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
2014-12-23 11:17:26	ga_ls8c_ard_3-0-0_109083_2014-12-23_final
2014-12-23 11:17:50	ga_ls8c_ard_3-0-0_109084_2014-12-23_final
2015-01-04 11:35:42	ga_ls8c_ard_3-0-0_113067_2015-01-04_final
2015-01-13 11:30:43	ga_ls8c_ard_3-0-0_112070_2015-01-13_final
2015-01-13 11:31:07	ga_ls8c_ard_3-0-0_112071_2015-01-13_final
2015-01-13 11:31:31	ga_ls8c_ard_3-0-0_112072_2015-01-13_final
2015-01-13 11:31:54	ga_ls8c_ard_3-0-0_112073_2015-01-13_final
2015-01-13 11:32:18	ga_ls8c_ard_3-0-0_112074_2015-01-13_final
2015-01-13 11:32:42	ga_ls8c_ard_3-0-0_112075_2015-01-13_final
2015-01-20 11:35:38	ga_ls8c_ard_3-0-0_113067_2015-01-20_final
2015-01-29 11:30:37	ga_ls8c_ard_3-0-0_112070_2015-01-29_final
2015-01-29 11:31:01	ga_ls8c_ard_3-0-0_112071_2015-01-29_final
2015-01-29 11:31:25	ga_ls8c_ard_3-0-0_112072_2015-01-29_final
2015-01-29 11:31:49	ga_ls8c_ard_3-0-0_112073_2015-01-29_final
2015-01-29 11:32:13	ga_ls8c_ard_3-0-0_112074_2015-01-29_final
2015-01-29 11:32:37	ga_ls8c_ard_3-0-0_112075_2015-01-29_final
2015-02-21 11:35:28	ga_ls8c_ard_3-0-0_113067_2015-02-21_final
2015-03-25 11:35:11	ga_ls8c_ard_3-0-0_113067_2015-03-25_final
2015-04-28 11:25:22	ga_ls8c_ard_3-0-0_111074_2015-04-28_final
2015-04-28 11:25:46	ga_ls8c_ard_3-0-0_111075_2015-04-28_final
2015-04-28 11:26:10	ga_ls8c_ard_3-0-0_111076_2015-04-28_final
2015-04-28 11:26:34	ga_ls8c_ard_3-0-0_111077_2015-04-28_final
2015-04-28 11:26:58	ga_ls8c_ard_3-0-0_111078_2015-04-28_final
2015-04-28 11:27:22	ga_ls8c_ard_3-0-0_111079_2015-04-28_final
2015-04-28 11:27:46	ga_ls8c_ard_3-0-0_111080_2015-04-28_final
2015-04-30 11:16:34	ga_ls8c_ard_3-0-0_109083_2015-04-30_final
2015-04-30 11:16:58	ga_ls8c_ard_3-0-0_109084_2015-04-30_final
2022-05-19 11:17:16	ga_ls8c_ard_3-2-1_109083_2022-05-19_final
2022-05-19 11:17:40	ga_ls8c_ard_3-2-1_109084_2022-05-19_final
2022-05-24 11:31:24	ga_ls8c_ard_3-2-1_112072_2022-05-24_final
2022-05-24 11:31:48	ga_ls8c_ard_3-2-1_112073_2022-05-24_final
2022-05-24 11:32:12	ga_ls8c_ard_3-2-1_112074_2022-05-24_final
2022-05-24 11:32:36	ga_ls8c_ard_3-2-1_112075_2022-05-24_final
2022-07-04 11:26:20	ga_ls8c_ard_3-2-1_111074_2022-07-04_final
2022-07-04 11:26:44	ga_ls8c_ard_3-2-1_111075_2022-07-04_final
2022-07-04 11:27:08	ga_ls8c_ard_3-2-1_111076_2022-07-04_final
2022-07-04 11:27:32	ga_ls8c_ard_3-2-1_111077_2022-07-04_final
2022-07-04 11:27:56	ga_ls8c_ard_3-2-1_111078_2022-07-04_final
2022-07-04 11:28:20	ga_ls8c_ard_3-2-1_111079_2022-07-04_final
2022-07-04 11:28:43	ga_ls8c_ard_3-2-1_111080_2022-07-04_final
2022-07-06 11:17:34	ga_ls8c_ard_3-2-1_109083_2022-07-06_final
2022-07-06 11:17:58	ga_ls8c_ard_3-2-1_109084_2022-07-06_final
2022-07-11 11:31:42	ga_ls8c_ard_3-2-1_112072_2022-07-11_final
2022-07-11 11:32:06	ga_ls8c_ard_3-2-1_112073_2022-07-11_final
2022-07-11 11:32:30	ga_ls8c_ard_3-2-1_112074_2022-07-11_final
2022-07-11 11:32:54	ga_ls8c_ard_3-2-1_112075_2022-07-11_final
2022-07-20 11:26:22	ga_ls8c_ard_3-2-1_111074_2022-07-20_final
2022-07-20 11:26:46	ga_ls8c_ard_3-2-1_111075_2022-07-20_final
2022-07-20 11:27:10	ga_ls8c_ard_3-2-1_111076_2022-07-20_final
2022-07-20 11:27:34	ga_ls8c_ard_3-2-1_111077_2022-07-20_final
2022-07-20 11:27:58	ga_ls8c_ard_3-2-1_111078_2022-07-20_final
2022-07-20 11:28:22	ga_ls8c_ard_3-2-1_111079_2022-07-20_final
2022-07-20 11:28:46	ga_ls8c_ard_3-2-1_111080_2022-07-20_final
2022-07-22 11:17:38	ga_ls8c_ard_3-2-1_109083_2022-07-22_final
2022-07-22 11:18:02	ga_ls8c_ard_3-2-1_109084_2022-07-22_final
2022-07-27 11:31:50	ga_ls8c_ard_3-2-1_112072_2022-07-27_final
2022-07-27 11:32:14	ga_ls8c_ard_3-2-1_112073_2022-07-27_final
2022-07-27 11:32:38	ga_ls8c_ard_3-2-1_112074_2022-07-27_final
2022-07-27 11:33:02	ga_ls8c_ard_3-2-1_112075_2022-07-27_final
2022-07-29 11:22:18	ga_ls8c_ard_3-2-1_110079_2022-07-29_final
2022-07-29 11:22:42	ga_ls8c_ard_3-2-1_110080_2022-07-29_final
2022-07-29 11:23:06	ga_ls8c_ard_3-2-1_110081_2022-07-29_final
2022-07-29 11:23:29	ga_ls8c_ard_3-2-1_110082_2022-07-29_final
2022-07-29 11:23:53	ga_ls8c_ard_3-2-1_110083_2022-07-29_final
2022-07-29 11:24:17	ga_ls8c_ard_3-2-1_110084_2022-07-29_final
2022-09-15 11:22:32	ga_ls8c_ard_3-2-1_110079_2022-09-15_final
2022-09-15 11:23:20	ga_ls8c_ard_3-2-1_110081_2022-09-15_final
2022-09-15 11:24:08	ga_ls8c_ard_3-2-1_110083_2022-09-15_final
2022-09-15 11:24:32	ga_ls8c_ard_3-2-1_110084_2022-09-15_final
2022-09-22 11:26:44	ga_ls8c_ard_3-2-1_111074_2022-09-22_final
2022-09-22 11:27:08	ga_ls8c_ard_3-2-1_111075_2022-09-22_final
2022-09-22 11:27:32	ga_ls8c_ard_3-2-1_111076_2022-09-22_final
2022-09-22 11:27:56	ga_ls8c_ard_3-2-1_111077_2022-09-22_final
2022-09-22 11:28:20	ga_ls8c_ard_3-2-1_111078_2022-09-22_final
2022-09-22 11:28:44	ga_ls8c_ard_3-2-1_111079_2022-09-22_final
2022-09-22 11:29:08	ga_ls8c_ard_3-2-1_111080_2022-09-22_final
2022-09-24 11:17:58	ga_ls8c_ard_3-2-1_109083_2022-09-24_final
2022-09-24 11:18:22	ga_ls8c_ard_3-2-1_109084_2022-09-24_final
2022-09-29 11:32:07	ga_ls8c_ard_3-2-1_112072_2022-09-29_final
2022-09-29 11:32:31	ga_ls8c_ard_3-2-1_112073_2022-09-29_final
2022-09-29 11:32:54	ga_ls8c_ard_3-2-1_112074_2022-09-29_final
2022-09-29 11:33:18	ga_ls8c_ard_3-2-1_112075_2022-09-29_final
2022-10-08 11:26:40	ga_ls8c_ard_3-2-1_111074_2022-10-08_final
2022-10-08 11:27:04	ga_ls8c_ard_3-2-1_111075_2022-10-08_final
2022-10-08 11:27:28	ga_ls8c_ard_3-2-1_111076_2022-10-08_final
2022-10-08 11:27:52	ga_ls8c_ard_3-2-1_111077_2022-10-08_final
2022-10-08 11:28:15	ga_ls8c_ard_3-2-1_111078_2022-10-08_final
2022-10-08 11:28:39	ga_ls8c_ard_3-2-1_111079_2022-10-08_final
2022-10-08 11:29:03	ga_ls8c_ard_3-2-1_111080_2022-10-08_final
2022-10-10 11:17:52	ga_ls8c_ard_3-2-1_109083_2022-10-10_final
2022-10-10 11:18:16	ga_ls8c_ard_3-2-1_109084_2022-10-10_final
2022-10-15 11:31:59	ga_ls8c_ard_3-2-1_112072_2022-10-15_final
2022-10-15 11:32:23	ga_ls8c_ard_3-2-1_112073_2022-10-15_final
2022-10-15 11:32:46	ga_ls8c_ard_3-2-1_112074_2022-10-15_final
2022-10-15 11:33:10	ga_ls8c_ard_3-2-1_112075_2022-10-15_final
2022-10-17 11:22:26	ga_ls8c_ard_3-2-1_110079_2022-10-17_final
2022-10-17 11:22:50	ga_ls8c_ard_3-2-1_110080_2022-10-17_final
2022-10-17 11:23:14	ga_ls8c_ard_3-2-1_110081_2022-10-17_final
2022-10-17 11:23:38	ga_ls8c_ard_3-2-1_110082_2022-10-17_final
2022-10-17 11:24:02	ga_ls8c_ard_3-2-1_110083_2022-10-17_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