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
2018-02-13 11:42:15	ga_ls8c_ard_3-0-0_113084_2018-02-13_final
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
2018-04-16 11:50:31	ga_ls8c_ard_3-0-0_115075_2018-04-16_final
2018-04-16 11:50:55	ga_ls8c_ard_3-0-0_115076_2018-04-16_final
2018-04-16 11:51:18	ga_ls8c_ard_3-0-0_115077_2018-04-16_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
2018-04-18 11:41:43	ga_ls8c_ard_3-0-0_113084_2018-04-18_final
2020-07-03 11:46:49	ga_ls8c_ard_3-1-0_114080_2020-07-03_final
2020-07-03 11:47:13	ga_ls8c_ard_3-1-0_114081_2020-07-03_final
2020-07-19 11:46:55	ga_ls8c_ard_3-1-0_114080_2020-07-19_final
2020-07-19 11:47:19	ga_ls8c_ard_3-1-0_114081_2020-07-19_final
2020-07-28 11:42:22	ga_ls8c_ard_3-1-0_113084_2020-07-28_final
2020-08-18 11:57:01	ga_ls8c_ard_3-1-0_116074_2020-08-18_final
2020-08-18 11:57:25	ga_ls8c_ard_3-1-0_116075_2020-08-18_final
2020-08-18 11:57:49	ga_ls8c_ard_3-1-0_116076_2020-08-18_final
2022-05-15 11:41:58	ga_ls8c_ard_3-2-1_113083_2022-05-15_final
2022-05-15 11:42:22	ga_ls8c_ard_3-2-1_113084_2022-05-15_final
2022-05-20 11:57:20	ga_ls8c_ard_3-2-1_116075_2022-05-20_final
2022-05-20 11:57:44	ga_ls8c_ard_3-2-1_116076_2022-05-20_final
2022-05-22 11:46:58	ga_ls8c_ard_3-2-1_114080_2022-05-22_final
2022-05-22 11:47:22	ga_ls8c_ard_3-2-1_114081_2022-05-22_final
2022-05-29 11:51:09	ga_ls8c_ard_3-2-1_115075_2022-05-29_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
2022-06-05 11:57:26	ga_ls8c_ard_3-2-1_116075_2022-06-05_final
2022-06-05 11:57:50	ga_ls8c_ard_3-2-1_116076_2022-06-05_final
2022-06-07 11:47:06	ga_ls8c_ard_3-2-1_114080_2022-06-07_final
2022-06-07 11:47:30	ga_ls8c_ard_3-2-1_114081_2022-06-07_final
2022-06-21 11:57:36	ga_ls8c_ard_3-2-1_116075_2022-06-21_final
2022-06-21 11:58:00	ga_ls8c_ard_3-2-1_116076_2022-06-21_final
2022-06-23 11:47:15	ga_ls8c_ard_3-2-1_114080_2022-06-23_final
2022-06-23 11:47:39	ga_ls8c_ard_3-2-1_114081_2022-06-23_final
2022-06-30 11:51:27	ga_ls8c_ard_3-2-1_115075_2022-06-30_final
2022-06-30 11:51:51	ga_ls8c_ard_3-2-1_115076_2022-06-30_final
2022-06-30 11:52:15	ga_ls8c_ard_3-2-1_115077_2022-06-30_final
2022-06-30 11:52:39	ga_ls8c_ard_3-2-1_115078_2022-06-30_final
2022-06-30 11:53:03	ga_ls8c_ard_3-2-1_115079_2022-06-30_final
2022-06-30 11:53:27	ga_ls8c_ard_3-2-1_115080_2022-06-30_final
2022-07-02 11:42:17	ga_ls8c_ard_3-2-1_113083_2022-07-02_final
2022-07-02 11:42:41	ga_ls8c_ard_3-2-1_113084_2022-07-02_final
2022-07-07 11:57:38	ga_ls8c_ard_3-2-1_116075_2022-07-07_final
2022-07-07 11:58:02	ga_ls8c_ard_3-2-1_116076_2022-07-07_final
2022-07-09 11:47:16	ga_ls8c_ard_3-2-1_114080_2022-07-09_final
2022-07-09 11:47:40	ga_ls8c_ard_3-2-1_114081_2022-07-09_final
2022-07-16 11:51:26	ga_ls8c_ard_3-2-1_115075_2022-07-16_final
2022-07-16 11:51:49	ga_ls8c_ard_3-2-1_115076_2022-07-16_final
2022-07-16 11:53:25	ga_ls8c_ard_3-2-1_115080_2022-07-16_final
2022-07-18 11:42:41	ga_ls8c_ard_3-2-1_113084_2022-07-18_final
2022-07-25 11:47:22	ga_ls8c_ard_3-2-1_114080_2022-07-25_final
2022-07-25 11:47:46	ga_ls8c_ard_3-2-1_114081_2022-07-25_final
2022-08-01 11:51:38	ga_ls8c_ard_3-2-1_115075_2022-08-01_final
2022-08-01 11:52:02	ga_ls8c_ard_3-2-1_115076_2022-08-01_final
2022-08-01 11:52:26	ga_ls8c_ard_3-2-1_115077_2022-08-01_final
2022-08-01 11:52:50	ga_ls8c_ard_3-2-1_115078_2022-08-01_final
2022-08-01 11:53:14	ga_ls8c_ard_3-2-1_115079_2022-08-01_final
2022-08-01 11:53:37	ga_ls8c_ard_3-2-1_115080_2022-08-01_final
2022-08-17 11:51:44	ga_ls8c_ard_3-2-1_115075_2022-08-17_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
2022-09-02 11:51:44	ga_ls8c_ard_3-2-1_115075_2022-09-02_final
2022-09-02 11:52:08	ga_ls8c_ard_3-2-1_115076_2022-09-02_final
2022-09-02 11:52:32	ga_ls8c_ard_3-2-1_115077_2022-09-02_final
2022-09-02 11:52:56	ga_ls8c_ard_3-2-1_115078_2022-09-02_final
2022-09-02 11:53:20	ga_ls8c_ard_3-2-1_115079_2022-09-02_final
2022-09-02 11:53:44	ga_ls8c_ard_3-2-1_115080_2022-09-02_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
2022-09-11 11:47:38	ga_ls8c_ard_3-2-1_114080_2022-09-11_final
2022-09-11 11:48:02	ga_ls8c_ard_3-2-1_114081_2022-09-11_final
2022-09-18 11:51:51	ga_ls8c_ard_3-2-1_115075_2022-09-18_final
2022-09-18 11:52:15	ga_ls8c_ard_3-2-1_115076_2022-09-18_final
2022-09-18 11:52:39	ga_ls8c_ard_3-2-1_115077_2022-09-18_final
2022-09-18 11:53:03	ga_ls8c_ard_3-2-1_115078_2022-09-18_final
2022-09-18 11:53:27	ga_ls8c_ard_3-2-1_115079_2022-09-18_final
2022-09-18 11:53:51	ga_ls8c_ard_3-2-1_115080_2022-09-18_final
2022-10-06 11:42:38	ga_ls8c_ard_3-2-1_113083_2022-10-06_final
2022-10-06 11:43:02	ga_ls8c_ard_3-2-1_113084_2022-10-06_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
2022-10-22 11:42:38	ga_ls8c_ard_3-2-1_113083_2022-10-22_final
2022-10-22 11:43:02	ga_ls8c_ard_3-2-1_113084_2022-10-22_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
2022-10-29 11:47:39	ga_ls8c_ard_3-2-1_114080_2022-10-29_final
2022-10-29 11:48:03	ga_ls8c_ard_3-2-1_114081_2022-10-29_final
2022-12-09 11:42:35	ga_ls8c_ard_3-2-1_113083_2022-12-09_final
2022-12-09 11:42:59	ga_ls8c_ard_3-2-1_113084_2022-12-09_final
2023-02-02 11:47:24	ga_ls8c_ard_3-2-1_114080_2023-02-02_final
2023-02-02 11:47:48	ga_ls8c_ard_3-2-1_114081_2023-02-02_final
2023-03-22 11:46:53	ga_ls8c_ard_3-2-1_114080_2023-03-22_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