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
2015-08-31 10:58:35	ga_ls8c_ard_3-0-0_106083_2015-08-31_final
2015-08-31 10:58:59	ga_ls8c_ard_3-0-0_106084_2015-08-31_final
2018-02-03 11:03:14	ga_ls8c_ard_3-0-0_107079_2018-02-03_final
2018-03-07 11:03:00	ga_ls8c_ard_3-0-0_107079_2018-03-07_final
2018-03-07 11:03:24	ga_ls8c_ard_3-0-0_107080_2018-03-07_final
2018-03-07 11:03:48	ga_ls8c_ard_3-0-0_107081_2018-03-07_final
2018-03-07 11:04:12	ga_ls8c_ard_3-1-0_107082_2018-03-07_final
2018-03-07 11:04:36	ga_ls8c_ard_3-0-0_107083_2018-03-07_final
2018-03-07 11:05:00	ga_ls8c_ard_3-0-0_107084_2018-03-07_final
2018-06-18 11:06:28	ga_ls8c_ard_3-0-0_108074_2018-06-18_final
2018-06-18 11:06:52	ga_ls8c_ard_3-0-0_108075_2018-06-18_final
2018-06-18 11:07:16	ga_ls8c_ard_3-0-0_108076_2018-06-18_final
2018-06-18 11:07:40	ga_ls8c_ard_3-0-0_108077_2018-06-18_final
2018-06-18 11:08:04	ga_ls8c_ard_3-0-0_108078_2018-06-18_final
2018-06-18 11:08:28	ga_ls8c_ard_3-0-0_108079_2018-06-18_final
2018-06-18 11:08:52	ga_ls8c_ard_3-0-0_108080_2018-06-18_final
2018-07-04 11:06:38	ga_ls8c_ard_3-0-0_108074_2018-07-04_final
2018-07-04 11:07:01	ga_ls8c_ard_3-0-0_108075_2018-07-04_final
2018-07-04 11:07:25	ga_ls8c_ard_3-0-0_108076_2018-07-04_final
2018-07-04 11:07:49	ga_ls8c_ard_3-0-0_108077_2018-07-04_final
2018-07-04 11:08:13	ga_ls8c_ard_3-0-0_108078_2018-07-04_final
2018-07-04 11:08:37	ga_ls8c_ard_3-0-0_108079_2018-07-04_final
2018-07-04 11:09:01	ga_ls8c_ard_3-0-0_108080_2018-07-04_final
2018-07-22 10:57:59	ga_ls8c_ard_3-0-0_106083_2018-07-22_final
2018-07-22 10:58:23	ga_ls8c_ard_3-0-0_106084_2018-07-22_final
2018-08-05 11:06:53	ga_ls8c_ard_3-0-0_108074_2018-08-05_final
2018-08-05 11:07:17	ga_ls8c_ard_3-0-0_108075_2018-08-05_final
2018-08-05 11:07:41	ga_ls8c_ard_3-0-0_108076_2018-08-05_final
2018-08-05 11:08:05	ga_ls8c_ard_3-0-0_108077_2018-08-05_final
2018-08-05 11:08:29	ga_ls8c_ard_3-0-0_108078_2018-08-05_final
2018-08-05 11:08:53	ga_ls8c_ard_3-0-0_108079_2018-08-05_final
2018-08-05 11:09:17	ga_ls8c_ard_3-0-0_108080_2018-08-05_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
2019-06-05 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
2019-06-05 11:08:30	ga_ls8c_ard_3-0-0_108077_2019-06-05_final
2019-06-05 11:08:54	ga_ls8c_ard_3-0-0_108078_2019-06-05_final
2019-06-05 11:09:18	ga_ls8c_ard_3-0-0_108079_2019-06-05_final
2019-06-05 11:09:42	ga_ls8c_ard_3-0-0_108080_2019-06-05_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
2023-01-05 11:18:19	ga_ls8c_ard_3-2-1_110069_2023-01-05_final
2023-01-05 11:18:43	ga_ls8c_ard_3-2-1_110070_2023-01-05_final
2023-01-05 11:19:07	ga_ls8c_ard_3-2-1_110071_2023-01-05_final
2023-01-07 11:07:57	ga_ls8c_ard_3-2-1_108074_2023-01-07_final
2023-01-07 11:08:21	ga_ls8c_ard_3-2-1_108075_2023-01-07_final
2023-01-07 11:08:45	ga_ls8c_ard_3-2-1_108076_2023-01-07_final
2023-01-07 11:09:09	ga_ls8c_ard_3-2-1_108077_2023-01-07_final
2023-01-07 11:09:33	ga_ls8c_ard_3-2-1_108078_2023-01-07_final
2023-01-07 11:09:57	ga_ls8c_ard_3-2-1_108079_2023-01-07_final
2023-01-07 11:10:20	ga_ls8c_ard_3-2-1_108080_2023-01-07_final
2023-01-14 11:12:28	ga_ls8c_ard_3-2-1_109070_2023-01-14_final
2023-01-14 11:12:52	ga_ls8c_ard_3-2-1_109071_2023-01-14_final
2023-01-14 11:13:16	ga_ls8c_ard_3-2-1_109072_2023-01-14_final
2023-01-14 11:13:40	ga_ls8c_ard_3-2-1_109073_2023-01-14_final
2023-01-14 11:14:03	ga_ls8c_ard_3-2-1_109074_2023-01-14_final
2023-01-14 11:14:27	ga_ls8c_ard_3-2-1_109075_2023-01-14_final
2023-01-16 11:03:40	ga_ls8c_ard_3-2-1_107079_2023-01-16_final
2023-01-16 11:04:03	ga_ls8c_ard_3-2-1_107080_2023-01-16_final
2023-01-16 11:04:27	ga_ls8c_ard_3-2-1_107081_2023-01-16_final
2023-01-16 11:04:51	ga_ls8c_ard_3-2-1_107082_2023-01-16_final
2023-01-16 11:05:15	ga_ls8c_ard_3-2-1_107083_2023-01-16_final
2023-01-16 11:05:39	ga_ls8c_ard_3-2-1_107084_2023-01-16_final
2023-01-25 10:59:08	ga_ls8c_ard_3-2-1_106083_2023-01-25_final
2023-02-01 11:03:45	ga_ls8c_ard_3-2-1_107079_2023-02-01_final
2023-02-01 11:04:08	ga_ls8c_ard_3-2-1_107080_2023-02-01_final
2023-02-01 11:04:32	ga_ls8c_ard_3-2-1_107081_2023-02-01_final
2023-02-01 11:04:56	ga_ls8c_ard_3-2-1_107082_2023-02-01_final
2023-02-01 11:05:20	ga_ls8c_ard_3-2-1_107083_2023-02-01_final
2023-02-01 11:05:44	ga_ls8c_ard_3-2-1_107084_2023-02-01_final
2023-02-08 11:07:54	ga_ls8c_ard_3-2-1_108074_2023-02-08_final
2023-02-08 11:08:18	ga_ls8c_ard_3-2-1_108075_2023-02-08_final
2023-02-08 11:08:42	ga_ls8c_ard_3-2-1_108076_2023-02-08_final
2023-02-08 11:09:06	ga_ls8c_ard_3-2-1_108077_2023-02-08_final
2023-02-08 11:09:30	ga_ls8c_ard_3-2-1_108078_2023-02-08_final
2023-02-08 11:09:54	ga_ls8c_ard_3-2-1_108079_2023-02-08_final
2023-02-08 11:10:18	ga_ls8c_ard_3-2-1_108080_2023-02-08_final
2023-02-24 11:08:01	ga_ls8c_ard_3-2-1_108075_2023-02-24_final
2023-02-24 11:08:25	ga_ls8c_ard_3-2-1_108076_2023-02-24_final
2023-02-24 11:08:49	ga_ls8c_ard_3-2-1_108077_2023-02-24_final
2023-02-24 11:09:13	ga_ls8c_ard_3-2-1_108078_2023-02-24_final
2023-02-24 11:09:37	ga_ls8c_ard_3-2-1_108079_2023-02-24_final
2023-02-24 11:10:01	ga_ls8c_ard_3-2-1_108080_2023-02-24_final
2023-02-26 10:58:50	ga_ls8c_ard_3-2-1_106083_2023-02-26_final
2023-06-02 10:58:05	ga_ls8c_ard_3-2-1_106083_2023-06-02_final
2023-08-21 10:58:45	ga_ls8c_ard_3-2-1_106083_2023-08-21_final
2023-09-04 11:07:31	ga_ls8c_ard_3-2-1_108074_2023-09-04_final
2023-09-04 11:07:55	ga_ls8c_ard_3-2-1_108075_2023-09-04_final
2023-09-04 11:08:19	ga_ls8c_ard_3-2-1_108076_2023-09-04_final
2023-09-04 11:08:43	ga_ls8c_ard_3-2-1_108077_2023-09-04_final
2023-09-04 11:09:07	ga_ls8c_ard_3-2-1_108078_2023-09-04_final
2023-09-04 11:09:31	ga_ls8c_ard_3-2-1_108079_2023-09-04_final
2023-09-04 11:09:55	ga_ls8c_ard_3-2-1_108080_2023-09-04_final
2023-10-13 11:12:18	ga_ls8c_ard_3-2-1_109070_2023-10-13_final
2023-10-13 11:12:42	ga_ls8c_ard_3-2-1_109071_2023-10-13_final
2023-10-13 11:13:06	ga_ls8c_ard_3-2-1_109072_2023-10-13_final
2023-10-13 11:13:30	ga_ls8c_ard_3-2-1_109073_2023-10-13_final
2023-10-13 11:13:54	ga_ls8c_ard_3-2-1_109074_2023-10-13_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