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
2014-10-06 09:20:17	ga_ls8c_ard_3-0-0_091068_2014-10-05_final
2014-11-23 09:20:15	ga_ls8c_ard_3-0-0_091068_2014-11-22_final
2015-07-05 09:19:32	ga_ls8c_ard_3-0-0_091068_2015-07-04_final
2015-08-22 09:19:51	ga_ls8c_ard_3-0-0_091068_2015-08-21_final
2015-09-07 09:19:56	ga_ls8c_ard_3-0-0_091068_2015-09-06_final
2015-09-23 09:20:04	ga_ls8c_ard_3-0-0_091068_2015-09-22_final
2015-11-26 09:20:14	ga_ls8c_ard_3-0-0_091068_2015-11-25_final
2018-02-21 09:09:53	ga_ls8c_ard_3-0-0_089074_2018-02-20_final
2018-02-21 09:10:17	ga_ls8c_ard_3-0-0_089075_2018-02-20_final
2018-02-21 09:10:41	ga_ls8c_ard_3-0-0_089076_2018-02-20_final
2018-02-21 09:11:05	ga_ls8c_ard_3-0-0_089077_2018-02-20_final
2018-02-21 09:11:29	ga_ls8c_ard_3-0-0_089078_2018-02-20_final
2018-03-09 09:09:45	ga_ls8c_ard_3-0-0_089074_2018-03-08_final
2018-03-09 09:10:09	ga_ls8c_ard_3-0-0_089075_2018-03-08_final
2018-03-09 09:10:33	ga_ls8c_ard_3-0-0_089076_2018-03-08_final
2018-03-09 09:10:57	ga_ls8c_ard_3-0-0_089077_2018-03-08_final
2018-03-09 09:11:21	ga_ls8c_ard_3-0-0_089078_2018-03-08_final
2018-03-23 09:19:36	ga_ls8c_ard_3-0-0_091068_2018-03-22_final
2018-04-03 09:05:22	ga_ls8c_ard_3-0-0_088079_2018-04-02_final
2018-04-03 09:05:46	ga_ls8c_ard_3-0-0_088080_2018-04-02_final
2018-04-03 09:06:10	ga_ls8c_ard_3-1-0_088081_2018-04-02_final
2018-04-03 09:06:34	ga_ls8c_ard_3-0-0_088082_2018-04-02_final
2018-04-24 09:19:19	ga_ls8c_ard_3-0-0_091068_2018-04-23_final
2018-04-26 09:09:20	ga_ls8c_ard_3-0-0_089074_2018-04-25_final
2018-04-26 09:09:44	ga_ls8c_ard_3-0-0_089075_2018-04-25_final
2018-04-26 09:10:08	ga_ls8c_ard_3-0-0_089076_2018-04-25_final
2018-04-26 09:10:32	ga_ls8c_ard_3-0-0_089077_2018-04-25_final
2018-04-26 09:10:56	ga_ls8c_ard_3-0-0_089078_2018-04-25_final
2018-06-13 09:08:59	ga_ls8c_ard_3-0-0_089074_2018-06-12_final
2018-06-13 09:09:23	ga_ls8c_ard_3-0-0_089075_2018-06-12_final
2018-06-27 09:19:06	ga_ls8c_ard_3-0-0_091068_2018-06-26_final
2018-06-29 09:09:09	ga_ls8c_ard_3-0-0_089074_2018-06-28_final
2018-06-29 09:09:33	ga_ls8c_ard_3-0-0_089075_2018-06-28_final
2018-06-29 09:09:57	ga_ls8c_ard_3-0-0_089076_2018-06-28_final
2018-06-29 09:10:21	ga_ls8c_ard_3-0-0_089077_2018-06-28_final
2018-06-29 09:10:45	ga_ls8c_ard_3-0-0_089078_2018-06-28_final
2018-07-15 09:09:17	ga_ls8c_ard_3-0-0_089074_2018-07-14_final
2018-07-15 09:09:41	ga_ls8c_ard_3-0-0_089075_2018-07-14_final
2018-07-15 09:10:05	ga_ls8c_ard_3-0-0_089076_2018-07-14_final
2018-07-15 09:10:29	ga_ls8c_ard_3-0-0_089077_2018-07-14_final
2018-07-15 09:10:53	ga_ls8c_ard_3-0-0_089078_2018-07-14_final
2022-08-11 09:10:37	ga_ls8c_ard_3-2-1_089074_2022-08-10_final
2022-08-11 09:11:01	ga_ls8c_ard_3-2-1_089075_2022-08-10_final
2022-08-11 09:11:25	ga_ls8c_ard_3-2-1_089076_2022-08-10_final
2022-08-11 09:11:49	ga_ls8c_ard_3-2-1_089077_2022-08-10_final
2022-08-11 09:12:13	ga_ls8c_ard_3-2-1_089078_2022-08-10_final
2022-08-20 09:06:52	ga_ls8c_ard_3-2-1_088080_2022-08-19_final
2022-08-20 09:07:16	ga_ls8c_ard_3-2-1_088081_2022-08-19_final
2022-08-20 09:07:40	ga_ls8c_ard_3-2-1_088082_2022-08-19_final
2022-09-05 09:06:53	ga_ls8c_ard_3-2-1_088080_2022-09-04_final
2022-09-05 09:07:17	ga_ls8c_ard_3-2-1_088081_2022-09-04_final
2022-09-05 09:07:41	ga_ls8c_ard_3-2-1_088082_2022-09-04_final
2022-09-12 09:10:44	ga_ls8c_ard_3-2-1_089074_2022-09-11_final
2022-09-12 09:11:08	ga_ls8c_ard_3-2-1_089075_2022-09-11_final
2022-09-12 09:11:32	ga_ls8c_ard_3-2-1_089076_2022-09-11_final
2022-09-12 09:11:56	ga_ls8c_ard_3-2-1_089077_2022-09-11_final
2022-09-12 09:12:20	ga_ls8c_ard_3-2-1_089078_2022-09-11_final
2022-09-21 09:06:59	ga_ls8c_ard_3-2-1_088080_2022-09-20_final
2022-09-21 09:07:23	ga_ls8c_ard_3-2-1_088081_2022-09-20_final
2022-09-21 09:07:47	ga_ls8c_ard_3-2-1_088082_2022-09-20_final
2022-09-28 09:10:46	ga_ls8c_ard_3-2-1_089074_2022-09-27_final
2022-09-28 09:11:10	ga_ls8c_ard_3-2-1_089075_2022-09-27_final
2022-09-28 09:11:34	ga_ls8c_ard_3-2-1_089076_2022-09-27_final
2022-09-28 09:11:58	ga_ls8c_ard_3-2-1_089077_2022-09-27_final
2022-09-28 09:12:22	ga_ls8c_ard_3-2-1_089078_2022-09-27_final
2022-10-30 09:10:46	ga_ls8c_ard_3-2-1_089074_2022-10-29_final
2022-10-30 09:11:10	ga_ls8c_ard_3-2-1_089075_2022-10-29_final
2022-10-30 09:11:34	ga_ls8c_ard_3-2-1_089076_2022-10-29_final
2022-10-30 09:11:57	ga_ls8c_ard_3-2-1_089077_2022-10-29_final
2022-10-30 09:12:21	ga_ls8c_ard_3-2-1_089078_2022-10-29_final
2022-11-15 09:10:40	ga_ls8c_ard_3-2-1_089074_2022-11-14_final
2022-11-15 09:11:04	ga_ls8c_ard_3-2-1_089075_2022-11-14_final
2022-11-15 09:11:28	ga_ls8c_ard_3-2-1_089076_2022-11-14_final
2022-11-15 09:11:52	ga_ls8c_ard_3-2-1_089077_2022-11-14_final
2022-11-15 09:12:16	ga_ls8c_ard_3-2-1_089078_2022-11-14_final
2022-11-24 09:06:53	ga_ls8c_ard_3-2-1_088080_2022-11-23_final
2022-11-24 09:07:17	ga_ls8c_ard_3-2-1_088081_2022-11-23_final
2022-11-24 09:07:41	ga_ls8c_ard_3-2-1_088082_2022-11-23_final
2022-12-01 09:10:41	ga_ls8c_ard_3-2-1_089074_2022-11-30_final
2022-12-01 09:11:05	ga_ls8c_ard_3-2-1_089075_2022-11-30_final
2022-12-01 09:11:29	ga_ls8c_ard_3-2-1_089076_2022-11-30_final
2022-12-01 09:11:53	ga_ls8c_ard_3-2-1_089077_2022-11-30_final
2022-12-01 09:12:17	ga_ls8c_ard_3-2-1_089078_2022-11-30_final
2022-12-10 09:06:52	ga_ls8c_ard_3-2-1_088080_2022-12-09_final
2022-12-10 09:07:16	ga_ls8c_ard_3-2-1_088081_2022-12-09_final
2022-12-10 09:07:40	ga_ls8c_ard_3-2-1_088082_2022-12-09_final
2022-12-17 09:10:35	ga_ls8c_ard_3-2-1_089074_2022-12-16_final
2022-12-17 09:10:59	ga_ls8c_ard_3-2-1_089075_2022-12-16_final
2022-12-17 09:11:23	ga_ls8c_ard_3-2-1_089076_2022-12-16_final
2022-12-17 09:11:47	ga_ls8c_ard_3-2-1_089077_2022-12-16_final
2022-12-17 09:12:11	ga_ls8c_ard_3-2-1_089078_2022-12-16_final
2023-07-13 09:09:49	ga_ls8c_ard_3-2-1_089074_2023-07-12_final
2023-07-13 09:10:13	ga_ls8c_ard_3-2-1_089075_2023-07-12_final
2023-07-13 09:10:37	ga_ls8c_ard_3-2-1_089076_2023-07-12_final
2023-07-13 09:11:01	ga_ls8c_ard_3-2-1_089077_2023-07-12_final
2023-07-13 09:11:25	ga_ls8c_ard_3-2-1_089078_2023-07-12_final
2023-07-29 09:09:56	ga_ls8c_ard_3-2-1_089074_2023-07-28_final
2023-07-29 09:10:20	ga_ls8c_ard_3-2-1_089075_2023-07-28_final
2023-07-29 09:10:44	ga_ls8c_ard_3-2-1_089076_2023-07-28_final
2023-07-29 09:11:08	ga_ls8c_ard_3-2-1_089077_2023-07-28_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years