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
2019-07-05 11:23:01	ga_ls8c_ard_3-1-0_110082_2019-07-05_final
2019-07-05 11:23:25	ga_ls8c_ard_3-1-0_110083_2019-07-05_final
2019-07-05 11:23:49	ga_ls8c_ard_3-1-0_110084_2019-07-05_final
2019-07-05 11:24:13	ga_ls8c_ard_3-1-0_110085_2019-07-05_final
2019-08-18 11:41:59	ga_ls8c_ard_3-1-0_114067_2019-08-18_final
2019-08-20 11:32:25	ga_ls8c_ard_3-1-0_112074_2019-08-20_final
2019-08-20 11:32:49	ga_ls8c_ard_3-1-0_112075_2019-08-20_final
2019-08-20 11:33:13	ga_ls8c_ard_3-1-0_112076_2019-08-20_final
2019-08-20 11:33:37	ga_ls8c_ard_3-1-0_112077_2019-08-20_final
2019-08-20 11:34:01	ga_ls8c_ard_3-1-0_112078_2019-08-20_final
2019-08-20 11:34:25	ga_ls8c_ard_3-1-0_112079_2019-08-20_final
2019-08-20 11:34:49	ga_ls8c_ard_3-1-0_112080_2019-08-20_final
2019-08-22 11:23:16	ga_ls8c_ard_3-1-0_110082_2019-08-22_final
2019-08-22 11:23:40	ga_ls8c_ard_3-1-0_110083_2019-08-22_final
2019-08-22 11:24:04	ga_ls8c_ard_3-1-0_110084_2019-08-22_final
2019-08-22 11:24:28	ga_ls8c_ard_3-1-0_110085_2019-08-22_final
2019-11-08 11:32:38	ga_ls8c_ard_3-1-0_112074_2019-11-08_final
2019-11-08 11:33:02	ga_ls8c_ard_3-1-0_112075_2019-11-08_final
2019-11-08 11:33:26	ga_ls8c_ard_3-1-0_112076_2019-11-08_final
2019-11-08 11:33:50	ga_ls8c_ard_3-1-0_112077_2019-11-08_final
2019-11-08 11:34:14	ga_ls8c_ard_3-1-0_112078_2019-11-08_final
2019-11-08 11:34:38	ga_ls8c_ard_3-1-0_112079_2019-11-08_final
2019-11-08 11:35:02	ga_ls8c_ard_3-1-0_112080_2019-11-08_final
2019-11-10 11:23:28	ga_ls8c_ard_3-1-0_110082_2019-11-10_final
2019-11-10 11:23:52	ga_ls8c_ard_3-1-0_110083_2019-11-10_final
2019-11-10 11:24:16	ga_ls8c_ard_3-1-0_110084_2019-11-10_final
2019-11-10 11:24:40	ga_ls8c_ard_3-1-0_110085_2019-11-10_final
2019-11-26 11:23:25	ga_ls8c_ard_3-1-0_110082_2019-11-26_final
2019-11-26 11:23:49	ga_ls8c_ard_3-1-0_110083_2019-11-26_final
2019-11-26 11:24:13	ga_ls8c_ard_3-1-0_110084_2019-11-26_final
2019-11-26 11:24:37	ga_ls8c_ard_3-1-0_110085_2019-11-26_final
2019-12-28 11:23:20	ga_ls8c_ard_3-1-0_110082_2019-12-28_final
2019-12-28 11:23:44	ga_ls8c_ard_3-1-0_110083_2019-12-28_final
2019-12-28 11:24:08	ga_ls8c_ard_3-1-0_110084_2019-12-28_final
2019-12-28 11:24:32	ga_ls8c_ard_3-1-0_110085_2019-12-28_final
2020-01-27 11:32:23	ga_ls8c_ard_3-1-0_112074_2020-01-27_final
2020-01-27 11:32:47	ga_ls8c_ard_3-1-0_112075_2020-01-27_final
2020-01-27 11:33:11	ga_ls8c_ard_3-1-0_112076_2020-01-27_final
2020-01-27 11:33:35	ga_ls8c_ard_3-1-0_112077_2020-01-27_final
2020-01-27 11:33:59	ga_ls8c_ard_3-1-0_112078_2020-01-27_final
2020-01-27 11:34:23	ga_ls8c_ard_3-1-0_112079_2020-01-27_final
2020-01-27 11:34:47	ga_ls8c_ard_3-1-0_112080_2020-01-27_final
2020-02-05 11:28:08	ga_ls8c_ard_3-1-0_111079_2020-02-05_final
2020-02-05 11:28:32	ga_ls8c_ard_3-1-0_111080_2020-02-05_final
2020-02-05 11:28:56	ga_ls8c_ard_3-1-0_111081_2020-02-05_final
2020-02-05 11:29:20	ga_ls8c_ard_3-1-0_111082_2020-02-05_final
2020-02-05 11:29:44	ga_ls8c_ard_3-1-0_111083_2020-02-05_final
2020-02-05 11:30:08	ga_ls8c_ard_3-1-0_111084_2020-02-05_final
2023-04-16 11:37:12	ga_ls8c_ard_3-2-1_113072_2023-04-16_final
2023-04-16 11:37:35	ga_ls8c_ard_3-2-1_113073_2023-04-16_final
2023-04-16 11:37:59	ga_ls8c_ard_3-2-1_113074_2023-04-16_final
2023-04-16 11:38:23	ga_ls8c_ard_3-2-1_113075_2023-04-16_final
2023-04-25 11:31:47	ga_ls8c_ard_3-2-1_112074_2023-04-25_final
2023-04-25 11:32:11	ga_ls8c_ard_3-2-1_112075_2023-04-25_final
2023-04-25 11:32:35	ga_ls8c_ard_3-2-1_112076_2023-04-25_final
2023-04-25 11:32:59	ga_ls8c_ard_3-2-1_112077_2023-04-25_final
2023-04-25 11:33:23	ga_ls8c_ard_3-2-1_112078_2023-04-25_final
2023-04-25 11:33:47	ga_ls8c_ard_3-2-1_112079_2023-04-25_final
2023-04-25 11:34:11	ga_ls8c_ard_3-2-1_112080_2023-04-25_final
2023-04-27 11:22:36	ga_ls8c_ard_3-2-1_110082_2023-04-27_final
2023-04-27 11:23:00	ga_ls8c_ard_3-2-1_110083_2023-04-27_final
2023-04-27 11:23:24	ga_ls8c_ard_3-2-1_110084_2023-04-27_final
2023-04-27 11:23:48	ga_ls8c_ard_3-2-1_110085_2023-04-27_final
2023-05-04 11:27:07	ga_ls8c_ard_3-2-1_111078_2023-05-04_final
2023-05-04 11:27:31	ga_ls8c_ard_3-2-1_111079_2023-05-04_final
2023-05-04 11:27:55	ga_ls8c_ard_3-2-1_111080_2023-05-04_final
2023-05-04 11:28:19	ga_ls8c_ard_3-2-1_111081_2023-05-04_final
2023-05-04 11:28:43	ga_ls8c_ard_3-2-1_111082_2023-05-04_final
2023-05-04 11:29:07	ga_ls8c_ard_3-2-1_111083_2023-05-04_final
2023-05-04 11:29:31	ga_ls8c_ard_3-2-1_111084_2023-05-04_final
2023-05-13 11:22:23	ga_ls8c_ard_3-2-1_110082_2023-05-13_final
2023-05-13 11:22:47	ga_ls8c_ard_3-2-1_110083_2023-05-13_final
2023-05-13 11:23:11	ga_ls8c_ard_3-2-1_110084_2023-05-13_final
2023-05-13 11:23:35	ga_ls8c_ard_3-2-1_110085_2023-05-13_final
2023-06-03 11:36:58	ga_ls8c_ard_3-2-1_113072_2023-06-03_final
2023-06-03 11:37:22	ga_ls8c_ard_3-2-1_113073_2023-06-03_final
2023-06-03 11:37:46	ga_ls8c_ard_3-2-1_113074_2023-06-03_final
2023-06-03 11:38:10	ga_ls8c_ard_3-2-1_113075_2023-06-03_final
2023-06-05 11:27:50	ga_ls8c_ard_3-2-1_111080_2023-06-05_final
2023-06-05 11:28:14	ga_ls8c_ard_3-2-1_111081_2023-06-05_final
2023-06-05 11:28:38	ga_ls8c_ard_3-2-1_111082_2023-06-05_final
2023-06-05 11:29:02	ga_ls8c_ard_3-2-1_111083_2023-06-05_final
2023-06-05 11:29:26	ga_ls8c_ard_3-2-1_111084_2023-06-05_final
2023-09-09 11:27:40	ga_ls8c_ard_3-2-1_111078_2023-09-09_final
2023-09-09 11:28:04	ga_ls8c_ard_3-2-1_111079_2023-09-09_final
2023-09-09 11:28:28	ga_ls8c_ard_3-2-1_111080_2023-09-09_final
2023-09-09 11:28:52	ga_ls8c_ard_3-2-1_111081_2023-09-09_final
2023-09-09 11:29:16	ga_ls8c_ard_3-2-1_111082_2023-09-09_final
2023-09-09 11:29:40	ga_ls8c_ard_3-2-1_111083_2023-09-09_final
2023-09-09 11:30:04	ga_ls8c_ard_3-2-1_111084_2023-09-09_final
2023-10-09 11:37:48	ga_ls8c_ard_3-2-1_113072_2023-10-09_final
2023-10-09 11:38:12	ga_ls8c_ard_3-2-1_113073_2023-10-09_final
2023-10-09 11:38:36	ga_ls8c_ard_3-2-1_113074_2023-10-09_final
2023-10-09 11:39:00	ga_ls8c_ard_3-2-1_113075_2023-10-09_final
2023-10-11 11:27:51	ga_ls8c_ard_3-2-1_111078_2023-10-11_final
2023-10-11 11:28:15	ga_ls8c_ard_3-2-1_111079_2023-10-11_final
2023-10-11 11:28:38	ga_ls8c_ard_3-2-1_111080_2023-10-11_final
2023-10-11 11:29:02	ga_ls8c_ard_3-2-1_111081_2023-10-11_final
2023-10-11 11:29:26	ga_ls8c_ard_3-2-1_111082_2023-10-11_final
2023-10-11 11:29:50	ga_ls8c_ard_3-2-1_111083_2023-10-11_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