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
2016-01-24 10:46:30	ga_ls8c_ard_3-1-0_104083_2016-01-24_final
2019-03-08 11:17:45	ga_ls8c_ard_3-1-0_109085_2019-03-08_final
2019-03-13 11:31:52	ga_ls8c_ard_3-1-0_112074_2019-03-13_final
2019-03-15 11:20:18	ga_ls8c_ard_3-1-0_110076_2019-03-15_final
2019-03-20 11:35:14	ga_ls8c_ard_3-1-0_113067_2019-03-20_final
2019-03-29 11:33:49	ga_ls8c_ard_3-1-0_112079_2019-03-29_final
2019-04-06 10:39:33	ga_ls8c_ard_3-1-0_104067_2019-04-06_final
2019-04-06 10:45:56	ga_ls8c_ard_3-1-0_104083_2019-04-06_final
2019-04-09 11:16:01	ga_ls8c_ard_3-1-0_109081_2019-04-09_final
2019-04-12 11:46:30	ga_ls8c_ard_3-1-0_114080_2019-04-12_final
2019-06-17 11:34:06	ga_ls8c_ard_3-1-0_112079_2019-06-17_final
2019-06-18 10:34:53	ga_ls8c_ard_3-1-0_103070_2019-06-18_final
2019-06-25 10:42:18	ga_ls8c_ard_3-1-0_104073_2019-06-25_final
2019-06-27 10:28:21	ga_ls8c_ard_3-1-0_102069_2019-06-27_final
2019-06-29 11:57:41	ga_ls8c_ard_3-1-0_116076_2019-06-29_final
2019-07-03 11:31:47	ga_ls8c_ard_3-1-0_112073_2019-07-03_final
2019-07-08 11:50:44	ga_ls8c_ard_3-1-0_115074_2019-07-08_final
2019-07-08 11:51:56	ga_ls8c_ard_3-1-0_115077_2019-07-08_final
2019-07-09 10:56:43	ga_ls8c_ard_3-1-0_106078_2019-07-09_final
2019-07-11 10:42:22	ga_ls8c_ard_3-1-0_104073_2019-07-11_final
2019-07-14 11:14:28	ga_ls8c_ard_3-1-0_109076_2019-07-14_final
2019-07-17 11:46:58	ga_ls8c_ard_3-1-0_114080_2019-07-17_final
2019-07-20 10:33:49	ga_ls8c_ard_3-1-0_103067_2019-07-20_final
2019-07-24 11:50:24	ga_ls8c_ard_3-1-0_115073_2019-07-24_final
2019-07-24 11:52:48	ga_ls8c_ard_3-1-0_115079_2019-07-24_final
2019-07-26 11:35:40	ga_ls8c_ard_3-1-0_113067_2019-07-26_final
2019-07-27 10:40:03	ga_ls8c_ard_3-1-0_104067_2019-07-27_final
2019-07-30 11:11:22	ga_ls8c_ard_3-1-0_109068_2019-07-30_final
2019-08-05 10:35:07	ga_ls8c_ard_3-1-0_103070_2019-08-05_final
2019-08-09 11:50:54	ga_ls8c_ard_3-1-0_115074_2019-08-09_final
2019-08-11 11:40:57	ga_ls8c_ard_3-1-0_113080_2019-08-11_final
2019-08-12 10:42:33	ga_ls8c_ard_3-1-0_104073_2019-08-12_final
2019-08-20 11:36:01	ga_ls8c_ard_3-1-0_112083_2019-08-20_final
2019-08-22 11:20:28	ga_ls8c_ard_3-1-0_110075_2019-08-22_final
2019-08-22 11:20:52	ga_ls8c_ard_3-1-0_110076_2019-08-22_final
2019-08-28 10:40:13	ga_ls8c_ard_3-1-0_104067_2019-08-28_final
2019-08-31 11:11:32	ga_ls8c_ard_3-1-0_109068_2019-08-31_final
2019-09-01 11:57:59	ga_ls8c_ard_3-1-0_116076_2019-09-01_final
2019-09-05 11:32:05	ga_ls8c_ard_3-1-0_112073_2019-09-05_final
2019-09-10 11:53:03	ga_ls8c_ard_3-1-0_115079_2019-09-10_final
2019-09-12 11:42:18	ga_ls8c_ard_3-1-0_113083_2019-09-12_final
2019-09-14 11:23:58	ga_ls8c_ard_3-1-0_111068_2019-09-14_final
2019-09-22 10:35:22	ga_ls8c_ard_3-1-0_103070_2019-09-22_final
2019-09-30 11:24:03	ga_ls8c_ard_3-1-0_111068_2019-09-30_final
2019-10-05 11:47:23	ga_ls8c_ard_3-1-0_114080_2019-10-05_final
2019-10-14 11:40:02	ga_ls8c_ard_3-1-0_113077_2019-10-14_final
2019-10-14 11:41:14	ga_ls8c_ard_3-1-0_113080_2019-10-14_final
2019-10-15 10:42:49	ga_ls8c_ard_3-1-0_104073_2019-10-15_final
2019-10-20 10:59:22	ga_ls8c_ard_3-1-0_107068_2019-10-20_final
2019-10-23 11:29:52	ga_ls8c_ard_3-1-0_112067_2019-10-23_final
2019-10-23 11:32:16	ga_ls8c_ard_3-1-0_112073_2019-10-23_final
2019-10-28 11:52:24	ga_ls8c_ard_3-1-0_115077_2019-10-28_final
2019-10-30 11:36:03	ga_ls8c_ard_3-1-0_113067_2019-10-30_final
2019-10-30 11:41:14	ga_ls8c_ard_3-1-0_113080_2019-10-30_final
2019-10-31 10:43:13	ga_ls8c_ard_3-1-0_104074_2019-10-31_final
2019-10-31 10:46:48	ga_ls8c_ard_3-1-0_104083_2019-10-31_final
2019-11-04 11:57:46	ga_ls8c_ard_3-1-0_116075_2019-11-04_final
2019-11-05 11:02:33	ga_ls8c_ard_3-1-0_107076_2019-11-05_final
2019-11-08 11:34:38	ga_ls8c_ard_3-1-0_112079_2019-11-08_final
2019-11-10 11:20:40	ga_ls8c_ard_3-1-0_110075_2019-11-10_final
2019-11-17 11:29:13	ga_ls8c_ard_3-1-0_111081_2019-11-17_final
2019-11-17 11:29:37	ga_ls8c_ard_3-1-0_111082_2019-11-17_final
2019-11-24 11:32:35	ga_ls8c_ard_3-1-0_112074_2019-11-24_final
2019-11-25 10:36:34	ga_ls8c_ard_3-1-0_103073_2019-11-25_final
2019-11-29 11:50:44	ga_ls8c_ard_3-1-0_115073_2019-11-29_final
2019-12-01 11:35:58	ga_ls8c_ard_3-1-0_113067_2019-12-01_final
2019-12-02 10:42:45	ga_ls8c_ard_3-1-0_104073_2019-12-02_final
2019-12-03 11:29:36	ga_ls8c_ard_3-1-0_111082_2019-12-03_final
2019-12-04 10:33:10	ga_ls8c_ard_3-1-0_102080_2019-12-04_final
2019-12-08 11:47:20	ga_ls8c_ard_3-1-0_114080_2019-12-08_final
2019-12-22 11:57:39	ga_ls8c_ard_3-1-0_116075_2019-12-22_final
2020-01-16 11:50:59	ga_ls8c_ard_3-1-0_115074_2020-01-16_final
2020-01-20 11:23:51	ga_ls8c_ard_3-1-0_111068_2020-01-20_final
2020-02-01 11:52:05	ga_ls8c_ard_3-1-0_115077_2020-02-01_final
2020-02-02 10:56:52	ga_ls8c_ard_3-1-0_106078_2020-02-02_final
2020-02-03 11:40:55	ga_ls8c_ard_3-1-0_113080_2020-02-03_final
2020-02-04 10:42:53	ga_ls8c_ard_3-1-0_104074_2020-02-04_final
2020-02-04 10:46:29	ga_ls8c_ard_3-1-0_104083_2020-02-04_final
2020-02-05 11:29:20	ga_ls8c_ard_3-1-0_111082_2020-02-05_final
2020-02-07 11:11:23	ga_ls8c_ard_3-1-0_109068_2020-02-07_final
2020-02-10 11:47:04	ga_ls8c_ard_3-1-0_114080_2020-02-10_final
2020-02-17 11:50:50	ga_ls8c_ard_3-1-0_115074_2020-02-17_final
2020-02-20 10:42:26	ga_ls8c_ard_3-1-0_104073_2020-02-20_final
2020-02-21 11:23:42	ga_ls8c_ard_3-1-0_111068_2020-02-21_final
2020-02-24 11:57:23	ga_ls8c_ard_3-1-0_116075_2020-02-24_final
2020-02-25 11:02:09	ga_ls8c_ard_3-1-0_107076_2020-02-25_final
2020-02-28 11:31:50	ga_ls8c_ard_3-1-0_112073_2020-02-28_final
2020-03-01 11:20:16	ga_ls8c_ard_3-1-0_110075_2020-03-01_final
2020-03-10 11:11:14	ga_ls8c_ard_3-1-0_109068_2020-03-10_final
2020-03-11 11:57:17	ga_ls8c_ard_3-1-0_116075_2020-03-11_final
2020-03-15 11:31:44	ga_ls8c_ard_3-1-0_112073_2020-03-15_final
2020-03-16 10:34:54	ga_ls8c_ard_3-1-0_103070_2020-03-16_final
2020-03-17 11:20:33	ga_ls8c_ard_3-1-0_110076_2020-03-17_final
2020-03-31 11:29:11	ga_ls8c_ard_3-1-0_112067_2020-03-31_final
2020-04-10 10:32:29	ga_ls8c_ard_3-1-0_102080_2020-04-10_final
2020-04-11 11:16:09	ga_ls8c_ard_3-1-0_109081_2020-04-11_final
2020-04-18 11:18:41	ga_ls8c_ard_3-1-0_110072_2020-04-18_final
2020-04-24 10:41:57	ga_ls8c_ard_3-1-0_104073_2020-04-24_final
2020-04-25 11:28:24	ga_ls8c_ard_3-1-0_111081_2020-04-25_final
2020-05-02 11:31:19	ga_ls8c_ard_3-1-0_112073_2020-05-02_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