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
2016-11-12 09:20:25	ga_ls8c_ard_3-0-0_091068_2016-11-11_final
2016-12-14 09:20:22	ga_ls8c_ard_3-0-0_091068_2016-12-13_final
2017-01-26 09:06:02	ga_ls8c_ard_3-0-0_088079_2017-01-25_final
2017-01-26 09:06:26	ga_ls8c_ard_3-0-0_088080_2017-01-25_final
2017-01-26 09:06:49	ga_ls8c_ard_3-1-0_088081_2017-01-25_final
2017-01-26 09:07:13	ga_ls8c_ard_3-0-0_088082_2017-01-25_final
2017-02-11 09:05:53	ga_ls8c_ard_3-0-0_088079_2017-02-10_final
2017-02-11 09:06:17	ga_ls8c_ard_3-0-0_088080_2017-02-10_final
2017-02-11 09:06:41	ga_ls8c_ard_3-1-0_088081_2017-02-10_final
2017-02-11 09:07:05	ga_ls8c_ard_3-0-0_088082_2017-02-10_final
2017-02-16 09:20:01	ga_ls8c_ard_3-0-0_091068_2017-02-15_final
2017-10-25 09:06:14	ga_ls8c_ard_3-0-0_088079_2017-10-24_final
2017-10-25 09:06:38	ga_ls8c_ard_3-0-0_088080_2017-10-24_final
2017-10-25 09:07:02	ga_ls8c_ard_3-1-0_088081_2017-10-24_final
2017-10-25 09:07:26	ga_ls8c_ard_3-0-0_088082_2017-10-24_final
2017-10-30 09:20:23	ga_ls8c_ard_3-0-0_091068_2017-10-29_final
2017-11-10 09:06:12	ga_ls8c_ard_3-0-0_088079_2017-11-09_final
2017-11-10 09:06:36	ga_ls8c_ard_3-0-0_088080_2017-11-09_final
2017-11-10 09:07:00	ga_ls8c_ard_3-1-0_088081_2017-11-09_final
2017-11-10 09:07:24	ga_ls8c_ard_3-0-0_088082_2017-11-09_final
2017-11-17 09:10:21	ga_ls8c_ard_3-0-0_089074_2017-11-16_final
2017-11-17 09:10:45	ga_ls8c_ard_3-0-0_089075_2017-11-16_final
2017-11-17 09:11:09	ga_ls8c_ard_3-0-0_089076_2017-11-16_final
2017-11-17 09:11:33	ga_ls8c_ard_3-0-0_089077_2017-11-16_final
2017-11-17 09:11:57	ga_ls8c_ard_3-0-0_089078_2017-11-16_final
2017-12-12 09:06:05	ga_ls8c_ard_3-0-0_088079_2017-12-11_final
2017-12-12 09:06:29	ga_ls8c_ard_3-0-0_088080_2017-12-11_final
2017-12-12 09:06:53	ga_ls8c_ard_3-1-0_088081_2017-12-11_final
2017-12-12 09:07:17	ga_ls8c_ard_3-0-0_088082_2017-12-11_final
2018-01-13 09:06:00	ga_ls8c_ard_3-0-0_088079_2018-01-12_final
2018-01-13 09:06:24	ga_ls8c_ard_3-0-0_088080_2018-01-12_final
2018-01-13 09:06:48	ga_ls8c_ard_3-1-0_088081_2018-01-12_final
2018-01-13 09:07:12	ga_ls8c_ard_3-0-0_088082_2018-01-12_final
2018-01-20 09:10:08	ga_ls8c_ard_3-0-0_089074_2018-01-19_final
2018-01-20 09:10:32	ga_ls8c_ard_3-0-0_089075_2018-01-19_final
2019-02-01 09:05:42	ga_ls8c_ard_3-0-0_088079_2019-01-31_final
2019-02-01 09:06:06	ga_ls8c_ard_3-0-0_088080_2019-01-31_final
2019-02-01 09:06:30	ga_ls8c_ard_3-1-0_088081_2019-01-31_final
2019-02-01 09:06:54	ga_ls8c_ard_3-0-0_088082_2019-01-31_final
2019-02-06 09:19:51	ga_ls8c_ard_3-0-0_091068_2019-02-05_final
2019-02-22 09:19:48	ga_ls8c_ard_3-0-0_091068_2019-02-21_final
2019-04-13 09:09:36	ga_ls8c_ard_3-1-0_089074_2019-04-12_final
2019-04-13 09:10:00	ga_ls8c_ard_3-1-0_089075_2019-04-12_final
2019-04-13 09:10:24	ga_ls8c_ard_3-1-0_089076_2019-04-12_final
2019-04-13 09:10:48	ga_ls8c_ard_3-1-0_089077_2019-04-12_final
2019-04-13 09:11:12	ga_ls8c_ard_3-1-0_089078_2019-04-12_final
2019-05-08 09:05:26	ga_ls8c_ard_3-0-0_088079_2019-05-07_final
2019-05-08 09:05:50	ga_ls8c_ard_3-0-0_088080_2019-05-07_final
2019-05-08 09:06:13	ga_ls8c_ard_3-0-0_088081_2019-05-07_final
2019-05-08 09:06:37	ga_ls8c_ard_3-0-0_088082_2019-05-07_final
2019-05-31 09:09:50	ga_ls8c_ard_3-0-0_089074_2019-05-30_final
2019-05-31 09:10:14	ga_ls8c_ard_3-0-0_089075_2019-05-30_final
2019-05-31 09:10:38	ga_ls8c_ard_3-0-0_089076_2019-05-30_final
2019-05-31 09:11:02	ga_ls8c_ard_3-0-0_089077_2019-05-30_final
2019-05-31 09:11:26	ga_ls8c_ard_3-0-0_089078_2019-05-30_final
2019-06-30 09:19:59	ga_ls8c_ard_3-1-0_091068_2019-06-29_final
2020-03-12 09:19:58	ga_ls8c_ard_3-1-0_091068_2020-03-11_final
2020-05-31 09:19:34	ga_ls8c_ard_3-1-0_091068_2020-05-30_final
2020-08-03 09:20:02	ga_ls8c_ard_3-1-0_091068_2020-08-02_final
2020-08-21 09:10:11	ga_ls8c_ard_3-1-0_089074_2020-08-20_final
2020-08-21 09:10:35	ga_ls8c_ard_3-1-0_089075_2020-08-20_final
2020-08-21 09:10:59	ga_ls8c_ard_3-1-0_089076_2020-08-20_final
2020-08-21 09:11:23	ga_ls8c_ard_3-1-0_089077_2020-08-20_final
2020-08-21 09:11:47	ga_ls8c_ard_3-1-0_089078_2020-08-20_final
2020-08-30 09:06:04	ga_ls8c_ard_3-1-0_088079_2020-08-29_final
2020-08-30 09:06:28	ga_ls8c_ard_3-1-0_088080_2020-08-29_final
2020-08-30 09:06:52	ga_ls8c_ard_3-1-0_088081_2020-08-29_final
2020-08-30 09:07:16	ga_ls8c_ard_3-1-0_088082_2020-08-29_final
2021-02-06 09:06:03	ga_ls8c_ard_3-2-0_088079_2021-02-05_final
2021-02-06 09:06:27	ga_ls8c_ard_3-2-0_088080_2021-02-05_final
2021-02-06 09:06:51	ga_ls8c_ard_3-2-0_088081_2021-02-05_final
2021-02-06 09:07:15	ga_ls8c_ard_3-2-0_088082_2021-02-05_final
2021-02-22 09:05:58	ga_ls8c_ard_3-2-0_088079_2021-02-21_final
2021-02-22 09:06:22	ga_ls8c_ard_3-2-0_088080_2021-02-21_final
2021-02-22 09:06:46	ga_ls8c_ard_3-2-0_088081_2021-02-21_final
2021-02-22 09:07:10	ga_ls8c_ard_3-2-0_088082_2021-02-21_final
2021-03-17 09:09:57	ga_ls8c_ard_3-2-0_089074_2021-03-16_final
2021-03-17 09:10:21	ga_ls8c_ard_3-2-0_089075_2021-03-16_final
2021-03-17 09:10:45	ga_ls8c_ard_3-2-0_089076_2021-03-16_final
2021-03-17 09:11:09	ga_ls8c_ard_3-2-0_089077_2021-03-16_final
2021-03-17 09:11:33	ga_ls8c_ard_3-2-0_089078_2021-03-16_final
2021-03-26 09:05:44	ga_ls8c_ard_3-2-0_088079_2021-03-25_final
2021-03-26 09:06:08	ga_ls8c_ard_3-2-0_088080_2021-03-25_final
2021-03-26 09:06:32	ga_ls8c_ard_3-2-0_088081_2021-03-25_final
2021-03-26 09:06:56	ga_ls8c_ard_3-2-0_088082_2021-03-25_final
2021-03-31 09:19:52	ga_ls8c_ard_3-2-0_091068_2021-03-30_final
2021-04-27 09:05:31	ga_ls8c_ard_3-2-0_088079_2021-04-26_final
2021-04-27 09:05:55	ga_ls8c_ard_3-2-0_088080_2021-04-26_final
2021-04-27 09:06:19	ga_ls8c_ard_3-2-0_088081_2021-04-26_final
2021-04-27 09:06:43	ga_ls8c_ard_3-2-0_088082_2021-04-26_final
2021-05-02 09:19:37	ga_ls8c_ard_3-2-0_091068_2021-05-01_final
2021-05-04 09:09:38	ga_ls8c_ard_3-2-0_089074_2021-05-03_final
2021-05-04 09:10:02	ga_ls8c_ard_3-2-0_089075_2021-05-03_final
2021-05-04 09:10:26	ga_ls8c_ard_3-2-0_089076_2021-05-03_final
2021-05-04 09:10:50	ga_ls8c_ard_3-2-0_089077_2021-05-03_final
2021-05-04 09:11:14	ga_ls8c_ard_3-2-0_089078_2021-05-03_final
2021-05-18 09:19:42	ga_ls8c_ard_3-2-0_091068_2021-05-17_final
2021-05-29 09:05:39	ga_ls8c_ard_3-2-0_088079_2021-05-28_final
2021-05-29 09:06:03	ga_ls8c_ard_3-2-0_088080_2021-05-28_final
2021-05-29 09:06:27	ga_ls8c_ard_3-2-0_088081_2021-05-28_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