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
2015-05-16 11:14:20	ga_ls8c_ard_3-0-0_109078_2015-05-16_final
2015-05-16 11:14:44	ga_ls8c_ard_3-0-0_109079_2015-05-16_final
2015-05-16 11:15:08	ga_ls8c_ard_3-0-0_109080_2015-05-16_final
2015-05-16 11:15:32	ga_ls8c_ard_3-0-0_109081_2015-05-16_final
2015-05-16 11:15:56	ga_ls8c_ard_3-0-0_109082_2015-05-16_final
2015-05-16 11:16:20	ga_ls8c_ard_3-0-0_109083_2015-05-16_final
2015-05-18 11:04:47	ga_ls8c_ard_3-0-0_107085_2015-05-18_final
2017-04-19 11:14:44	ga_ls8c_ard_3-0-0_109078_2017-04-19_final
2017-04-19 11:15:08	ga_ls8c_ard_3-0-0_109079_2017-04-19_final
2017-04-19 11:15:32	ga_ls8c_ard_3-0-0_109080_2017-04-19_final
2017-04-19 11:15:56	ga_ls8c_ard_3-0-0_109081_2017-04-19_final
2017-04-19 11:16:20	ga_ls8c_ard_3-0-0_109082_2017-04-19_final
2017-04-19 11:16:44	ga_ls8c_ard_3-0-0_109083_2017-04-19_final
2017-04-28 11:10:03	ga_ls8c_ard_3-0-0_108082_2017-04-28_final
2017-04-28 11:10:27	ga_ls8c_ard_3-0-0_108083_2017-04-28_final
2017-04-28 11:10:51	ga_ls8c_ard_3-0-0_108084_2017-04-28_final
2017-04-28 11:11:15	ga_ls8c_ard_3-0-0_108085_2017-04-28_final
2017-06-04 11:23:43	ga_ls8c_ard_3-0-0_111069_2017-06-04_final
2017-06-04 11:24:07	ga_ls8c_ard_3-0-0_111070_2017-06-04_final
2017-06-04 11:24:31	ga_ls8c_ard_3-0-0_111071_2017-06-04_final
2017-06-04 11:24:55	ga_ls8c_ard_3-0-0_111072_2017-06-04_final
2017-06-04 11:25:19	ga_ls8c_ard_3-0-0_111073_2017-06-04_final
2017-06-04 11:25:43	ga_ls8c_ard_3-0-0_111074_2017-06-04_final
2017-07-22 11:23:59	ga_ls8c_ard_3-0-0_111069_2017-07-22_final
2017-07-22 11:24:22	ga_ls8c_ard_3-0-0_111070_2017-07-22_final
2017-07-22 11:24:46	ga_ls8c_ard_3-0-0_111071_2017-07-22_final
2017-07-22 11:25:10	ga_ls8c_ard_3-0-0_111072_2017-07-22_final
2017-07-22 11:25:34	ga_ls8c_ard_3-0-0_111073_2017-07-22_final
2017-07-22 11:25:58	ga_ls8c_ard_3-0-0_111074_2017-07-22_final
2017-08-16 11:19:33	ga_ls8c_ard_3-0-0_110073_2017-08-16_final
2017-08-16 11:19:57	ga_ls8c_ard_3-0-0_110074_2017-08-16_final
2017-08-16 11:20:21	ga_ls8c_ard_3-0-0_110075_2017-08-16_final
2017-08-16 11:20:45	ga_ls8c_ard_3-0-0_110076_2017-08-16_final
2017-08-16 11:21:09	ga_ls8c_ard_3-0-0_110077_2017-08-16_final
2017-08-16 11:21:33	ga_ls8c_ard_3-0-0_110078_2017-08-16_final
2017-08-16 11:21:57	ga_ls8c_ard_3-0-0_110079_2017-08-16_final
2017-08-18 11:10:48	ga_ls8c_ard_3-0-0_108082_2017-08-18_final
2017-08-18 11:11:12	ga_ls8c_ard_3-0-0_108083_2017-08-18_final
2017-08-18 11:11:36	ga_ls8c_ard_3-0-0_108084_2017-08-18_final
2017-08-18 11:12:00	ga_ls8c_ard_3-0-0_108085_2017-08-18_final
2018-03-12 11:19:30	ga_ls8c_ard_3-0-0_110074_2018-03-12_final
2018-03-12 11:19:54	ga_ls8c_ard_3-0-0_110075_2018-03-12_final
2018-03-12 11:20:18	ga_ls8c_ard_3-0-0_110076_2018-03-12_final
2018-03-12 11:20:42	ga_ls8c_ard_3-0-0_110077_2018-03-12_final
2018-03-12 11:21:06	ga_ls8c_ard_3-0-0_110078_2018-03-12_final
2018-03-12 11:21:30	ga_ls8c_ard_3-0-0_110079_2018-03-12_final
2018-03-14 11:10:19	ga_ls8c_ard_3-0-0_108082_2018-03-14_final
2018-03-14 11:10:43	ga_ls8c_ard_3-0-0_108083_2018-03-14_final
2018-03-14 11:11:07	ga_ls8c_ard_3-0-0_108084_2018-03-14_final
2018-03-14 11:11:31	ga_ls8c_ard_3-0-0_108085_2018-03-14_final
2018-05-17 11:09:44	ga_ls8c_ard_3-0-0_108082_2018-05-17_final
2018-05-17 11:10:08	ga_ls8c_ard_3-0-0_108083_2018-05-17_final
2018-05-17 11:10:32	ga_ls8c_ard_3-0-0_108084_2018-05-17_final
2018-05-17 11:10:55	ga_ls8c_ard_3-0-0_108085_2018-05-17_final
2023-04-11 11:19:28	ga_ls8c_ard_3-2-1_110074_2023-04-11_final
2023-04-11 11:19:52	ga_ls8c_ard_3-2-1_110075_2023-04-11_final
2023-04-11 11:20:16	ga_ls8c_ard_3-2-1_110076_2023-04-11_final
2023-04-11 11:20:40	ga_ls8c_ard_3-2-1_110077_2023-04-11_final
2023-04-11 11:21:04	ga_ls8c_ard_3-2-1_110078_2023-04-11_final
2023-04-11 11:21:28	ga_ls8c_ard_3-2-1_110079_2023-04-11_final
2023-04-13 11:10:18	ga_ls8c_ard_3-2-1_108082_2023-04-13_final
2023-04-13 11:10:42	ga_ls8c_ard_3-2-1_108083_2023-04-13_final
2023-04-13 11:11:06	ga_ls8c_ard_3-2-1_108084_2023-04-13_final
2023-04-18 11:23:37	ga_ls8c_ard_3-2-1_111069_2023-04-18_final
2023-04-18 11:24:01	ga_ls8c_ard_3-2-1_111070_2023-04-18_final
2023-04-18 11:24:25	ga_ls8c_ard_3-2-1_111071_2023-04-18_final
2023-04-18 11:24:49	ga_ls8c_ard_3-2-1_111072_2023-04-18_final
2023-04-18 11:25:13	ga_ls8c_ard_3-2-1_111073_2023-04-18_final
2023-04-18 11:25:37	ga_ls8c_ard_3-2-1_111074_2023-04-18_final
2023-04-20 11:14:50	ga_ls8c_ard_3-2-1_109078_2023-04-20_final
2023-04-20 11:15:14	ga_ls8c_ard_3-2-1_109079_2023-04-20_final
2023-04-20 11:15:37	ga_ls8c_ard_3-2-1_109080_2023-04-20_final
2023-04-20 11:16:01	ga_ls8c_ard_3-2-1_109081_2023-04-20_final
2023-04-20 11:16:25	ga_ls8c_ard_3-2-1_109082_2023-04-20_final
2023-04-20 11:16:49	ga_ls8c_ard_3-2-1_109083_2023-04-20_final
2023-06-14 11:19:21	ga_ls8c_ard_3-2-1_110074_2023-06-14_final
2023-06-14 11:19:45	ga_ls8c_ard_3-2-1_110075_2023-06-14_final
2023-06-14 11:20:09	ga_ls8c_ard_3-2-1_110076_2023-06-14_final
2023-06-14 11:20:33	ga_ls8c_ard_3-2-1_110077_2023-06-14_final
2023-06-14 11:20:57	ga_ls8c_ard_3-2-1_110078_2023-06-14_final
2023-06-16 11:10:12	ga_ls8c_ard_3-2-1_108082_2023-06-16_final
2023-06-16 11:10:36	ga_ls8c_ard_3-2-1_108083_2023-06-16_final
2023-06-16 11:11:00	ga_ls8c_ard_3-2-1_108084_2023-06-16_final
2023-06-21 11:23:33	ga_ls8c_ard_3-2-1_111069_2023-06-21_final
2023-06-21 11:23:57	ga_ls8c_ard_3-2-1_111070_2023-06-21_final
2023-06-21 11:24:21	ga_ls8c_ard_3-2-1_111071_2023-06-21_final
2023-06-21 11:24:45	ga_ls8c_ard_3-2-1_111072_2023-06-21_final
2023-06-21 11:25:09	ga_ls8c_ard_3-2-1_111073_2023-06-21_final
2023-06-21 11:25:33	ga_ls8c_ard_3-2-1_111074_2023-06-21_final
2023-06-23 11:14:48	ga_ls8c_ard_3-2-1_109078_2023-06-23_final
2023-06-23 11:15:11	ga_ls8c_ard_3-2-1_109079_2023-06-23_final
2023-06-23 11:15:35	ga_ls8c_ard_3-2-1_109080_2023-06-23_final
2023-06-23 11:15:59	ga_ls8c_ard_3-2-1_109081_2023-06-23_final
2023-06-23 11:16:23	ga_ls8c_ard_3-2-1_109082_2023-06-23_final
2023-06-23 11:16:47	ga_ls8c_ard_3-2-1_109083_2023-06-23_final
2023-08-10 11:15:10	ga_ls8c_ard_3-2-1_109078_2023-08-10_final
2023-08-10 11:15:34	ga_ls8c_ard_3-2-1_109079_2023-08-10_final
2023-08-10 11:15:58	ga_ls8c_ard_3-2-1_109080_2023-08-10_final
2023-08-10 11:16:22	ga_ls8c_ard_3-2-1_109081_2023-08-10_final
2023-08-10 11:16:46	ga_ls8c_ard_3-2-1_109082_2023-08-10_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