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
2017-03-23 11:31:54	ga_ls8c_ard_3-0-0_112074_2017-03-23_final
2017-03-25 11:23:07	ga_ls8c_ard_3-0-0_110083_2017-03-25_final
2017-03-25 11:23:31	ga_ls8c_ard_3-0-0_110084_2017-03-25_final
2017-03-25 11:23:55	ga_ls8c_ard_3-0-0_110085_2017-03-25_final
2017-05-01 11:36:56	ga_ls8c_ard_3-0-0_113072_2017-05-01_final
2017-05-01 11:37:20	ga_ls8c_ard_3-0-0_113073_2017-05-01_final
2017-05-01 11:37:44	ga_ls8c_ard_3-0-0_113074_2017-05-01_final
2017-05-01 11:38:08	ga_ls8c_ard_3-0-0_113075_2017-05-01_final
2017-05-03 11:26:57	ga_ls8c_ard_3-0-0_111078_2017-05-03_final
2017-05-03 11:27:21	ga_ls8c_ard_3-0-0_111079_2017-05-03_final
2017-05-03 11:27:45	ga_ls8c_ard_3-0-0_111080_2017-05-03_final
2017-05-03 11:28:09	ga_ls8c_ard_3-0-0_111081_2017-05-03_final
2017-05-03 11:28:33	ga_ls8c_ard_3-0-0_111082_2017-05-03_final
2017-05-03 11:28:57	ga_ls8c_ard_3-0-0_111083_2017-05-03_final
2017-05-03 11:29:21	ga_ls8c_ard_3-0-0_111084_2017-05-03_final
2017-05-08 11:41:11	ga_ls8c_ard_3-0-0_114067_2017-05-08_final
2017-05-10 11:31:38	ga_ls8c_ard_3-0-0_112074_2017-05-10_final
2017-05-10 11:32:02	ga_ls8c_ard_3-0-0_112075_2017-05-10_final
2017-05-10 11:32:26	ga_ls8c_ard_3-0-0_112076_2017-05-10_final
2017-05-10 11:32:50	ga_ls8c_ard_3-0-0_112077_2017-05-10_final
2017-05-10 11:33:14	ga_ls8c_ard_3-0-0_112078_2017-05-10_final
2017-05-10 11:33:38	ga_ls8c_ard_3-0-0_112079_2017-05-10_final
2017-05-10 11:34:02	ga_ls8c_ard_3-0-0_112080_2017-05-10_final
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
2018-02-15 11:27:53	ga_ls8c_ard_3-0-0_111079_2018-02-15_final
2018-02-15 11:28:17	ga_ls8c_ard_3-0-0_111080_2018-02-15_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
2018-03-01 11:37:21	ga_ls8c_ard_3-0-0_113072_2018-03-01_final
2018-03-01 11:37:45	ga_ls8c_ard_3-1-0_113073_2018-03-01_final
2018-03-01 11:38:09	ga_ls8c_ard_3-0-0_113074_2018-03-01_final
2018-03-01 11:38:33	ga_ls8c_ard_3-0-0_113075_2018-03-01_final
2018-03-03 11:27:46	ga_ls8c_ard_3-0-0_111079_2018-03-03_final
2018-03-03 11:28:10	ga_ls8c_ard_3-0-0_111080_2018-03-03_final
2018-03-03 11:28:34	ga_ls8c_ard_3-0-0_111081_2018-03-03_final
2018-03-03 11:28:58	ga_ls8c_ard_3-0-0_111082_2018-03-03_final
2018-03-03 11:29:22	ga_ls8c_ard_3-0-0_111083_2018-03-03_final
2018-03-03 11:29:46	ga_ls8c_ard_3-0-0_111084_2018-03-03_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
2018-04-20 11:27:20	ga_ls8c_ard_3-0-0_111079_2018-04-20_final
2018-04-20 11:27:44	ga_ls8c_ard_3-0-0_111080_2018-04-20_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
2018-05-20 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
2018-05-22 11:26:36	ga_ls8c_ard_3-0-0_111078_2018-05-22_final
2018-05-22 11:27:00	ga_ls8c_ard_3-0-0_111079_2018-05-22_final
2018-05-22 11:27:24	ga_ls8c_ard_3-0-0_111080_2018-05-22_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
2018-06-05 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
2018-06-07 11:26:28	ga_ls8c_ard_3-0-0_111078_2018-06-07_final
2018-06-07 11:26:52	ga_ls8c_ard_3-0-0_111079_2018-06-07_final
2018-06-07 11:27:16	ga_ls8c_ard_3-0-0_111080_2018-06-07_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
2018-06-12 11:40:41	ga_ls8c_ard_3-0-0_114067_2018-06-12_final
2018-06-14 11:31:09	ga_ls8c_ard_3-0-0_112074_2018-06-14_final
2018-06-14 11:31:33	ga_ls8c_ard_3-0-0_112075_2018-06-14_final
2018-06-14 11:31:56	ga_ls8c_ard_3-0-0_112076_2018-06-14_final
2018-06-14 11:32:20	ga_ls8c_ard_3-0-0_112077_2018-06-14_final
2018-06-14 11:32:44	ga_ls8c_ard_3-0-0_112078_2018-06-14_final
2018-06-14 11:33:08	ga_ls8c_ard_3-0-0_112079_2018-06-14_final
2018-06-14 11:33:32	ga_ls8c_ard_3-0-0_112080_2018-06-14_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
2018-06-23 11:26:40	ga_ls8c_ard_3-0-0_111078_2018-06-23_final
2018-06-23 11:27:03	ga_ls8c_ard_3-0-0_111079_2018-06-23_final
2018-06-23 11:27:27	ga_ls8c_ard_3-0-0_111080_2018-06-23_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
2018-06-30 11:31:19	ga_ls8c_ard_3-0-0_112074_2018-06-30_final
2018-06-30 11:31:43	ga_ls8c_ard_3-0-0_112075_2018-06-30_final
2018-06-30 11:32:07	ga_ls8c_ard_3-0-0_112076_2018-06-30_final
2018-06-30 11:32:31	ga_ls8c_ard_3-0-0_112077_2018-06-30_final
2018-06-30 11:32:54	ga_ls8c_ard_3-0-0_112078_2018-06-30_final
2018-06-30 11:33:18	ga_ls8c_ard_3-0-0_112079_2018-06-30_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