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
2018-02-13 11:37:28	ga_ls8c_ard_3-0-0_113072_2018-02-13_final
2018-02-13 11:37:52	ga_ls8c_ard_3-0-0_113073_2018-02-13_final
2018-02-13 11:38:16	ga_ls8c_ard_3-0-0_113074_2018-02-13_final
2018-02-13 11:38:40	ga_ls8c_ard_3-0-0_113075_2018-02-13_final
2018-02-13 11:39:04	ga_ls8c_ard_3-0-0_113076_2018-02-13_final
2018-02-13 11:39:28	ga_ls8c_ard_3-0-0_113077_2018-02-13_final
2018-02-13 11:39:52	ga_ls8c_ard_3-0-0_113078_2018-02-13_final
2018-02-15 11:28:41	ga_ls8c_ard_3-0-0_111081_2018-02-15_final
2018-02-15 11:29:05	ga_ls8c_ard_3-0-0_111082_2018-02-15_final
2018-02-15 11:29:29	ga_ls8c_ard_3-0-0_111083_2018-02-15_final
2018-02-15 11:29:53	ga_ls8c_ard_3-0-0_111084_2018-02-15_final
2018-02-15 11:30:17	ga_ls8c_ard_3-0-0_111085_2018-02-15_final
2018-04-18 11:36:56	ga_ls8c_ard_3-0-0_113072_2018-04-18_final
2018-04-18 11:37:20	ga_ls8c_ard_3-0-0_113073_2018-04-18_final
2018-04-18 11:37:44	ga_ls8c_ard_3-0-0_113074_2018-04-18_final
2018-04-18 11:38:08	ga_ls8c_ard_3-0-0_113075_2018-04-18_final
2018-04-18 11:38:32	ga_ls8c_ard_3-0-0_113076_2018-04-18_final
2018-04-18 11:38:56	ga_ls8c_ard_3-0-0_113077_2018-04-18_final
2018-04-18 11:39:19	ga_ls8c_ard_3-0-0_113078_2018-04-18_final
2018-04-20 11:28:08	ga_ls8c_ard_3-0-0_111081_2018-04-20_final
2018-04-20 11:28:32	ga_ls8c_ard_3-0-0_111082_2018-04-20_final
2018-04-20 11:28:56	ga_ls8c_ard_3-0-0_111083_2018-04-20_final
2018-04-20 11:29:20	ga_ls8c_ard_3-0-0_111084_2018-04-20_final
2018-04-20 11:29:44	ga_ls8c_ard_3-0-0_111085_2018-04-20_final
2018-05-20 11:36:36	ga_ls8c_ard_3-0-0_113072_2018-05-20_final
2018-05-20 11:37:00	ga_ls8c_ard_3-0-0_113073_2018-05-20_final
2018-05-20 11:37:24	ga_ls8c_ard_3-0-0_113074_2018-05-20_final
2018-05-20 11:37:48	ga_ls8c_ard_3-0-0_113075_2018-05-20_final
2018-05-20 11:38:12	ga_ls8c_ard_3-0-0_113076_2018-05-20_final
2018-05-20 11:38:36	ga_ls8c_ard_3-0-0_113077_2018-05-20_final
2018-05-20 11:39:00	ga_ls8c_ard_3-0-0_113078_2018-05-20_final
2018-05-22 11:27:48	ga_ls8c_ard_3-0-0_111081_2018-05-22_final
2018-05-22 11:28:12	ga_ls8c_ard_3-0-0_111082_2018-05-22_final
2018-05-22 11:28:36	ga_ls8c_ard_3-0-0_111083_2018-05-22_final
2018-05-22 11:29:00	ga_ls8c_ard_3-0-0_111084_2018-05-22_final
2018-05-22 11:29:24	ga_ls8c_ard_3-0-0_111085_2018-05-22_final
2018-06-05 11:36:25	ga_ls8c_ard_3-0-0_113072_2018-06-05_final
2018-06-05 11:36:49	ga_ls8c_ard_3-1-0_113073_2018-06-05_final
2018-06-05 11:37:13	ga_ls8c_ard_3-0-0_113074_2018-06-05_final
2018-06-05 11:37:37	ga_ls8c_ard_3-0-0_113075_2018-06-05_final
2018-06-05 11:38:01	ga_ls8c_ard_3-0-0_113076_2018-06-05_final
2018-06-05 11:38:25	ga_ls8c_ard_3-0-0_113077_2018-06-05_final
2018-06-05 11:38:49	ga_ls8c_ard_3-0-0_113078_2018-06-05_final
2018-06-07 11:27:40	ga_ls8c_ard_3-0-0_111081_2018-06-07_final
2018-06-07 11:28:04	ga_ls8c_ard_3-0-0_111082_2018-06-07_final
2018-06-07 11:28:28	ga_ls8c_ard_3-0-0_111083_2018-06-07_final
2018-06-07 11:28:52	ga_ls8c_ard_3-0-0_111084_2018-06-07_final
2018-06-07 11:29:16	ga_ls8c_ard_3-0-0_111085_2018-06-07_final
2018-06-21 11:36:36	ga_ls8c_ard_3-0-0_113072_2018-06-21_final
2018-06-21 11:37:00	ga_ls8c_ard_3-0-0_113073_2018-06-21_final
2018-06-21 11:37:24	ga_ls8c_ard_3-0-0_113074_2018-06-21_final
2018-06-21 11:37:48	ga_ls8c_ard_3-0-0_113075_2018-06-21_final
2018-06-21 11:38:12	ga_ls8c_ard_3-0-0_113076_2018-06-21_final
2018-06-21 11:38:36	ga_ls8c_ard_3-0-0_113077_2018-06-21_final
2018-06-21 11:39:00	ga_ls8c_ard_3-0-0_113078_2018-06-21_final
2018-06-23 11:27:51	ga_ls8c_ard_3-0-0_111081_2018-06-23_final
2018-06-23 11:28:15	ga_ls8c_ard_3-0-0_111082_2018-06-23_final
2018-06-23 11:28:39	ga_ls8c_ard_3-0-0_111083_2018-06-23_final
2018-06-23 11:29:03	ga_ls8c_ard_3-0-0_111084_2018-06-23_final
2018-06-23 11:29:27	ga_ls8c_ard_3-0-0_111085_2018-06-23_final
2020-09-21 11:42:07	ga_ls8c_ard_3-1-0_114067_2020-09-21_final
2020-10-18 11:29:13	ga_ls8c_ard_3-1-0_111081_2020-10-18_final
2020-10-18 11:29:37	ga_ls8c_ard_3-1-0_111082_2020-10-18_final
2020-10-18 11:30:01	ga_ls8c_ard_3-1-0_111083_2020-10-18_final
2020-10-18 11:30:25	ga_ls8c_ard_3-1-0_111084_2020-10-18_final
2020-10-18 11:30:49	ga_ls8c_ard_3-1-0_111085_2020-10-18_final
2020-11-28 11:24:38	ga_ls8c_ard_3-1-0_110085_2020-11-28_final
2021-01-04 11:37:55	ga_ls8c_ard_3-2-0_113072_2021-01-04_final
2021-01-04 11:38:18	ga_ls8c_ard_3-2-0_113073_2021-01-04_final
2021-01-04 11:38:42	ga_ls8c_ard_3-2-0_113074_2021-01-04_final
2021-01-04 11:39:06	ga_ls8c_ard_3-2-0_113075_2021-01-04_final
2021-01-04 11:39:30	ga_ls8c_ard_3-2-0_113076_2021-01-04_final
2021-01-04 11:39:54	ga_ls8c_ard_3-2-0_113077_2021-01-04_final
2021-01-04 11:40:18	ga_ls8c_ard_3-2-0_113078_2021-01-04_final
2021-01-06 11:29:08	ga_ls8c_ard_3-2-0_111081_2021-01-06_final
2021-01-06 11:29:31	ga_ls8c_ard_3-2-0_111082_2021-01-06_final
2021-01-06 11:29:55	ga_ls8c_ard_3-2-0_111083_2021-01-06_final
2021-01-06 11:30:19	ga_ls8c_ard_3-2-0_111084_2021-01-06_final
2021-01-06 11:30:43	ga_ls8c_ard_3-2-0_111085_2021-01-06_final
2021-01-31 11:24:26	ga_ls8c_ard_3-2-0_110085_2021-01-31_final
2021-03-27 11:28:40	ga_ls8c_ard_3-2-0_111081_2021-03-27_final
2021-03-27 11:29:04	ga_ls8c_ard_3-2-0_111082_2021-03-27_final
2021-03-27 11:29:28	ga_ls8c_ard_3-2-0_111083_2021-03-27_final
2021-03-27 11:29:52	ga_ls8c_ard_3-2-0_111084_2021-03-27_final
2021-03-27 11:30:16	ga_ls8c_ard_3-2-0_111085_2021-03-27_final
2021-04-03 11:33:14	ga_ls8c_ard_3-2-0_112077_2021-04-03_final
2021-04-03 11:33:38	ga_ls8c_ard_3-2-0_112078_2021-04-03_final
2021-04-03 11:34:02	ga_ls8c_ard_3-2-0_112079_2021-04-03_final
2021-04-03 11:34:25	ga_ls8c_ard_3-2-0_112080_2021-04-03_final
2021-04-03 11:34:49	ga_ls8c_ard_3-2-0_112081_2021-04-03_final
2021-04-03 11:35:13	ga_ls8c_ard_3-2-0_112082_2021-04-03_final
2021-04-05 11:24:03	ga_ls8c_ard_3-2-0_110085_2021-04-05_final
2021-07-15 11:37:33	ga_ls8c_ard_3-2-0_113072_2021-07-15_final
2021-07-15 11:37:57	ga_ls8c_ard_3-2-0_113073_2021-07-15_final
2021-07-15 11:38:21	ga_ls8c_ard_3-2-0_113074_2021-07-15_final
2021-07-15 11:38:45	ga_ls8c_ard_3-2-0_113075_2021-07-15_final
2021-07-15 11:39:09	ga_ls8c_ard_3-2-0_113076_2021-07-15_final
2021-07-15 11:39:33	ga_ls8c_ard_3-2-0_113077_2021-07-15_final
2021-07-15 11:39:57	ga_ls8c_ard_3-2-0_113078_2021-07-15_final
2021-07-17 11:29:36	ga_ls8c_ard_3-2-0_111083_2021-07-17_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years