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
2022-07-15 11:09:21	ga_ls8c_ard_3-2-1_108078_2022-07-15_final
2022-07-15 11:09:45	ga_ls8c_ard_3-2-1_108079_2022-07-15_final
2022-07-15 11:10:09	ga_ls8c_ard_3-2-1_108080_2022-07-15_final
2022-07-15 11:10:33	ga_ls8c_ard_3-2-1_108081_2022-07-15_final
2022-07-15 11:10:57	ga_ls8c_ard_3-2-1_108082_2022-07-15_final
2022-07-15 11:11:21	ga_ls8c_ard_3-2-1_108083_2022-07-15_final
2022-07-15 11:11:45	ga_ls8c_ard_3-2-1_108084_2022-07-15_final
2022-07-20 11:23:58	ga_ls8c_ard_3-2-1_111068_2022-07-20_final
2022-07-20 11:24:22	ga_ls8c_ard_3-2-1_111069_2022-07-20_final
2022-07-20 11:24:46	ga_ls8c_ard_3-2-1_111070_2022-07-20_final
2022-07-22 11:14:02	ga_ls8c_ard_3-2-1_109074_2022-07-22_final
2022-07-22 11:14:26	ga_ls8c_ard_3-2-1_109075_2022-07-22_final
2022-07-22 11:14:50	ga_ls8c_ard_3-2-1_109076_2022-07-22_final
2022-07-22 11:15:14	ga_ls8c_ard_3-2-1_109077_2022-07-22_final
2022-07-22 11:15:38	ga_ls8c_ard_3-2-1_109078_2022-07-22_final
2022-07-22 11:16:02	ga_ls8c_ard_3-2-1_109079_2022-07-22_final
2022-07-29 11:18:18	ga_ls8c_ard_3-2-1_110069_2022-07-29_final
2022-07-29 11:18:42	ga_ls8c_ard_3-2-1_110070_2022-07-29_final
2022-07-29 11:19:06	ga_ls8c_ard_3-2-1_110071_2022-07-29_final
2022-07-29 11:19:30	ga_ls8c_ard_3-2-1_110072_2022-07-29_final
2022-07-29 11:19:54	ga_ls8c_ard_3-2-1_110073_2022-07-29_final
2022-07-29 11:20:18	ga_ls8c_ard_3-2-1_110074_2022-07-29_final
2022-07-29 11:20:42	ga_ls8c_ard_3-2-1_110075_2022-07-29_final
2022-07-31 11:09:33	ga_ls8c_ard_3-2-1_108078_2022-07-31_final
2022-07-31 11:09:57	ga_ls8c_ard_3-2-1_108079_2022-07-31_final
2022-07-31 11:10:21	ga_ls8c_ard_3-2-1_108080_2022-07-31_final
2022-07-31 11:10:45	ga_ls8c_ard_3-2-1_108081_2022-07-31_final
2022-07-31 11:11:09	ga_ls8c_ard_3-2-1_108082_2022-07-31_final
2022-07-31 11:11:33	ga_ls8c_ard_3-2-1_108083_2022-07-31_final
2022-07-31 11:11:57	ga_ls8c_ard_3-2-1_108084_2022-07-31_final
2022-10-12 11:05:04	ga_ls8c_ard_3-2-1_107082_2022-10-12_final
2022-10-12 11:05:28	ga_ls8c_ard_3-2-1_107083_2022-10-12_final
2022-10-12 11:05:52	ga_ls8c_ard_3-2-1_107084_2022-10-12_final
2022-10-17 11:18:27	ga_ls8c_ard_3-2-1_110069_2022-10-17_final
2022-10-17 11:18:51	ga_ls8c_ard_3-2-1_110070_2022-10-17_final
2022-10-17 11:19:15	ga_ls8c_ard_3-2-1_110071_2022-10-17_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
2022-10-19 11:09:42	ga_ls8c_ard_3-2-1_108078_2022-10-19_final
2022-10-19 11:10:06	ga_ls8c_ard_3-2-1_108079_2022-10-19_final
2022-10-19 11:10:30	ga_ls8c_ard_3-2-1_108080_2022-10-19_final
2022-10-19 11:10:54	ga_ls8c_ard_3-2-1_108081_2022-10-19_final
2022-10-19 11:11:18	ga_ls8c_ard_3-2-1_108082_2022-10-19_final
2022-10-19 11:11:42	ga_ls8c_ard_3-2-1_108083_2022-10-19_final
2022-10-19 11:12:06	ga_ls8c_ard_3-2-1_108084_2022-10-19_final
2022-10-28 11:05:11	ga_ls8c_ard_3-2-1_107082_2022-10-28_final
2022-10-28 11:05:35	ga_ls8c_ard_3-2-1_107083_2022-10-28_final
2022-10-28 11:05:59	ga_ls8c_ard_3-2-1_107084_2022-10-28_final
2022-11-02 11:18:33	ga_ls8c_ard_3-2-1_110069_2022-11-02_final
2022-11-02 11:18:57	ga_ls8c_ard_3-2-1_110070_2022-11-02_final
2022-11-02 11:19:21	ga_ls8c_ard_3-2-1_110071_2022-11-02_final
2022-11-02 11:19:45	ga_ls8c_ard_3-2-1_110072_2022-11-02_final
2022-11-02 11:20:09	ga_ls8c_ard_3-2-1_110073_2022-11-02_final
2022-11-02 11:20:33	ga_ls8c_ard_3-2-1_110074_2022-11-02_final
2022-11-02 11:20:57	ga_ls8c_ard_3-2-1_110075_2022-11-02_final
2022-11-04 11:09:47	ga_ls8c_ard_3-2-1_108078_2022-11-04_final
2022-11-04 11:10:11	ga_ls8c_ard_3-2-1_108079_2022-11-04_final
2022-11-04 11:10:35	ga_ls8c_ard_3-2-1_108080_2022-11-04_final
2022-11-04 11:10:59	ga_ls8c_ard_3-2-1_108081_2022-11-04_final
2022-11-04 11:11:23	ga_ls8c_ard_3-2-1_108082_2022-11-04_final
2022-11-04 11:11:47	ga_ls8c_ard_3-2-1_108083_2022-11-04_final
2022-11-04 11:12:11	ga_ls8c_ard_3-2-1_108084_2022-11-04_final
2022-12-20 11:19:31	ga_ls8c_ard_3-2-1_110072_2022-12-20_final
2022-12-20 11:20:43	ga_ls8c_ard_3-2-1_110075_2022-12-20_final
2022-12-29 11:14:08	ga_ls8c_ard_3-2-1_109074_2022-12-29_final
2022-12-29 11:14:32	ga_ls8c_ard_3-2-1_109075_2022-12-29_final
2022-12-29 11:14:56	ga_ls8c_ard_3-2-1_109076_2022-12-29_final
2022-12-29 11:15:20	ga_ls8c_ard_3-2-1_109077_2022-12-29_final
2022-12-29 11:15:44	ga_ls8c_ard_3-2-1_109078_2022-12-29_final
2022-12-29 11:16:08	ga_ls8c_ard_3-2-1_109079_2022-12-29_final
2023-06-09 11:03:58	ga_ls8c_ard_3-2-1_107082_2023-06-09_final
2023-06-09 11:04:22	ga_ls8c_ard_3-2-1_107083_2023-06-09_final
2023-06-09 11:04:46	ga_ls8c_ard_3-2-1_107084_2023-06-09_final
2023-07-23 11:23:26	ga_ls8c_ard_3-2-1_111068_2023-07-23_final
2023-07-23 11:23:50	ga_ls8c_ard_3-2-1_111069_2023-07-23_final
2023-07-23 11:24:13	ga_ls8c_ard_3-2-1_111070_2023-07-23_final
2023-07-27 11:04:21	ga_ls8c_ard_3-2-1_107082_2023-07-27_final
2023-07-27 11:04:45	ga_ls8c_ard_3-2-1_107083_2023-07-27_final
2023-07-27 11:05:09	ga_ls8c_ard_3-2-1_107084_2023-07-27_final
2023-08-01 11:17:45	ga_ls8c_ard_3-2-1_110069_2023-08-01_final
2023-08-01 11:18:09	ga_ls8c_ard_3-2-1_110070_2023-08-01_final
2023-08-01 11:18:33	ga_ls8c_ard_3-2-1_110071_2023-08-01_final
2023-08-01 11:18:57	ga_ls8c_ard_3-2-1_110072_2023-08-01_final
2023-08-01 11:19:21	ga_ls8c_ard_3-2-1_110073_2023-08-01_final
2023-08-01 11:19:45	ga_ls8c_ard_3-2-1_110074_2023-08-01_final
2023-08-01 11:20:09	ga_ls8c_ard_3-2-1_110075_2023-08-01_final
2023-08-03 11:09:00	ga_ls8c_ard_3-2-1_108078_2023-08-03_final
2023-08-03 11:09:23	ga_ls8c_ard_3-2-1_108079_2023-08-03_final
2023-08-03 11:09:47	ga_ls8c_ard_3-2-1_108080_2023-08-03_final
2023-08-03 11:10:11	ga_ls8c_ard_3-2-1_108081_2023-08-03_final
2023-08-03 11:10:35	ga_ls8c_ard_3-2-1_108082_2023-08-03_final
2023-08-03 11:10:59	ga_ls8c_ard_3-2-1_108083_2023-08-03_final
2023-08-03 11:11:23	ga_ls8c_ard_3-2-1_108084_2023-08-03_final
2023-08-10 11:13:35	ga_ls8c_ard_3-2-1_109074_2023-08-10_final
2023-08-10 11:13:59	ga_ls8c_ard_3-2-1_109075_2023-08-10_final
2023-08-10 11:14:23	ga_ls8c_ard_3-2-1_109076_2023-08-10_final
2023-08-10 11:14:46	ga_ls8c_ard_3-2-1_109077_2023-08-10_final
2023-08-10 11:15:10	ga_ls8c_ard_3-2-1_109078_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years