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
2019-07-30 11:18:09	ga_ls8c_ard_3-1-0_109085_2019-07-30_final
2019-08-27 11:37:26	ga_ls8c_ard_3-1-0_113071_2019-08-27_final
2019-08-27 11:37:50	ga_ls8c_ard_3-1-0_113072_2019-08-27_final
2019-08-27 11:38:14	ga_ls8c_ard_3-1-0_113073_2019-08-27_final
2019-08-27 11:38:38	ga_ls8c_ard_3-1-0_113074_2019-08-27_final
2019-11-03 11:18:30	ga_ls8c_ard_3-1-0_109085_2019-11-03_final
2019-11-15 11:37:36	ga_ls8c_ard_3-1-0_113071_2019-11-15_final
2019-11-15 11:38:00	ga_ls8c_ard_3-1-0_113072_2019-11-15_final
2019-11-15 11:38:24	ga_ls8c_ard_3-1-0_113073_2019-11-15_final
2019-11-15 11:38:48	ga_ls8c_ard_3-1-0_113074_2019-11-15_final
2022-08-05 11:28:08	ga_ls8c_ard_3-2-1_111078_2022-08-05_final
2022-08-05 11:28:32	ga_ls8c_ard_3-2-1_111079_2022-08-05_final
2022-08-05 11:28:56	ga_ls8c_ard_3-2-1_111080_2022-08-05_final
2022-08-05 11:29:44	ga_ls8c_ard_3-2-1_111082_2022-08-05_final
2022-08-05 11:30:08	ga_ls8c_ard_3-2-1_111083_2022-08-05_final
2022-08-28 11:32:24	ga_ls8c_ard_3-2-1_112073_2022-08-28_final
2022-08-28 11:32:48	ga_ls8c_ard_3-2-1_112074_2022-08-28_final
2022-08-28 11:33:12	ga_ls8c_ard_3-2-1_112075_2022-08-28_final
2022-08-28 11:33:36	ga_ls8c_ard_3-2-1_112076_2022-08-28_final
2022-08-28 11:34:00	ga_ls8c_ard_3-2-1_112077_2022-08-28_final
2022-08-28 11:34:24	ga_ls8c_ard_3-2-1_112078_2022-08-28_final
2022-08-28 11:34:48	ga_ls8c_ard_3-2-1_112079_2022-08-28_final
2022-09-13 11:32:29	ga_ls8c_ard_3-2-1_112073_2022-09-13_final
2022-09-13 11:32:53	ga_ls8c_ard_3-2-1_112074_2022-09-13_final
2022-09-13 11:33:17	ga_ls8c_ard_3-2-1_112075_2022-09-13_final
2022-09-13 11:33:41	ga_ls8c_ard_3-2-1_112076_2022-09-13_final
2022-09-13 11:34:05	ga_ls8c_ard_3-2-1_112077_2022-09-13_final
2022-09-13 11:34:29	ga_ls8c_ard_3-2-1_112078_2022-09-13_final
2022-09-13 11:34:53	ga_ls8c_ard_3-2-1_112079_2022-09-13_final
2022-09-15 11:23:44	ga_ls8c_ard_3-2-1_110082_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
2022-09-15 11:24:56	ga_ls8c_ard_3-2-1_110085_2022-09-15_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
2022-09-22 11:29:32	ga_ls8c_ard_3-2-1_111081_2022-09-22_final
2022-09-22 11:29:56	ga_ls8c_ard_3-2-1_111082_2022-09-22_final
2022-09-22 11:30:20	ga_ls8c_ard_3-2-1_111083_2022-09-22_final
2022-10-06 11:38:15	ga_ls8c_ard_3-2-1_113072_2022-10-06_final
2022-10-06 11:38:39	ga_ls8c_ard_3-2-1_113073_2022-10-06_final
2022-10-06 11:39:03	ga_ls8c_ard_3-2-1_113074_2022-10-06_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
2022-10-08 11:29:27	ga_ls8c_ard_3-2-1_111081_2022-10-08_final
2022-10-08 11:29:51	ga_ls8c_ard_3-2-1_111082_2022-10-08_final
2022-10-08 11:30:15	ga_ls8c_ard_3-2-1_111083_2022-10-08_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
2022-10-15 11:33:34	ga_ls8c_ard_3-2-1_112076_2022-10-15_final
2022-10-15 11:33:58	ga_ls8c_ard_3-2-1_112077_2022-10-15_final
2022-10-15 11:34:22	ga_ls8c_ard_3-2-1_112078_2022-10-15_final
2022-10-15 11:34:46	ga_ls8c_ard_3-2-1_112079_2022-10-15_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
2022-10-17 11:24:26	ga_ls8c_ard_3-2-1_110084_2022-10-17_final
2022-10-17 11:24:50	ga_ls8c_ard_3-2-1_110085_2022-10-17_final
2022-10-22 11:38:14	ga_ls8c_ard_3-2-1_113072_2022-10-22_final
2022-10-22 11:38:38	ga_ls8c_ard_3-2-1_113073_2022-10-22_final
2022-10-22 11:39:02	ga_ls8c_ard_3-2-1_113074_2022-10-22_final
2022-11-25 11:28:14	ga_ls8c_ard_3-2-1_111078_2022-11-25_final
2022-11-25 11:28:38	ga_ls8c_ard_3-2-1_111079_2022-11-25_final
2022-11-25 11:29:02	ga_ls8c_ard_3-2-1_111080_2022-11-25_final
2022-11-25 11:29:26	ga_ls8c_ard_3-2-1_111081_2022-11-25_final
2022-11-25 11:29:50	ga_ls8c_ard_3-2-1_111082_2022-11-25_final
2022-11-25 11:30:14	ga_ls8c_ard_3-2-1_111083_2022-11-25_final
2022-12-04 11:23:39	ga_ls8c_ard_3-2-1_110082_2022-12-04_final
2022-12-04 11:24:03	ga_ls8c_ard_3-2-1_110083_2022-12-04_final
2022-12-04 11:24:27	ga_ls8c_ard_3-2-1_110084_2022-12-04_final
2022-12-04 11:24:51	ga_ls8c_ard_3-2-1_110085_2022-12-04_final
2022-12-09 11:38:11	ga_ls8c_ard_3-2-1_113072_2022-12-09_final
2022-12-09 11:38:35	ga_ls8c_ard_3-2-1_113073_2022-12-09_final
2022-12-09 11:38:59	ga_ls8c_ard_3-2-1_113074_2022-12-09_final
2022-12-11 11:28:12	ga_ls8c_ard_3-2-1_111078_2022-12-11_final
2022-12-11 11:28:36	ga_ls8c_ard_3-2-1_111079_2022-12-11_final
2022-12-11 11:29:00	ga_ls8c_ard_3-2-1_111080_2022-12-11_final
2022-12-11 11:29:24	ga_ls8c_ard_3-2-1_111081_2022-12-11_final
2022-12-11 11:29:48	ga_ls8c_ard_3-2-1_111082_2022-12-11_final
2022-12-11 11:30:12	ga_ls8c_ard_3-2-1_111083_2022-12-11_final
2022-12-18 11:32:19	ga_ls8c_ard_3-2-1_112073_2022-12-18_final
2022-12-18 11:32:43	ga_ls8c_ard_3-2-1_112074_2022-12-18_final
2022-12-18 11:33:07	ga_ls8c_ard_3-2-1_112075_2022-12-18_final
2022-12-18 11:33:31	ga_ls8c_ard_3-2-1_112076_2022-12-18_final
2022-12-18 11:33:55	ga_ls8c_ard_3-2-1_112077_2022-12-18_final
2022-12-18 11:34:18	ga_ls8c_ard_3-2-1_112078_2022-12-18_final
2022-12-18 11:34:42	ga_ls8c_ard_3-2-1_112079_2022-12-18_final
2022-12-20 11:23:31	ga_ls8c_ard_3-2-1_110082_2022-12-20_final
2022-12-20 11:23:55	ga_ls8c_ard_3-2-1_110083_2022-12-20_final
2022-12-20 11:24:19	ga_ls8c_ard_3-2-1_110084_2022-12-20_final
2022-12-20 11:24:43	ga_ls8c_ard_3-2-1_110085_2022-12-20_final
2022-12-25 11:38:02	ga_ls8c_ard_3-2-1_113072_2022-12-25_final
2022-12-25 11:38:26	ga_ls8c_ard_3-2-1_113073_2022-12-25_final
2022-12-25 11:38:50	ga_ls8c_ard_3-2-1_113074_2022-12-25_final
2022-12-27 11:28:05	ga_ls8c_ard_3-2-1_111078_2022-12-27_final
2022-12-27 11:28:29	ga_ls8c_ard_3-2-1_111079_2022-12-27_final
2022-12-27 11:28:53	ga_ls8c_ard_3-2-1_111080_2022-12-27_final
2022-12-27 11:29:17	ga_ls8c_ard_3-2-1_111081_2022-12-27_final
2022-12-27 11:29:41	ga_ls8c_ard_3-2-1_111082_2022-12-27_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