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
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
2023-10-22 11:07:42	ga_ls8c_ard_3-2-1_108074_2023-10-22_final
2023-10-22 11:08:06	ga_ls8c_ard_3-2-1_108075_2023-10-22_final
2023-10-22 11:08:30	ga_ls8c_ard_3-2-1_108076_2023-10-22_final
2023-10-22 11:08:54	ga_ls8c_ard_3-2-1_108077_2023-10-22_final
2023-10-22 11:09:18	ga_ls8c_ard_3-2-1_108078_2023-10-22_final
2023-10-22 11:09:42	ga_ls8c_ard_3-2-1_108079_2023-10-22_final
2023-10-22 11:10:06	ga_ls8c_ard_3-2-1_108080_2023-10-22_final
2023-10-22 11:10:30	ga_ls8c_ard_3-2-1_108081_2023-10-22_final
2023-10-22 11:10:54	ga_ls8c_ard_3-2-1_108082_2023-10-22_final
2023-10-22 11:11:18	ga_ls8c_ard_3-2-1_108083_2023-10-22_final
2023-10-22 11:11:42	ga_ls8c_ard_3-2-1_108084_2023-10-22_final
2023-10-24 10:58:34	ga_ls8c_ard_3-2-1_106082_2023-10-24_final
2023-10-24 10:58:58	ga_ls8c_ard_3-2-1_106083_2023-10-24_final
2023-10-31 11:03:35	ga_ls8c_ard_3-2-1_107079_2023-10-31_final
2023-10-31 11:03:59	ga_ls8c_ard_3-2-1_107080_2023-10-31_final
2023-10-31 11:04:46	ga_ls8c_ard_3-2-1_107082_2023-10-31_final
2023-10-31 11:05:10	ga_ls8c_ard_3-2-1_107083_2023-10-31_final
2023-10-31 11:05:34	ga_ls8c_ard_3-2-1_107084_2023-10-31_final
2023-11-03 11:31:41	ga_ls8c_ard_3-2-1_112072_2023-11-03_final
2023-11-05 11:18:06	ga_ls8c_ard_3-2-1_110069_2023-11-05_final
2023-11-05 11:18:30	ga_ls8c_ard_3-2-1_110070_2023-11-05_final
2023-11-05 11:18:54	ga_ls8c_ard_3-2-1_110071_2023-11-05_final
2023-11-05 11:19:18	ga_ls8c_ard_3-2-1_110072_2023-11-05_final
2023-11-05 11:19:42	ga_ls8c_ard_3-2-1_110073_2023-11-05_final
2023-11-05 11:20:06	ga_ls8c_ard_3-2-1_110074_2023-11-05_final
2023-11-05 11:20:30	ga_ls8c_ard_3-2-1_110075_2023-11-05_final
2023-11-05 11:20:54	ga_ls8c_ard_3-2-1_110076_2023-11-05_final
2023-11-05 11:21:18	ga_ls8c_ard_3-2-1_110077_2023-11-05_final
2023-11-05 11:21:42	ga_ls8c_ard_3-2-1_110078_2023-11-05_final
2023-11-05 11:22:06	ga_ls8c_ard_3-2-1_110079_2023-11-05_final
2023-11-05 11:22:30	ga_ls8c_ard_3-2-1_110080_2023-11-05_final
2023-11-05 11:22:54	ga_ls8c_ard_3-2-1_110081_2023-11-05_final
2023-11-07 11:07:43	ga_ls8c_ard_3-2-1_108074_2023-11-07_final
2023-11-07 11:08:31	ga_ls8c_ard_3-2-1_108076_2023-11-07_final
2023-11-07 11:08:55	ga_ls8c_ard_3-2-1_108077_2023-11-07_final
2023-11-07 11:09:18	ga_ls8c_ard_3-2-1_108078_2023-11-07_final
2023-11-07 11:09:42	ga_ls8c_ard_3-2-1_108079_2023-11-07_final
2023-11-07 11:10:06	ga_ls8c_ard_3-2-1_108080_2023-11-07_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
2023-11-12 11:25:02	ga_ls8c_ard_3-2-1_111071_2023-11-12_final
2023-11-12 11:25:26	ga_ls8c_ard_3-2-1_111072_2023-11-12_final
2023-11-12 11:25:50	ga_ls8c_ard_3-2-1_111073_2023-11-12_final
2023-11-12 11:26:14	ga_ls8c_ard_3-2-1_111074_2023-11-12_final
2023-11-12 11:26:38	ga_ls8c_ard_3-2-1_111075_2023-11-12_final
2023-11-12 11:27:02	ga_ls8c_ard_3-2-1_111076_2023-11-12_final
2023-11-12 11:27:26	ga_ls8c_ard_3-2-1_111077_2023-11-12_final
2023-11-14 11:11:55	ga_ls8c_ard_3-2-1_109069_2023-11-14_final
2023-11-14 11:12:18	ga_ls8c_ard_3-2-1_109070_2023-11-14_final
2023-11-14 11:12:42	ga_ls8c_ard_3-2-1_109071_2023-11-14_final
2023-11-14 11:13:06	ga_ls8c_ard_3-2-1_109072_2023-11-14_final
2023-11-14 11:13:30	ga_ls8c_ard_3-2-1_109073_2023-11-14_final
2023-11-14 11:13:54	ga_ls8c_ard_3-2-1_109074_2023-11-14_final
2023-11-14 11:14:18	ga_ls8c_ard_3-2-1_109075_2023-11-14_final
2023-11-14 11:14:42	ga_ls8c_ard_3-2-1_109076_2023-11-14_final
2023-11-14 11:15:06	ga_ls8c_ard_3-2-1_109077_2023-11-14_final
2023-11-14 11:15:30	ga_ls8c_ard_3-2-1_109078_2023-11-14_final
2023-11-14 11:15:54	ga_ls8c_ard_3-2-1_109079_2023-11-14_final
2023-11-14 11:16:18	ga_ls8c_ard_3-2-1_109080_2023-11-14_final
2023-11-14 11:16:42	ga_ls8c_ard_3-2-1_109081_2023-11-14_final
2023-11-14 11:17:06	ga_ls8c_ard_3-2-1_109082_2023-11-14_final
2023-11-14 11:17:30	ga_ls8c_ard_3-2-1_109083_2023-11-14_final
2023-11-14 11:17:54	ga_ls8c_ard_3-2-1_109084_2023-11-14_final
2023-11-16 11:03:10	ga_ls8c_ard_3-2-1_107078_2023-11-16_final
2023-11-16 11:03:34	ga_ls8c_ard_3-2-1_107079_2023-11-16_final
2023-11-16 11:03:58	ga_ls8c_ard_3-2-1_107080_2023-11-16_final
2023-11-16 11:04:22	ga_ls8c_ard_3-2-1_107081_2023-11-16_final
2023-11-16 11:04:45	ga_ls8c_ard_3-2-1_107082_2023-11-16_final
2023-11-16 11:05:09	ga_ls8c_ard_3-2-1_107083_2023-11-16_final
2023-11-16 11:05:33	ga_ls8c_ard_3-2-1_107084_2023-11-16_final
2023-11-19 11:31:42	ga_ls8c_ard_3-2-1_112072_2023-11-19_final
2023-11-21 11:18:09	ga_ls8c_ard_3-2-1_110069_2023-11-21_final
2023-11-21 11:18:33	ga_ls8c_ard_3-2-1_110070_2023-11-21_final
2023-11-21 11:18:57	ga_ls8c_ard_3-2-1_110071_2023-11-21_final
2023-11-21 11:19:21	ga_ls8c_ard_3-2-1_110072_2023-11-21_final
2023-11-21 11:19:45	ga_ls8c_ard_3-2-1_110073_2023-11-21_final
2023-11-21 11:20:09	ga_ls8c_ard_3-2-1_110074_2023-11-21_final
2023-11-21 11:20:33	ga_ls8c_ard_3-2-1_110075_2023-11-21_final
2023-11-21 11:20:57	ga_ls8c_ard_3-2-1_110076_2023-11-21_final
2023-11-21 11:21:21	ga_ls8c_ard_3-2-1_110077_2023-11-21_final
2023-11-21 11:21:45	ga_ls8c_ard_3-2-1_110078_2023-11-21_final
2023-11-21 11:22:08	ga_ls8c_ard_3-2-1_110079_2023-11-21_final
2023-11-21 11:22:32	ga_ls8c_ard_3-2-1_110080_2023-11-21_final
2023-11-21 11:22:56	ga_ls8c_ard_3-2-1_110081_2023-11-21_final
2023-11-23 11:07:48	ga_ls8c_ard_3-2-1_108074_2023-11-23_final
2023-11-23 11:08:12	ga_ls8c_ard_3-2-1_108075_2023-11-23_final
2023-11-23 11:08:35	ga_ls8c_ard_3-2-1_108076_2023-11-23_final
2023-11-23 11:08:59	ga_ls8c_ard_3-2-1_108077_2023-11-23_final
2023-11-23 11:09:23	ga_ls8c_ard_3-2-1_108078_2023-11-23_final
2023-11-23 11:09:47	ga_ls8c_ard_3-2-1_108079_2023-11-23_final
2023-11-23 11:10:11	ga_ls8c_ard_3-2-1_108080_2023-11-23_final
2023-11-23 11:10:35	ga_ls8c_ard_3-2-1_108081_2023-11-23_final
2023-11-23 11:10:59	ga_ls8c_ard_3-2-1_108082_2023-11-23_final
2023-11-23 11:11:23	ga_ls8c_ard_3-2-1_108083_2023-11-23_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