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
2016-08-24 11:00:42	ga_ls8c_ard_3-0-0_107072_2016-08-24_final
2016-08-24 11:01:06	ga_ls8c_ard_3-0-0_107073_2016-08-24_final
2016-08-24 11:01:30	ga_ls8c_ard_3-0-0_107074_2016-08-24_final
2016-08-24 11:01:54	ga_ls8c_ard_3-0-0_107075_2016-08-24_final
2016-08-24 11:02:18	ga_ls8c_ard_3-0-0_107076_2016-08-24_final
2016-08-24 11:02:42	ga_ls8c_ard_3-0-0_107077_2016-08-24_final
2016-08-26 10:51:33	ga_ls8c_ard_3-0-0_105080_2016-08-26_final
2016-08-26 10:51:57	ga_ls8c_ard_3-0-0_105081_2016-08-26_final
2016-08-26 10:52:21	ga_ls8c_ard_3-0-0_105082_2016-08-26_final
2016-08-26 10:52:45	ga_ls8c_ard_3-0-0_105083_2016-08-26_final
2016-10-02 11:05:00	ga_ls8c_ard_3-0-0_108067_2016-10-02_final
2016-10-02 11:05:24	ga_ls8c_ard_3-0-0_108068_2016-10-02_final
2016-10-02 11:05:48	ga_ls8c_ard_3-0-0_108069_2016-10-02_final
2016-10-02 11:06:12	ga_ls8c_ard_3-0-0_108070_2016-10-02_final
2016-10-02 11:06:36	ga_ls8c_ard_3-0-0_108071_2016-10-02_final
2016-10-02 11:07:00	ga_ls8c_ard_3-0-0_108072_2016-10-02_final
2016-10-18 11:05:05	ga_ls8c_ard_3-0-0_108067_2016-10-18_final
2016-10-18 11:05:29	ga_ls8c_ard_3-0-0_108068_2016-10-18_final
2016-10-18 11:05:53	ga_ls8c_ard_3-0-0_108069_2016-10-18_final
2016-10-18 11:06:17	ga_ls8c_ard_3-0-0_108070_2016-10-18_final
2016-10-18 11:06:41	ga_ls8c_ard_3-0-0_108071_2016-10-18_final
2016-10-18 11:07:05	ga_ls8c_ard_3-0-0_108072_2016-10-18_final
2016-11-10 11:11:15	ga_ls8c_ard_3-0-0_109067_2016-11-10_final
2016-11-14 10:51:44	ga_ls8c_ard_3-0-0_105080_2016-11-14_final
2016-11-14 10:52:08	ga_ls8c_ard_3-0-0_105081_2016-11-14_final
2016-11-14 10:52:32	ga_ls8c_ard_3-0-0_105082_2016-11-14_final
2016-11-14 10:52:56	ga_ls8c_ard_3-0-0_105083_2016-11-14_final
2016-11-19 11:05:05	ga_ls8c_ard_3-0-0_108067_2016-11-19_final
2016-11-19 11:05:29	ga_ls8c_ard_3-0-0_108068_2016-11-19_final
2016-11-19 11:05:53	ga_ls8c_ard_3-0-0_108069_2016-11-19_final
2018-03-05 11:10:36	ga_ls8c_ard_3-0-0_109067_2018-03-05_final
2018-03-05 11:11:00	ga_ls8c_ard_3-0-0_109068_2018-03-05_final
2018-04-22 11:10:11	ga_ls8c_ard_3-0-0_109067_2018-04-22_final
2018-05-03 10:55:08	ga_ls8c_ard_3-0-0_106076_2018-05-03_final
2018-05-03 10:55:32	ga_ls8c_ard_3-0-0_106077_2018-05-03_final
2018-05-03 10:55:56	ga_ls8c_ard_3-0-0_106078_2018-05-03_final
2018-05-03 10:56:20	ga_ls8c_ard_3-0-0_106079_2018-05-03_final
2018-05-03 10:56:43	ga_ls8c_ard_3-0-0_106080_2018-05-03_final
2018-05-03 10:57:07	ga_ls8c_ard_3-0-0_106081_2018-05-03_final
2018-05-03 10:57:31	ga_ls8c_ard_3-0-0_106082_2018-05-03_final
2018-05-19 10:54:57	ga_ls8c_ard_3-0-0_106076_2018-05-19_final
2018-05-19 10:55:21	ga_ls8c_ard_3-0-0_106077_2018-05-19_final
2018-05-19 10:55:45	ga_ls8c_ard_3-0-0_106078_2018-05-19_final
2018-05-19 10:56:09	ga_ls8c_ard_3-0-0_106079_2018-05-19_final
2018-05-19 10:56:33	ga_ls8c_ard_3-0-0_106080_2018-05-19_final
2018-05-19 10:56:57	ga_ls8c_ard_3-0-0_106081_2018-05-19_final
2018-09-17 10:51:02	ga_ls8c_ard_3-0-0_105080_2018-09-17_final
2018-09-17 10:51:26	ga_ls8c_ard_3-0-0_105081_2018-09-17_final
2018-09-17 10:51:49	ga_ls8c_ard_3-0-0_105082_2018-09-17_final
2018-09-17 10:52:13	ga_ls8c_ard_3-0-0_105083_2018-09-17_final
2018-12-02 11:10:51	ga_ls8c_ard_3-0-0_109067_2018-12-02_final
2018-12-18 11:10:48	ga_ls8c_ard_3-0-0_109067_2018-12-18_final
2019-01-07 10:51:16	ga_ls8c_ard_3-0-0_105080_2019-01-07_final
2019-01-07 10:51:39	ga_ls8c_ard_3-0-0_105081_2019-01-07_final
2019-01-07 10:52:03	ga_ls8c_ard_3-0-0_105082_2019-01-07_final
2019-01-07 10:52:27	ga_ls8c_ard_3-0-0_105083_2019-01-07_final
2022-02-16 10:51:28	ga_ls8c_ard_3-2-1_105080_2022-02-16_final
2022-02-16 10:51:52	ga_ls8c_ard_3-2-1_105081_2022-02-16_final
2022-02-16 10:52:16	ga_ls8c_ard_3-2-1_105082_2022-02-16_final
2022-02-16 10:52:40	ga_ls8c_ard_3-2-1_105083_2022-02-16_final
2022-06-06 11:00:14	ga_ls8c_ard_3-2-1_107071_2022-06-06_final
2022-06-06 11:00:38	ga_ls8c_ard_3-2-1_107072_2022-06-06_final
2022-06-06 11:01:02	ga_ls8c_ard_3-2-1_107073_2022-06-06_final
2022-06-06 11:01:26	ga_ls8c_ard_3-2-1_107074_2022-06-06_final
2022-06-06 11:01:50	ga_ls8c_ard_3-2-1_107075_2022-06-06_final
2022-06-06 11:02:14	ga_ls8c_ard_3-2-1_107076_2022-06-06_final
2022-06-06 11:02:38	ga_ls8c_ard_3-2-1_107077_2022-06-06_final
2022-06-08 10:51:29	ga_ls8c_ard_3-2-1_105080_2022-06-08_final
2022-06-08 10:51:53	ga_ls8c_ard_3-2-1_105081_2022-06-08_final
2022-06-08 10:52:17	ga_ls8c_ard_3-2-1_105082_2022-06-08_final
2022-06-08 10:52:41	ga_ls8c_ard_3-2-1_105083_2022-06-08_final
2022-06-13 11:05:42	ga_ls8c_ard_3-2-1_108069_2022-06-13_final
2022-06-13 11:06:06	ga_ls8c_ard_3-2-1_108070_2022-06-13_final
2022-06-13 11:06:30	ga_ls8c_ard_3-2-1_108071_2022-06-13_final
2022-06-13 11:06:54	ga_ls8c_ard_3-2-1_108072_2022-06-13_final
2022-06-22 11:00:23	ga_ls8c_ard_3-2-1_107071_2022-06-22_final
2022-06-22 11:00:47	ga_ls8c_ard_3-2-1_107072_2022-06-22_final
2022-06-22 11:01:11	ga_ls8c_ard_3-2-1_107073_2022-06-22_final
2022-06-22 11:01:35	ga_ls8c_ard_3-2-1_107074_2022-06-22_final
2022-06-22 11:01:59	ga_ls8c_ard_3-2-1_107075_2022-06-22_final
2022-06-22 11:02:23	ga_ls8c_ard_3-2-1_107076_2022-06-22_final
2022-06-22 11:02:47	ga_ls8c_ard_3-2-1_107077_2022-06-22_final
2022-06-24 10:51:38	ga_ls8c_ard_3-2-1_105080_2022-06-24_final
2022-06-24 10:52:01	ga_ls8c_ard_3-2-1_105081_2022-06-24_final
2022-06-24 10:52:25	ga_ls8c_ard_3-2-1_105082_2022-06-24_final
2022-06-24 10:52:49	ga_ls8c_ard_3-2-1_105083_2022-06-24_final
2022-07-08 11:00:24	ga_ls8c_ard_3-2-1_107071_2022-07-08_final
2022-07-08 11:00:48	ga_ls8c_ard_3-2-1_107072_2022-07-08_final
2022-07-08 11:01:12	ga_ls8c_ard_3-2-1_107073_2022-07-08_final
2022-07-08 11:01:36	ga_ls8c_ard_3-2-1_107074_2022-07-08_final
2022-07-08 11:02:00	ga_ls8c_ard_3-2-1_107075_2022-07-08_final
2022-07-08 11:02:24	ga_ls8c_ard_3-2-1_107076_2022-07-08_final
2022-07-08 11:02:48	ga_ls8c_ard_3-2-1_107077_2022-07-08_final
2022-07-10 10:51:38	ga_ls8c_ard_3-2-1_105080_2022-07-10_final
2022-07-10 10:52:02	ga_ls8c_ard_3-2-1_105081_2022-07-10_final
2022-07-10 10:52:26	ga_ls8c_ard_3-2-1_105082_2022-07-10_final
2022-07-10 10:52:50	ga_ls8c_ard_3-2-1_105083_2022-07-10_final
2023-08-30 10:51:24	ga_ls8c_ard_3-2-1_105080_2023-08-30_final
2023-08-30 10:51:48	ga_ls8c_ard_3-2-1_105081_2023-08-30_final
2023-08-30 10:52:12	ga_ls8c_ard_3-2-1_105082_2023-08-30_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