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
2016-03-12 09:06:11	ga_ls8c_ard_3-0-0_088080_2016-03-11_final
2016-03-28 09:06:02	ga_ls8c_ard_3-0-0_088080_2016-03-27_final
2016-04-13 09:05:56	ga_ls8c_ard_3-0-0_088080_2016-04-12_final
2016-05-15 09:05:53	ga_ls8c_ard_3-0-0_088080_2016-05-14_final
2016-05-31 09:05:59	ga_ls8c_ard_3-0-0_088080_2016-05-30_final
2016-06-16 09:06:02	ga_ls8c_ard_3-0-0_088080_2016-06-15_final
2016-07-02 09:06:11	ga_ls8c_ard_3-0-0_088080_2016-07-01_final
2016-07-18 09:06:18	ga_ls8c_ard_3-0-0_088080_2016-07-17_final
2016-08-19 09:06:26	ga_ls8c_ard_3-0-0_088080_2016-08-18_final
2016-09-04 09:06:32	ga_ls8c_ard_3-0-0_088080_2016-09-03_final
2016-09-20 09:06:34	ga_ls8c_ard_3-0-0_088080_2016-09-19_final
2016-10-06 09:06:37	ga_ls8c_ard_3-0-0_088080_2016-10-05_final
2016-10-22 09:06:41	ga_ls8c_ard_3-0-0_088080_2016-10-21_final
2016-11-07 09:06:40	ga_ls8c_ard_3-0-0_088080_2016-11-06_final
2016-11-23 09:06:41	ga_ls8c_ard_3-0-0_088080_2016-11-22_final
2016-12-09 09:06:38	ga_ls8c_ard_3-0-0_088080_2016-12-08_final
2016-12-25 09:06:34	ga_ls8c_ard_3-0-0_088080_2016-12-24_final
2017-01-16 11:46:23	ga_ls8c_ard_3-0-0_114078_2017-01-16_final
2017-01-26 09:06:26	ga_ls8c_ard_3-0-0_088080_2017-01-25_final
2017-02-01 11:46:16	ga_ls8c_ard_3-0-0_114078_2017-02-01_final
2017-02-11 09:06:17	ga_ls8c_ard_3-0-0_088080_2017-02-10_final
2017-02-17 11:46:09	ga_ls8c_ard_3-0-0_114078_2017-02-17_final
2017-02-27 09:06:12	ga_ls8c_ard_3-0-0_088080_2017-02-26_final
2017-03-15 09:06:04	ga_ls8c_ard_3-0-0_088080_2017-03-14_final
2017-03-21 11:45:53	ga_ls8c_ard_3-0-0_114078_2017-03-21_final
2017-03-31 09:05:55	ga_ls8c_ard_3-0-0_088080_2017-03-30_final
2017-04-06 11:45:46	ga_ls8c_ard_3-0-0_114078_2017-04-06_final
2017-04-16 09:05:47	ga_ls8c_ard_3-0-0_088080_2017-04-15_final
2017-04-22 11:45:36	ga_ls8c_ard_3-0-0_114078_2017-04-22_final
2017-05-02 09:05:36	ga_ls8c_ard_3-0-0_088080_2017-05-01_final
2017-05-08 11:45:34	ga_ls8c_ard_3-0-0_114078_2017-05-08_final
2017-05-18 09:05:48	ga_ls8c_ard_3-0-0_088080_2017-05-17_final
2017-05-24 11:45:45	ga_ls8c_ard_3-0-0_114078_2017-05-24_final
2017-06-03 09:05:57	ga_ls8c_ard_3-0-0_088080_2017-06-02_final
2017-06-19 09:06:04	ga_ls8c_ard_3-0-0_088080_2017-06-18_final
2017-06-25 11:45:59	ga_ls8c_ard_3-0-0_114078_2017-06-25_final
2017-07-05 09:06:07	ga_ls8c_ard_3-0-0_088080_2017-07-04_final
2017-07-11 11:46:02	ga_ls8c_ard_3-0-0_114078_2017-07-11_final
2017-07-21 09:06:13	ga_ls8c_ard_3-0-0_088080_2017-07-20_final
2017-08-06 09:06:20	ga_ls8c_ard_3-0-0_088080_2017-08-05_final
2017-08-22 09:06:25	ga_ls8c_ard_3-0-0_088080_2017-08-21_final
2017-08-28 11:46:19	ga_ls8c_ard_3-0-0_114078_2017-08-28_final
2017-09-07 09:06:27	ga_ls8c_ard_3-0-0_088080_2017-09-06_final
2017-09-13 11:46:20	ga_ls8c_ard_3-0-0_114078_2017-09-13_final
2017-09-23 09:06:31	ga_ls8c_ard_3-0-0_088080_2017-09-22_final
2017-09-29 11:46:27	ga_ls8c_ard_3-0-0_114078_2017-09-29_final
2017-10-09 09:06:36	ga_ls8c_ard_3-0-0_088080_2017-10-08_final
2017-10-15 11:46:31	ga_ls8c_ard_3-0-0_114078_2017-10-15_final
2017-10-25 09:06:38	ga_ls8c_ard_3-0-0_088080_2017-10-24_final
2017-10-31 11:46:31	ga_ls8c_ard_3-0-0_114078_2017-10-31_final
2017-11-10 09:06:36	ga_ls8c_ard_3-0-0_088080_2017-11-09_final
2017-11-16 11:46:28	ga_ls8c_ard_3-0-0_114078_2017-11-16_final
2017-11-26 09:06:31	ga_ls8c_ard_3-0-0_088080_2017-11-25_final
2017-12-02 11:46:22	ga_ls8c_ard_3-0-0_114078_2017-12-02_final
2017-12-12 09:06:29	ga_ls8c_ard_3-0-0_088080_2017-12-11_final
2017-12-18 11:46:25	ga_ls8c_ard_3-0-0_114078_2017-12-18_final
2017-12-28 09:06:31	ga_ls8c_ard_3-0-0_088080_2017-12-27_final
2018-01-03 11:46:22	ga_ls8c_ard_3-0-0_114078_2018-01-03_final
2018-01-13 09:06:24	ga_ls8c_ard_3-0-0_088080_2018-01-12_final
2018-01-19 11:46:14	ga_ls8c_ard_3-0-0_114078_2018-01-19_final
2018-02-04 11:46:05	ga_ls8c_ard_3-0-0_114078_2018-02-04_final
2018-02-14 09:06:09	ga_ls8c_ard_3-0-0_088080_2018-02-13_final
2018-03-02 09:06:02	ga_ls8c_ard_3-0-0_088080_2018-03-01_final
2018-03-08 11:45:52	ga_ls8c_ard_3-0-0_114078_2018-03-08_final
2018-03-18 09:05:53	ga_ls8c_ard_3-0-0_088080_2018-03-17_final
2018-04-03 09:05:46	ga_ls8c_ard_3-0-0_088080_2018-04-02_final
2018-04-19 09:05:36	ga_ls8c_ard_3-0-0_088080_2018-04-18_final
2018-04-25 11:45:27	ga_ls8c_ard_3-0-0_114078_2018-04-25_final
2018-05-05 09:05:28	ga_ls8c_ard_3-0-0_088080_2018-05-04_final
2018-05-11 11:45:17	ga_ls8c_ard_3-0-0_114078_2018-05-11_final
2018-05-21 09:05:16	ga_ls8c_ard_3-0-0_088080_2018-05-20_final
2018-05-27 11:45:05	ga_ls8c_ard_3-0-0_114078_2018-05-27_final
2018-06-06 09:05:07	ga_ls8c_ard_3-0-0_088080_2018-06-05_final
2018-06-12 11:45:05	ga_ls8c_ard_3-0-0_114078_2018-06-12_final
2018-06-22 09:05:18	ga_ls8c_ard_3-0-0_088080_2018-06-21_final
2018-06-28 11:45:15	ga_ls8c_ard_3-0-0_114078_2018-06-28_final
2018-07-08 09:05:27	ga_ls8c_ard_3-0-0_088080_2018-07-07_final
2018-07-14 11:45:23	ga_ls8c_ard_3-0-0_114078_2018-07-14_final
2018-07-24 09:05:33	ga_ls8c_ard_3-0-0_088080_2018-07-23_final
2018-07-30 11:45:30	ga_ls8c_ard_3-0-0_114078_2018-07-30_final
2018-08-09 09:05:43	ga_ls8c_ard_3-0-0_088080_2018-08-08_final
2018-08-15 11:45:39	ga_ls8c_ard_3-0-0_114078_2018-08-15_final
2018-08-25 09:05:51	ga_ls8c_ard_3-0-0_088080_2018-08-24_final
2018-08-31 11:45:46	ga_ls8c_ard_3-0-0_114078_2018-08-31_final
2018-09-10 09:05:56	ga_ls8c_ard_3-0-0_088080_2018-09-09_final
2018-09-16 11:45:51	ga_ls8c_ard_3-0-0_114078_2018-09-16_final
2018-09-26 09:06:02	ga_ls8c_ard_3-0-0_088080_2018-09-25_final
2018-10-02 11:45:58	ga_ls8c_ard_3-0-0_114078_2018-10-02_final
2018-10-12 09:06:09	ga_ls8c_ard_3-0-0_088080_2018-10-11_final
2018-10-18 11:46:05	ga_ls8c_ard_3-0-0_114078_2018-10-18_final
2018-10-22 09:45:17	ga_ls8c_ard_3-0-0_094085_2018-10-22_final
2018-10-28 09:06:14	ga_ls8c_ard_3-0-0_088080_2018-10-27_final
2018-11-03 11:46:09	ga_ls8c_ard_3-0-0_114078_2018-11-03_final
2018-11-13 09:06:16	ga_ls8c_ard_3-0-0_088080_2018-11-12_final
2018-11-19 11:46:09	ga_ls8c_ard_3-0-0_114078_2018-11-19_final
2018-11-23 09:45:21	ga_ls8c_ard_3-0-0_094085_2018-11-23_final
2018-11-29 09:06:15	ga_ls8c_ard_3-0-0_088080_2018-11-28_final
2018-12-05 11:46:07	ga_ls8c_ard_3-0-0_114078_2018-12-05_final
2018-12-15 09:06:12	ga_ls8c_ard_3-0-0_088080_2018-12-14_final
2018-12-21 11:46:06	ga_ls8c_ard_3-0-0_114078_2018-12-21_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years