023-05-23 11:56:41	ga_ls8c_ard_3-2-1_116075_2023-05-23_final
2023-05-23 11:57:05	ga_ls8c_ard_3-2-1_116076_2023-05-23_final
2023-05-23 11:57:29	ga_ls8c_ard_3-2-1_116077_2023-05-23_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years