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
2018-09-17 10:52:13	ga_ls8c_ard_3-0-0_105083_2018-09-17_final
2019-01-07 10:52:27	ga_ls8c_ard_3-0-0_105083_2019-01-07_final
2019-02-11 11:16:52	ga_ls8c_ard_3-0-0_110067_2019-02-11_final
2019-02-13 11:06:06	ga_ls8c_ard_3-0-0_108071_2019-02-13_final
2019-02-13 11:06:30	ga_ls8c_ard_3-0-0_108072_2019-02-13_final
2019-02-13 11:06:54	ga_ls8c_ard_3-0-0_108073_2019-02-13_final
2019-02-13 11:07:17	ga_ls8c_ard_3-0-0_108074_2019-02-13_final
2019-02-13 11:07:41	ga_ls8c_ard_3-0-0_108075_2019-02-13_final
2019-02-13 11:08:05	ga_ls8c_ard_3-0-0_108076_2019-02-13_final
2019-02-24 10:52:18	ga_ls8c_ard_3-0-0_105083_2019-02-24_final
2019-03-01 11:06:02	ga_ls8c_ard_3-0-0_108071_2019-03-01_final
2019-03-01 11:06:26	ga_ls8c_ard_3-0-0_108072_2019-03-01_final
2019-03-01 11:06:50	ga_ls8c_ard_3-0-0_108073_2019-03-01_final
2019-03-01 11:07:14	ga_ls8c_ard_3-0-0_108074_2019-03-01_final
2019-03-01 11:07:38	ga_ls8c_ard_3-0-0_108075_2019-03-01_final
2019-03-01 11:08:01	ga_ls8c_ard_3-0-0_108076_2019-03-01_final
2019-03-03 10:57:15	ga_ls8c_ard_3-0-0_106080_2019-03-03_final
2019-03-03 10:57:39	ga_ls8c_ard_3-0-0_106081_2019-03-03_final
2019-03-03 10:58:03	ga_ls8c_ard_3-0-0_106082_2019-03-03_final
2019-03-03 10:58:27	ga_ls8c_ard_3-0-0_106083_2019-03-03_final
2019-03-03 10:58:51	ga_ls8c_ard_3-0-0_106084_2019-03-03_final
2019-03-26 11:01:20	ga_ls8c_ard_3-1-0_107075_2019-03-26_final
2019-03-26 11:01:44	ga_ls8c_ard_3-1-0_107076_2019-03-26_final
2019-03-26 11:02:08	ga_ls8c_ard_3-1-0_107077_2019-03-26_final
2019-03-26 11:02:31	ga_ls8c_ard_3-1-0_107078_2019-03-26_final
2019-03-26 11:02:55	ga_ls8c_ard_3-1-0_107079_2019-03-26_final
2019-03-26 11:03:19	ga_ls8c_ard_3-1-0_107080_2019-03-26_final
2019-03-26 11:03:43	ga_ls8c_ard_3-1-0_107081_2019-03-26_final
2019-03-28 10:52:09	ga_ls8c_ard_3-1-0_105083_2019-03-28_final
2019-04-13 10:52:04	ga_ls8c_ard_3-1-0_105083_2019-04-13_final
2019-05-13 11:01:19	ga_ls8c_ard_3-0-0_107075_2019-05-13_final
2019-05-13 11:01:43	ga_ls8c_ard_3-0-0_107076_2019-05-13_final
2019-05-13 11:02:07	ga_ls8c_ard_3-0-0_107077_2019-05-13_final
2019-05-13 11:02:31	ga_ls8c_ard_3-0-0_107078_2019-05-13_final
2019-05-13 11:02:54	ga_ls8c_ard_3-0-0_107079_2019-05-13_final
2019-05-13 11:03:18	ga_ls8c_ard_3-0-0_107080_2019-05-13_final
2019-05-13 11:03:42	ga_ls8c_ard_3-0-0_107081_2019-05-13_final
2019-05-15 10:52:10	ga_ls8c_ard_3-0-0_105083_2019-05-15_final
2019-05-20 11:05:58	ga_ls8c_ard_3-0-0_108071_2019-05-20_final
2019-05-20 11:06:22	ga_ls8c_ard_3-0-0_108072_2019-05-20_final
2019-05-20 11:06:46	ga_ls8c_ard_3-0-0_108073_2019-05-20_final
2019-05-20 11:07:10	ga_ls8c_ard_3-0-0_108074_2019-05-20_final
2019-05-20 11:07:34	ga_ls8c_ard_3-0-0_108075_2019-05-20_final
2019-05-20 11:07:58	ga_ls8c_ard_3-0-0_108076_2019-05-20_final
2019-05-31 10:52:19	ga_ls8c_ard_3-0-0_105083_2019-05-31_final
2019-06-05 11:06:06	ga_ls8c_ard_3-0-0_108071_2019-06-05_final
2019-06-05 11:06:30	ga_ls8c_ard_3-0-0_108072_2019-06-05_final
2019-06-05 11:06:54	ga_ls8c_ard_3-0-0_108073_2019-06-05_final
2019-06-05 11:07:18	ga_ls8c_ard_3-0-0_108074_2019-06-05_final
2019-06-05 11:07:42	ga_ls8c_ard_3-0-0_108075_2019-06-05_final
2019-06-05 11:08:06	ga_ls8c_ard_3-0-0_108076_2019-06-05_final
2019-06-07 10:56:57	ga_ls8c_ard_3-0-0_106079_2019-06-07_final
2019-06-07 10:57:21	ga_ls8c_ard_3-0-0_106080_2019-06-07_final
2019-06-07 10:57:45	ga_ls8c_ard_3-0-0_106081_2019-06-07_final
2019-06-07 10:58:09	ga_ls8c_ard_3-0-0_106082_2019-06-07_final
2019-06-07 10:58:33	ga_ls8c_ard_3-0-0_106083_2019-06-07_final
2019-06-07 10:58:57	ga_ls8c_ard_3-0-0_106084_2019-06-07_final
2022-10-26 11:12:21	ga_ls8c_ard_3-2-1_109069_2022-10-26_final
2022-10-26 11:12:45	ga_ls8c_ard_3-2-1_109070_2022-10-26_final
2022-10-26 11:13:09	ga_ls8c_ard_3-2-1_109071_2022-10-26_final
2022-10-28 11:02:24	ga_ls8c_ard_3-2-1_107075_2022-10-28_final
2022-10-28 11:02:48	ga_ls8c_ard_3-2-1_107076_2022-10-28_final
2022-10-28 11:03:12	ga_ls8c_ard_3-2-1_107077_2022-10-28_final
2022-10-28 11:03:36	ga_ls8c_ard_3-2-1_107078_2022-10-28_final
2022-10-28 11:04:00	ga_ls8c_ard_3-2-1_107079_2022-10-28_final
2022-10-28 11:04:23	ga_ls8c_ard_3-2-1_107080_2022-10-28_final
2022-10-28 11:04:47	ga_ls8c_ard_3-2-1_107081_2022-10-28_final
2022-10-30 10:53:14	ga_ls8c_ard_3-2-1_105083_2022-10-30_final
2022-11-04 11:06:59	ga_ls8c_ard_3-2-1_108071_2022-11-04_final
2022-11-04 11:07:23	ga_ls8c_ard_3-2-1_108072_2022-11-04_final
2022-11-04 11:07:47	ga_ls8c_ard_3-2-1_108073_2022-11-04_final
2022-11-04 11:08:11	ga_ls8c_ard_3-2-1_108074_2022-11-04_final
2022-11-04 11:08:35	ga_ls8c_ard_3-2-1_108075_2022-11-04_final
2022-11-04 11:08:59	ga_ls8c_ard_3-2-1_108076_2022-11-04_final
2022-11-06 10:57:49	ga_ls8c_ard_3-2-1_106079_2022-11-06_final
2022-11-06 10:58:13	ga_ls8c_ard_3-2-1_106080_2022-11-06_final
2022-11-06 10:58:37	ga_ls8c_ard_3-2-1_106081_2022-11-06_final
2022-11-06 10:59:01	ga_ls8c_ard_3-2-1_106082_2022-11-06_final
2022-11-06 10:59:25	ga_ls8c_ard_3-2-1_106083_2022-11-06_final
2022-11-20 11:06:52	ga_ls8c_ard_3-2-1_108071_2022-11-20_final
2022-11-20 11:07:16	ga_ls8c_ard_3-2-1_108072_2022-11-20_final
2022-11-20 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-11-20_final
2022-11-20 11:08:04	ga_ls8c_ard_3-2-1_108074_2022-11-20_final
2022-11-20 11:08:28	ga_ls8c_ard_3-2-1_108075_2022-11-20_final
2022-11-20 11:08:52	ga_ls8c_ard_3-2-1_108076_2022-11-20_final
2022-11-22 10:57:43	ga_ls8c_ard_3-2-1_106079_2022-11-22_final
2022-11-22 10:58:07	ga_ls8c_ard_3-2-1_106080_2022-11-22_final
2022-11-22 10:58:31	ga_ls8c_ard_3-2-1_106081_2022-11-22_final
2022-11-22 10:58:55	ga_ls8c_ard_3-2-1_106082_2022-11-22_final
2022-11-22 10:59:19	ga_ls8c_ard_3-2-1_106083_2022-11-22_final
2022-11-27 11:12:17	ga_ls8c_ard_3-2-1_109069_2022-11-27_final
2022-11-27 11:12:41	ga_ls8c_ard_3-2-1_109070_2022-11-27_final
2022-11-27 11:13:05	ga_ls8c_ard_3-2-1_109071_2022-11-27_final
2022-11-29 11:02:19	ga_ls8c_ard_3-2-1_107075_2022-11-29_final
2022-11-29 11:02:43	ga_ls8c_ard_3-2-1_107076_2022-11-29_final
2022-11-29 11:03:07	ga_ls8c_ard_3-2-1_107077_2022-11-29_final
2022-11-29 11:03:31	ga_ls8c_ard_3-2-1_107078_2022-11-29_final
2022-11-29 11:03:55	ga_ls8c_ard_3-2-1_107079_2022-11-29_final
2022-11-29 11:04:19	ga_ls8c_ard_3-2-1_107080_2022-11-29_final
2022-11-29 11:04:43	ga_ls8c_ard_3-2-1_107081_2022-11-29_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