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
2013-03-31 11:12:49	ga_ls8c_ard_3-0-0_108080_2013-03-31_final
2013-03-31 11:13:13	ga_ls8c_ard_3-0-0_108081_2013-03-31_final
2013-03-31 11:13:37	ga_ls8c_ard_3-0-0_108082_2013-03-31_final
2013-07-27 11:25:17	ga_ls8c_ard_3-0-0_111067_2013-07-27_final
2013-07-27 11:25:40	ga_ls8c_ard_3-0-0_111068_2013-07-27_final
2013-07-27 11:26:52	ga_ls8c_ard_3-0-0_111071_2013-07-27_final
2013-07-27 11:27:16	ga_ls8c_ard_3-0-0_111072_2013-07-27_final
2013-07-27 11:27:40	ga_ls8c_ard_3-0-0_111073_2013-07-27_final
2013-08-03 11:31:29	ga_ls8c_ard_3-0-0_112067_2013-08-03_final
2013-10-31 11:25:01	ga_ls8c_ard_3-0-0_111067_2013-10-31_final
2013-10-31 11:25:25	ga_ls8c_ard_3-0-0_111068_2013-10-31_final
2013-10-31 11:25:49	ga_ls8c_ard_3-0-0_111069_2013-10-31_final
2013-10-31 11:26:13	ga_ls8c_ard_3-0-0_111070_2013-10-31_final
2013-10-31 11:26:37	ga_ls8c_ard_3-0-0_111071_2013-10-31_final
2013-10-31 11:27:01	ga_ls8c_ard_3-0-0_111072_2013-10-31_final
2013-10-31 11:27:25	ga_ls8c_ard_3-0-0_111073_2013-10-31_final
2022-05-10 11:19:00	ga_ls8c_ard_3-2-1_110072_2022-05-10_final
2022-05-10 11:19:24	ga_ls8c_ard_3-2-1_110073_2022-05-10_final
2022-05-10 11:19:48	ga_ls8c_ard_3-2-1_110074_2022-05-10_final
2022-05-10 11:20:12	ga_ls8c_ard_3-2-1_110075_2022-05-10_final
2022-05-10 11:20:36	ga_ls8c_ard_3-2-1_110076_2022-05-10_final
2022-05-10 11:21:00	ga_ls8c_ard_3-2-1_110077_2022-05-10_final
2022-05-12 11:10:15	ga_ls8c_ard_3-2-1_108081_2022-05-12_final
2022-05-12 11:10:39	ga_ls8c_ard_3-2-1_108082_2022-05-12_final
2022-05-12 11:11:03	ga_ls8c_ard_3-2-1_108083_2022-05-12_final
2022-05-12 11:11:27	ga_ls8c_ard_3-2-1_108084_2022-05-12_final
2022-05-21 11:05:18	ga_ls8c_ard_3-2-1_107084_2022-05-21_final
2022-05-26 11:19:02	ga_ls8c_ard_3-2-1_110072_2022-05-26_final
2022-05-26 11:19:26	ga_ls8c_ard_3-2-1_110073_2022-05-26_final
2022-05-26 11:19:50	ga_ls8c_ard_3-2-1_110074_2022-05-26_final
2022-05-26 11:20:14	ga_ls8c_ard_3-2-1_110075_2022-05-26_final
2022-05-26 11:20:38	ga_ls8c_ard_3-2-1_110076_2022-05-26_final
2022-05-26 11:21:02	ga_ls8c_ard_3-2-1_110077_2022-05-26_final
2022-09-17 11:10:59	ga_ls8c_ard_3-2-1_108081_2022-09-17_final
2022-09-17 11:11:23	ga_ls8c_ard_3-2-1_108082_2022-09-17_final
2022-09-17 11:11:46	ga_ls8c_ard_3-2-1_108083_2022-09-17_final
2022-09-17 11:12:10	ga_ls8c_ard_3-2-1_108084_2022-09-17_final
2022-09-22 11:24:21	ga_ls8c_ard_3-2-1_111068_2022-09-22_final
2022-09-22 11:24:44	ga_ls8c_ard_3-2-1_111069_2022-09-22_final
2022-09-22 11:25:08	ga_ls8c_ard_3-2-1_111070_2022-09-22_final
2022-09-22 11:25:32	ga_ls8c_ard_3-2-1_111071_2022-09-22_final
2022-09-22 11:25:56	ga_ls8c_ard_3-2-1_111072_2022-09-22_final
2022-09-22 11:26:20	ga_ls8c_ard_3-2-1_111073_2022-09-22_final
2022-09-24 11:15:10	ga_ls8c_ard_3-2-1_109076_2022-09-24_final
2022-09-24 11:15:34	ga_ls8c_ard_3-2-1_109077_2022-09-24_final
2022-09-24 11:15:58	ga_ls8c_ard_3-2-1_109078_2022-09-24_final
2022-09-24 11:16:22	ga_ls8c_ard_3-2-1_109079_2022-09-24_final
2022-09-24 11:16:46	ga_ls8c_ard_3-2-1_109080_2022-09-24_final
2022-09-24 11:17:10	ga_ls8c_ard_3-2-1_109081_2022-09-24_final
2022-09-24 11:17:34	ga_ls8c_ard_3-2-1_109082_2022-09-24_final
2022-10-01 11:19:44	ga_ls8c_ard_3-2-1_110072_2022-10-01_final
2022-10-01 11:20:08	ga_ls8c_ard_3-2-1_110073_2022-10-01_final
2022-10-01 11:20:32	ga_ls8c_ard_3-2-1_110074_2022-10-01_final
2022-10-01 11:20:56	ga_ls8c_ard_3-2-1_110075_2022-10-01_final
2022-10-01 11:21:20	ga_ls8c_ard_3-2-1_110076_2022-10-01_final
2022-10-01 11:21:44	ga_ls8c_ard_3-2-1_110077_2022-10-01_final
2022-10-03 11:10:58	ga_ls8c_ard_3-2-1_108081_2022-10-03_final
2022-10-03 11:11:22	ga_ls8c_ard_3-2-1_108082_2022-10-03_final
2022-10-03 11:11:46	ga_ls8c_ard_3-2-1_108083_2022-10-03_final
2022-10-03 11:12:10	ga_ls8c_ard_3-2-1_108084_2022-10-03_final
2022-10-10 11:15:04	ga_ls8c_ard_3-2-1_109076_2022-10-10_final
2022-10-10 11:15:28	ga_ls8c_ard_3-2-1_109077_2022-10-10_final
2022-10-10 11:15:52	ga_ls8c_ard_3-2-1_109078_2022-10-10_final
2022-10-10 11:16:16	ga_ls8c_ard_3-2-1_109079_2022-10-10_final
2022-10-10 11:16:40	ga_ls8c_ard_3-2-1_109080_2022-10-10_final
2022-10-10 11:17:04	ga_ls8c_ard_3-2-1_109081_2022-10-10_final
2022-10-10 11:17:28	ga_ls8c_ard_3-2-1_109082_2022-10-10_final
2022-10-17 11:19:39	ga_ls8c_ard_3-2-1_110072_2022-10-17_final
2022-10-17 11:20:02	ga_ls8c_ard_3-2-1_110073_2022-10-17_final
2022-10-17 11:20:26	ga_ls8c_ard_3-2-1_110074_2022-10-17_final
2022-10-17 11:20:50	ga_ls8c_ard_3-2-1_110075_2022-10-17_final
2022-10-17 11:21:14	ga_ls8c_ard_3-2-1_110076_2022-10-17_final
2022-10-17 11:21:38	ga_ls8c_ard_3-2-1_110077_2022-10-17_final
2022-10-17 11:22:02	ga_ls8c_ard_3-2-1_110078_2022-10-17_final
2022-10-24 11:24:18	ga_ls8c_ard_3-2-1_111068_2022-10-24_final
2022-10-24 11:24:42	ga_ls8c_ard_3-2-1_111069_2022-10-24_final
2022-10-24 11:25:06	ga_ls8c_ard_3-2-1_111070_2022-10-24_final
2022-10-24 11:25:30	ga_ls8c_ard_3-2-1_111071_2022-10-24_final
2022-10-24 11:25:54	ga_ls8c_ard_3-2-1_111072_2022-10-24_final
2022-10-24 11:26:18	ga_ls8c_ard_3-2-1_111073_2022-10-24_final
2022-10-26 11:15:09	ga_ls8c_ard_3-2-1_109076_2022-10-26_final
2022-10-26 11:15:33	ga_ls8c_ard_3-2-1_109077_2022-10-26_final
2022-10-26 11:15:57	ga_ls8c_ard_3-2-1_109078_2022-10-26_final
2022-10-26 11:16:20	ga_ls8c_ard_3-2-1_109079_2022-10-26_final
2022-10-26 11:16:44	ga_ls8c_ard_3-2-1_109080_2022-10-26_final
2022-10-26 11:17:08	ga_ls8c_ard_3-2-1_109081_2022-10-26_final
2022-10-26 11:17:32	ga_ls8c_ard_3-2-1_109082_2022-10-26_final
2022-10-28 11:05:59	ga_ls8c_ard_3-2-1_107084_2022-10-28_final
2023-10-31 11:05:34	ga_ls8c_ard_3-2-1_107084_2023-10-31_final
2023-11-07 11:10:30	ga_ls8c_ard_3-2-1_108081_2023-11-07_final
2023-11-07 11:10:54	ga_ls8c_ard_3-2-1_108082_2023-11-07_final
2023-11-07 11:11:18	ga_ls8c_ard_3-2-1_108083_2023-11-07_final
2023-11-07 11:11:42	ga_ls8c_ard_3-2-1_108084_2023-11-07_final
2024-01-03 11:05:27	ga_ls8c_ard_3-2-1_107084_2024-01-03_final
2024-01-08 11:19:12	ga_ls8c_ard_3-2-1_110072_2024-01-08_final
2024-01-08 11:19:36	ga_ls8c_ard_3-2-1_110073_2024-01-08_final
2024-01-08 11:20:00	ga_ls8c_ard_3-2-1_110074_2024-01-08_final
2024-01-08 11:20:24	ga_ls8c_ard_3-2-1_110075_2024-01-08_final
2024-01-08 11:20:48	ga_ls8c_ard_3-2-1_110076_2024-01-08_final
2024-01-08 11:21:12	ga_ls8c_ard_3-2-1_110077_2024-01-08_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