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
2018-09-14 11:56:36	ga_ls8c_ard_3-0-0_116074_2018-09-14_final
2018-09-14 11:57:00	ga_ls8c_ard_3-0-0_116075_2018-09-14_final
2018-09-14 11:57:24	ga_ls8c_ard_3-0-0_116076_2018-09-14_final
2018-09-14 11:57:48	ga_ls8c_ard_3-0-0_116077_2018-09-14_final
2018-09-14 11:58:12	ga_ls8c_ard_3-0-0_116078_2018-09-14_final
2018-10-16 11:56:50	ga_ls8c_ard_3-0-0_116074_2018-10-16_final
2018-10-16 11:57:14	ga_ls8c_ard_3-0-0_116075_2018-10-16_final
2018-10-16 11:57:38	ga_ls8c_ard_3-0-0_116076_2018-10-16_final
2018-10-16 11:58:02	ga_ls8c_ard_3-0-0_116077_2018-10-16_final
2018-10-16 11:58:26	ga_ls8c_ard_3-0-0_116078_2018-10-16_final
2018-11-17 11:56:55	ga_ls8c_ard_3-0-0_116074_2018-11-17_final
2018-11-17 11:57:19	ga_ls8c_ard_3-0-0_116075_2018-11-17_final
2018-11-17 11:57:43	ga_ls8c_ard_3-0-0_116076_2018-11-17_final
2018-11-17 11:58:07	ga_ls8c_ard_3-0-0_116077_2018-11-17_final
2018-11-17 11:58:31	ga_ls8c_ard_3-0-0_116078_2018-11-17_final
2018-11-26 11:51:56	ga_ls8c_ard_3-0-0_115077_2018-11-26_final
2018-11-26 11:52:20	ga_ls8c_ard_3-0-0_115078_2018-11-26_final
2018-11-26 11:52:44	ga_ls8c_ard_3-0-0_115079_2018-11-26_final
2018-11-26 11:53:08	ga_ls8c_ard_3-0-0_115080_2018-11-26_final
2018-12-12 11:51:53	ga_ls8c_ard_3-0-0_115077_2018-12-12_final
2018-12-12 11:52:17	ga_ls8c_ard_3-0-0_115078_2018-12-12_final
2018-12-12 11:52:40	ga_ls8c_ard_3-0-0_115079_2018-12-12_final
2018-12-12 11:53:04	ga_ls8c_ard_3-0-0_115080_2018-12-12_final
2018-12-19 11:56:52	ga_ls8c_ard_3-0-0_116074_2018-12-19_final
2018-12-19 11:57:16	ga_ls8c_ard_3-0-0_116075_2018-12-19_final
2018-12-19 11:57:39	ga_ls8c_ard_3-0-0_116076_2018-12-19_final
2018-12-19 11:58:03	ga_ls8c_ard_3-0-0_116077_2018-12-19_final
2018-12-19 11:58:27	ga_ls8c_ard_3-0-0_116078_2018-12-19_final
2019-01-06 11:47:17	ga_ls8c_ard_3-0-0_114081_2019-01-06_final
2019-01-20 11:56:48	ga_ls8c_ard_3-0-0_116074_2019-01-20_final
2019-01-20 11:57:12	ga_ls8c_ard_3-0-0_116075_2019-01-20_final
2019-01-20 11:57:36	ga_ls8c_ard_3-0-0_116076_2019-01-20_final
2019-01-20 11:58:00	ga_ls8c_ard_3-0-0_116077_2019-01-20_final
2019-01-20 11:58:24	ga_ls8c_ard_3-0-0_116078_2019-01-20_final
2019-09-03 11:47:37	ga_ls8c_ard_3-1-0_114081_2019-09-03_final
2023-07-19 11:51:42	ga_ls8c_ard_3-2-1_115077_2023-07-19_final
2023-07-19 11:52:06	ga_ls8c_ard_3-2-1_115078_2023-07-19_final
2023-07-19 11:52:30	ga_ls8c_ard_3-2-1_115079_2023-07-19_final
2023-07-19 11:52:54	ga_ls8c_ard_3-2-1_115080_2023-07-19_final
2023-07-21 11:42:08	ga_ls8c_ard_3-2-1_113084_2023-07-21_final
2023-07-26 11:57:10	ga_ls8c_ard_3-2-1_116075_2023-07-26_final
2023-07-26 11:57:34	ga_ls8c_ard_3-2-1_116076_2023-07-26_final
2023-07-26 11:57:58	ga_ls8c_ard_3-2-1_116077_2023-07-26_final
2023-07-26 11:58:22	ga_ls8c_ard_3-2-1_116078_2023-07-26_final
2023-08-20 11:51:58	ga_ls8c_ard_3-2-1_115077_2023-08-20_final
2023-08-20 11:52:22	ga_ls8c_ard_3-2-1_115078_2023-08-20_final
2023-08-20 11:52:46	ga_ls8c_ard_3-2-1_115079_2023-08-20_final
2023-08-20 11:53:10	ga_ls8c_ard_3-2-1_115080_2023-08-20_final
2023-08-22 11:42:25	ga_ls8c_ard_3-2-1_113084_2023-08-22_final
2023-08-27 11:57:23	ga_ls8c_ard_3-2-1_116075_2023-08-27_final
2023-08-27 11:57:47	ga_ls8c_ard_3-2-1_116076_2023-08-27_final
2023-08-27 11:58:11	ga_ls8c_ard_3-2-1_116077_2023-08-27_final
2023-08-27 11:58:35	ga_ls8c_ard_3-2-1_116078_2023-08-27_final
2023-08-29 11:47:25	ga_ls8c_ard_3-2-1_114081_2023-08-29_final
2023-09-05 11:51:58	ga_ls8c_ard_3-2-1_115077_2023-09-05_final
2023-09-05 11:52:22	ga_ls8c_ard_3-2-1_115078_2023-09-05_final
2023-09-05 11:52:46	ga_ls8c_ard_3-2-1_115079_2023-09-05_final
2023-09-05 11:53:10	ga_ls8c_ard_3-2-1_115080_2023-09-05_final
2023-09-12 11:57:25	ga_ls8c_ard_3-2-1_116075_2023-09-12_final
2023-09-12 11:57:49	ga_ls8c_ard_3-2-1_116076_2023-09-12_final
2023-09-12 11:58:13	ga_ls8c_ard_3-2-1_116077_2023-09-12_final
2023-09-12 11:58:37	ga_ls8c_ard_3-2-1_116078_2023-09-12_final
2023-09-23 11:42:30	ga_ls8c_ard_3-2-1_113084_2023-09-23_final
2023-10-14 11:58:21	ga_ls8c_ard_3-2-1_116077_2023-10-14_final
2023-10-14 11:58:45	ga_ls8c_ard_3-2-1_116078_2023-10-14_final
2023-12-10 11:52:08	ga_ls8c_ard_3-2-1_115077_2023-12-10_final
2023-12-10 11:52:32	ga_ls8c_ard_3-2-1_115078_2023-12-10_final
2023-12-10 11:52:56	ga_ls8c_ard_3-2-1_115079_2023-12-10_final
2023-12-10 11:53:20	ga_ls8c_ard_3-2-1_115080_2023-12-10_final
2023-12-12 11:42:36	ga_ls8c_ard_3-2-1_113084_2023-12-12_final
2023-12-17 11:57:35	ga_ls8c_ard_3-2-1_116075_2023-12-17_final
2023-12-17 11:57:59	ga_ls8c_ard_3-2-1_116076_2023-12-17_final
2023-12-17 11:58:23	ga_ls8c_ard_3-2-1_116077_2023-12-17_final
2023-12-17 11:58:47	ga_ls8c_ard_3-2-1_116078_2023-12-17_final
2023-12-19 11:47:38	ga_ls8c_ard_3-2-1_114081_2023-12-19_final
2023-12-26 11:52:12	ga_ls8c_ard_3-2-1_115077_2023-12-26_final
2023-12-26 11:52:36	ga_ls8c_ard_3-2-1_115078_2023-12-26_final
2023-12-26 11:53:00	ga_ls8c_ard_3-2-1_115079_2023-12-26_final
2023-12-26 11:53:24	ga_ls8c_ard_3-2-1_115080_2023-12-26_final
2024-03-17 11:42:14	ga_ls8c_ard_3-2-1_113084_2024-03-17_final
2024-03-22 11:57:07	ga_ls8c_ard_3-2-1_116075_2024-03-22_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
2024-04-07 11:56:59	ga_ls8c_ard_3-2-1_116075_2024-04-07_final
2024-04-07 11:57:23	ga_ls8c_ard_3-2-1_116076_2024-04-07_final
2024-04-07 11:57:47	ga_ls8c_ard_3-2-1_116077_2024-04-07_final
2024-04-07 11:58:11	ga_ls8c_ard_3-2-1_116078_2024-04-07_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
2024-04-23 11:58:03	ga_ls8c_ard_3-2-1_116078_2024-04-23_nrt
2024-04-25 11:46:52	ga_ls8c_ard_3-2-1_114081_2024-04-25_nrt
2024-05-02 11:51:20	ga_ls8c_ard_3-2-1_115077_2024-05-02_nrt
2024-05-02 11:51:44	ga_ls8c_ard_3-2-1_115078_2024-05-02_nrt
2024-05-02 11:52:08	ga_ls8c_ard_3-2-1_115079_2024-05-02_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