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
2019-03-01 11:09:37	ga_ls8c_ard_3-0-0_108080_2019-03-01_final
2019-03-01 11:10:01	ga_ls8c_ard_3-0-0_108081_2019-03-01_final
2019-03-01 11:10:25	ga_ls8c_ard_3-0-0_108082_2019-03-01_final
2019-03-01 11:10:49	ga_ls8c_ard_3-0-0_108083_2019-03-01_final
2019-03-01 11:11:13	ga_ls8c_ard_3-0-0_108084_2019-03-01_final
2019-03-01 11:11:37	ga_ls8c_ard_3-0-0_108085_2019-03-01_final
2019-03-26 11:04:55	ga_ls8c_ard_3-1-0_107084_2019-03-26_final
2019-03-26 11:05:19	ga_ls8c_ard_3-1-0_107085_2019-03-26_final
2019-03-29 11:29:02	ga_ls8c_ard_3-1-0_112067_2019-03-29_final
2019-05-13 11:04:30	ga_ls8c_ard_3-0-0_107083_2019-05-13_final
2019-05-13 11:04:54	ga_ls8c_ard_3-0-0_107084_2019-05-13_final
2019-05-13 11:05:18	ga_ls8c_ard_3-0-0_107085_2019-05-13_final
2019-05-16 11:29:03	ga_ls8c_ard_3-0-0_112067_2019-05-16_final
2022-08-07 11:15:00	ga_ls8c_ard_3-2-1_109076_2022-08-07_final
2022-08-07 11:15:48	ga_ls8c_ard_3-2-1_109078_2022-08-07_final
2022-08-07 11:16:12	ga_ls8c_ard_3-2-1_109079_2022-08-07_final
2022-08-07 11:16:36	ga_ls8c_ard_3-2-1_109080_2022-08-07_final
2022-08-07 11:17:00	ga_ls8c_ard_3-2-1_109081_2022-08-07_final
2022-08-14 11:19:14	ga_ls8c_ard_3-2-1_110071_2022-08-14_final
2022-08-14 11:19:37	ga_ls8c_ard_3-2-1_110072_2022-08-14_final
2022-08-14 11:20:01	ga_ls8c_ard_3-2-1_110073_2022-08-14_final
2022-08-14 11:20:25	ga_ls8c_ard_3-2-1_110074_2022-08-14_final
2022-08-14 11:20:49	ga_ls8c_ard_3-2-1_110075_2022-08-14_final
2022-08-14 11:21:13	ga_ls8c_ard_3-2-1_110076_2022-08-14_final
2022-08-16 11:10:28	ga_ls8c_ard_3-2-1_108080_2022-08-16_final
2022-08-16 11:10:52	ga_ls8c_ard_3-2-1_108081_2022-08-16_final
2022-08-16 11:11:16	ga_ls8c_ard_3-2-1_108082_2022-08-16_final
2022-08-16 11:11:40	ga_ls8c_ard_3-2-1_108083_2022-08-16_final
2022-08-16 11:12:04	ga_ls8c_ard_3-2-1_108084_2022-08-16_final
2022-08-21 11:24:14	ga_ls8c_ard_3-2-1_111068_2022-08-21_final
2022-08-21 11:24:38	ga_ls8c_ard_3-2-1_111069_2022-08-21_final
2022-08-21 11:25:02	ga_ls8c_ard_3-2-1_111070_2022-08-21_final
2022-08-21 11:25:25	ga_ls8c_ard_3-2-1_111071_2022-08-21_final
2022-08-21 11:25:49	ga_ls8c_ard_3-2-1_111072_2022-08-21_final
2022-08-30 11:19:14	ga_ls8c_ard_3-2-1_110071_2022-08-30_final
2022-08-30 11:19:38	ga_ls8c_ard_3-2-1_110072_2022-08-30_final
2022-08-30 11:20:02	ga_ls8c_ard_3-2-1_110073_2022-08-30_final
2022-08-30 11:20:26	ga_ls8c_ard_3-2-1_110074_2022-08-30_final
2022-08-30 11:20:50	ga_ls8c_ard_3-2-1_110075_2022-08-30_final
2022-08-30 11:21:14	ga_ls8c_ard_3-2-1_110076_2022-08-30_final
2022-09-08 11:14:42	ga_ls8c_ard_3-2-1_109075_2022-09-08_final
2022-09-08 11:15:06	ga_ls8c_ard_3-2-1_109076_2022-09-08_final
2022-09-08 11:15:30	ga_ls8c_ard_3-2-1_109077_2022-09-08_final
2022-09-08 11:15:54	ga_ls8c_ard_3-2-1_109078_2022-09-08_final
2022-09-08 11:16:18	ga_ls8c_ard_3-2-1_109079_2022-09-08_final
2022-09-08 11:16:42	ga_ls8c_ard_3-2-1_109080_2022-09-08_final
2022-09-08 11:17:06	ga_ls8c_ard_3-2-1_109081_2022-09-08_final
2022-09-10 11:05:33	ga_ls8c_ard_3-2-1_107083_2022-09-10_final
2022-09-10 11:05:57	ga_ls8c_ard_3-2-1_107084_2022-09-10_final
2022-11-09 11:24:19	ga_ls8c_ard_3-2-1_111068_2022-11-09_final
2022-11-09 11:24:42	ga_ls8c_ard_3-2-1_111069_2022-11-09_final
2022-11-09 11:25:06	ga_ls8c_ard_3-2-1_111070_2022-11-09_final
2022-11-09 11:25:30	ga_ls8c_ard_3-2-1_111071_2022-11-09_final
2022-11-09 11:25:54	ga_ls8c_ard_3-2-1_111072_2022-11-09_final
2022-11-11 11:14:43	ga_ls8c_ard_3-2-1_109075_2022-11-11_final
2022-11-11 11:15:07	ga_ls8c_ard_3-2-1_109076_2022-11-11_final
2022-11-11 11:15:31	ga_ls8c_ard_3-2-1_109077_2022-11-11_final
2022-11-11 11:15:55	ga_ls8c_ard_3-2-1_109078_2022-11-11_final
2022-11-11 11:16:19	ga_ls8c_ard_3-2-1_109079_2022-11-11_final
2022-11-11 11:16:43	ga_ls8c_ard_3-2-1_109080_2022-11-11_final
2022-11-11 11:17:07	ga_ls8c_ard_3-2-1_109081_2022-11-11_final
2022-11-13 11:05:32	ga_ls8c_ard_3-2-1_107083_2022-11-13_final
2022-11-13 11:05:56	ga_ls8c_ard_3-2-1_107084_2022-11-13_final
2022-11-18 11:19:13	ga_ls8c_ard_3-2-1_110071_2022-11-18_final
2022-11-18 11:19:37	ga_ls8c_ard_3-2-1_110072_2022-11-18_final
2022-11-18 11:20:01	ga_ls8c_ard_3-2-1_110073_2022-11-18_final
2022-11-18 11:20:25	ga_ls8c_ard_3-2-1_110074_2022-11-18_final
2022-11-18 11:20:49	ga_ls8c_ard_3-2-1_110075_2022-11-18_final
2022-11-18 11:21:13	ga_ls8c_ard_3-2-1_110076_2022-11-18_final
2022-11-20 11:10:28	ga_ls8c_ard_3-2-1_108080_2022-11-20_final
2022-11-20 11:10:52	ga_ls8c_ard_3-2-1_108081_2022-11-20_final
2022-11-20 11:11:16	ga_ls8c_ard_3-2-1_108082_2022-11-20_final
2022-11-20 11:11:40	ga_ls8c_ard_3-2-1_108083_2022-11-20_final
2022-11-20 11:12:04	ga_ls8c_ard_3-2-1_108084_2022-11-20_final
2022-12-04 11:19:16	ga_ls8c_ard_3-2-1_110071_2022-12-04_final
2022-12-04 11:19:40	ga_ls8c_ard_3-2-1_110072_2022-12-04_final
2022-12-04 11:20:04	ga_ls8c_ard_3-2-1_110073_2022-12-04_final
2022-12-04 11:20:28	ga_ls8c_ard_3-2-1_110074_2022-12-04_final
2022-12-04 11:20:52	ga_ls8c_ard_3-2-1_110075_2022-12-04_final
2022-12-04 11:21:16	ga_ls8c_ard_3-2-1_110076_2022-12-04_final
2022-12-06 11:10:30	ga_ls8c_ard_3-2-1_108080_2022-12-06_final
2022-12-06 11:10:54	ga_ls8c_ard_3-2-1_108081_2022-12-06_final
2022-12-06 11:11:17	ga_ls8c_ard_3-2-1_108082_2022-12-06_final
2022-12-06 11:11:41	ga_ls8c_ard_3-2-1_108083_2022-12-06_final
2022-12-06 11:12:05	ga_ls8c_ard_3-2-1_108084_2022-12-06_final
2022-12-27 11:24:06	ga_ls8c_ard_3-2-1_111068_2022-12-27_final
2022-12-27 11:24:30	ga_ls8c_ard_3-2-1_111069_2022-12-27_final
2022-12-27 11:24:54	ga_ls8c_ard_3-2-1_111070_2022-12-27_final
2022-12-27 11:25:17	ga_ls8c_ard_3-2-1_111071_2022-12-27_final
2022-12-27 11:25:41	ga_ls8c_ard_3-2-1_111072_2022-12-27_final
2023-03-26 11:18:32	ga_ls8c_ard_3-2-1_110071_2023-03-26_final
2023-03-26 11:18:56	ga_ls8c_ard_3-2-1_110072_2023-03-26_final
2023-03-26 11:19:20	ga_ls8c_ard_3-2-1_110073_2023-03-26_final
2023-03-26 11:19:44	ga_ls8c_ard_3-2-1_110074_2023-03-26_final
2023-03-26 11:20:08	ga_ls8c_ard_3-2-1_110075_2023-03-26_final
2023-03-26 11:20:32	ga_ls8c_ard_3-2-1_110076_2023-03-26_final
2023-03-28 11:09:45	ga_ls8c_ard_3-2-1_108080_2023-03-28_final
2023-03-28 11:10:09	ga_ls8c_ard_3-2-1_108081_2023-03-28_final
2023-03-28 11:10:33	ga_ls8c_ard_3-2-1_108082_2023-03-28_final
2023-03-28 11:10:57	ga_ls8c_ard_3-2-1_108083_2023-03-28_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