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
2019-01-26 11:22:29	ga_ls8c_ard_3-0-0_110081_2019-01-26_final
2019-01-26 11:22:53	ga_ls8c_ard_3-0-0_110082_2019-01-26_final
2019-01-26 11:23:17	ga_ls8c_ard_3-0-0_110083_2019-01-26_final
2019-01-26 11:23:41	ga_ls8c_ard_3-0-0_110084_2019-01-26_final
2019-01-26 11:24:05	ga_ls8c_ard_3-0-0_110085_2019-01-26_final
2019-02-16 11:35:24	ga_ls8c_ard_3-0-0_113067_2019-02-16_final
2019-02-16 11:37:23	ga_ls8c_ard_3-0-0_113072_2019-02-16_final
2019-02-16 11:37:47	ga_ls8c_ard_3-0-0_113073_2019-02-16_final
2019-02-20 11:17:26	ga_ls8c_ard_3-0-0_109084_2019-02-20_final
2019-02-20 11:17:50	ga_ls8c_ard_3-0-0_109085_2019-02-20_final
2019-03-22 11:26:28	ga_ls8c_ard_3-1-0_111076_2019-03-22_final
2019-03-22 11:26:52	ga_ls8c_ard_3-1-0_111077_2019-03-22_final
2019-03-22 11:27:16	ga_ls8c_ard_3-1-0_111078_2019-03-22_final
2019-03-22 11:27:39	ga_ls8c_ard_3-1-0_111079_2019-03-22_final
2019-03-22 11:28:03	ga_ls8c_ard_3-1-0_111080_2019-03-22_final
2019-03-22 11:28:27	ga_ls8c_ard_3-1-0_111081_2019-03-22_final
2019-03-22 11:28:51	ga_ls8c_ard_3-1-0_111082_2019-03-22_final
2019-03-24 11:17:17	ga_ls8c_ard_3-1-0_109084_2019-03-24_final
2019-03-24 11:17:41	ga_ls8c_ard_3-1-0_109085_2019-03-24_final
2019-07-01 11:41:44	ga_ls8c_ard_3-1-0_114067_2019-07-01_final
2019-07-03 11:31:23	ga_ls8c_ard_3-1-0_112072_2019-07-03_final
2019-07-03 11:31:47	ga_ls8c_ard_3-1-0_112073_2019-07-03_final
2019-07-03 11:32:11	ga_ls8c_ard_3-1-0_112074_2019-07-03_final
2019-07-03 11:32:35	ga_ls8c_ard_3-1-0_112075_2019-07-03_final
2019-07-03 11:32:58	ga_ls8c_ard_3-1-0_112076_2019-07-03_final
2019-07-03 11:33:22	ga_ls8c_ard_3-1-0_112077_2019-07-03_final
2019-09-03 11:42:02	ga_ls8c_ard_3-1-0_114067_2019-09-03_final
2019-10-05 11:42:12	ga_ls8c_ard_3-1-0_114067_2019-10-05_final
2019-10-07 11:31:50	ga_ls8c_ard_3-1-0_112072_2019-10-07_final
2019-10-07 11:32:14	ga_ls8c_ard_3-1-0_112073_2019-10-07_final
2019-10-07 11:32:38	ga_ls8c_ard_3-1-0_112074_2019-10-07_final
2019-10-07 11:33:02	ga_ls8c_ard_3-1-0_112075_2019-10-07_final
2019-10-07 11:33:26	ga_ls8c_ard_3-1-0_112076_2019-10-07_final
2019-10-07 11:33:50	ga_ls8c_ard_3-1-0_112077_2019-10-07_final
2019-10-21 11:42:14	ga_ls8c_ard_3-1-0_114067_2019-10-21_final
2023-04-04 11:17:26	ga_ls8c_ard_3-2-1_109084_2023-04-04_final
2023-04-09 11:31:04	ga_ls8c_ard_3-2-1_112072_2023-04-09_final
2023-04-09 11:31:28	ga_ls8c_ard_3-2-1_112073_2023-04-09_final
2023-04-09 11:31:52	ga_ls8c_ard_3-2-1_112074_2023-04-09_final
2023-04-09 11:32:16	ga_ls8c_ard_3-2-1_112075_2023-04-09_final
2023-04-09 11:32:40	ga_ls8c_ard_3-2-1_112076_2023-04-09_final
2023-04-09 11:33:04	ga_ls8c_ard_3-2-1_112077_2023-04-09_final
2023-04-11 11:22:16	ga_ls8c_ard_3-2-1_110081_2023-04-11_final
2023-04-11 11:22:40	ga_ls8c_ard_3-2-1_110082_2023-04-11_final
2023-04-11 11:23:03	ga_ls8c_ard_3-2-1_110083_2023-04-11_final
2023-04-11 11:23:27	ga_ls8c_ard_3-2-1_110084_2023-04-11_final
2023-04-11 11:23:51	ga_ls8c_ard_3-2-1_110085_2023-04-11_final
2023-07-14 11:32:46	ga_ls8c_ard_3-2-1_112076_2023-07-14_final
2023-07-14 11:33:10	ga_ls8c_ard_3-2-1_112077_2023-07-14_final
2023-07-16 11:22:00	ga_ls8c_ard_3-2-1_110080_2023-07-16_final
2023-07-16 11:22:24	ga_ls8c_ard_3-2-1_110081_2023-07-16_final
2023-07-16 11:22:48	ga_ls8c_ard_3-2-1_110082_2023-07-16_final
2023-07-16 11:23:12	ga_ls8c_ard_3-2-1_110083_2023-07-16_final
2023-07-16 11:23:36	ga_ls8c_ard_3-2-1_110084_2023-07-16_final
2023-07-16 11:24:00	ga_ls8c_ard_3-2-1_110085_2023-07-16_final
2023-08-08 11:26:44	ga_ls8c_ard_3-2-1_111076_2023-08-08_final
2023-08-08 11:27:08	ga_ls8c_ard_3-2-1_111077_2023-08-08_final
2023-08-08 11:27:32	ga_ls8c_ard_3-2-1_111078_2023-08-08_final
2023-08-08 11:27:56	ga_ls8c_ard_3-2-1_111079_2023-08-08_final
2023-08-08 11:28:20	ga_ls8c_ard_3-2-1_111080_2023-08-08_final
2023-08-08 11:28:44	ga_ls8c_ard_3-2-1_111081_2023-08-08_final
2023-08-08 11:29:08	ga_ls8c_ard_3-2-1_111082_2023-08-08_final
2023-08-17 11:22:14	ga_ls8c_ard_3-2-1_110080_2023-08-17_final
2023-08-17 11:22:38	ga_ls8c_ard_3-2-1_110081_2023-08-17_final
2023-08-17 11:23:02	ga_ls8c_ard_3-2-1_110082_2023-08-17_final
2023-08-17 11:23:26	ga_ls8c_ard_3-2-1_110083_2023-08-17_final
2023-08-17 11:23:50	ga_ls8c_ard_3-2-1_110084_2023-08-17_final
2023-08-17 11:24:14	ga_ls8c_ard_3-2-1_110085_2023-08-17_final
2023-12-05 11:31:35	ga_ls8c_ard_3-2-1_112072_2023-12-05_final
2023-12-05 11:31:59	ga_ls8c_ard_3-2-1_112073_2023-12-05_final
2023-12-05 11:32:23	ga_ls8c_ard_3-2-1_112074_2023-12-05_final
2023-12-05 11:32:47	ga_ls8c_ard_3-2-1_112075_2023-12-05_final
2023-12-05 11:33:11	ga_ls8c_ard_3-2-1_112076_2023-12-05_final
2023-12-05 11:33:35	ga_ls8c_ard_3-2-1_112077_2023-12-05_final
2023-12-07 11:22:47	ga_ls8c_ard_3-2-1_110081_2023-12-07_final
2023-12-07 11:23:11	ga_ls8c_ard_3-2-1_110082_2023-12-07_final
2023-12-07 11:23:35	ga_ls8c_ard_3-2-1_110083_2023-12-07_final
2023-12-07 11:23:59	ga_ls8c_ard_3-2-1_110084_2023-12-07_final
2023-12-07 11:24:23	ga_ls8c_ard_3-2-1_110085_2023-12-07_final
2023-12-12 11:37:48	ga_ls8c_ard_3-2-1_113072_2023-12-12_final
2023-12-12 11:38:12	ga_ls8c_ard_3-2-1_113073_2023-12-12_final
2023-12-14 11:27:04	ga_ls8c_ard_3-2-1_111076_2023-12-14_final
2023-12-14 11:27:28	ga_ls8c_ard_3-2-1_111077_2023-12-14_final
2023-12-14 11:27:52	ga_ls8c_ard_3-2-1_111078_2023-12-14_final
2023-12-14 11:28:16	ga_ls8c_ard_3-2-1_111079_2023-12-14_final
2023-12-14 11:28:39	ga_ls8c_ard_3-2-1_111080_2023-12-14_final
2023-12-14 11:29:03	ga_ls8c_ard_3-2-1_111081_2023-12-14_final
2023-12-14 11:29:27	ga_ls8c_ard_3-2-1_111082_2023-12-14_final
2023-12-16 11:17:55	ga_ls8c_ard_3-2-1_109084_2023-12-16_final
2023-12-21 11:31:41	ga_ls8c_ard_3-2-1_112072_2023-12-21_final
2023-12-21 11:32:05	ga_ls8c_ard_3-2-1_112073_2023-12-21_final
2023-12-21 11:32:29	ga_ls8c_ard_3-2-1_112074_2023-12-21_final
2023-12-21 11:32:53	ga_ls8c_ard_3-2-1_112075_2023-12-21_final
2023-12-21 11:33:17	ga_ls8c_ard_3-2-1_112076_2023-12-21_final
2023-12-21 11:33:41	ga_ls8c_ard_3-2-1_112077_2023-12-21_final
2023-12-23 11:22:31	ga_ls8c_ard_3-2-1_110080_2023-12-23_final
2023-12-23 11:22:55	ga_ls8c_ard_3-2-1_110081_2023-12-23_final
2023-12-23 11:23:19	ga_ls8c_ard_3-2-1_110082_2023-12-23_final
2023-12-23 11:23:43	ga_ls8c_ard_3-2-1_110083_2023-12-23_final
2023-12-23 11:24:07	ga_ls8c_ard_3-2-1_110084_2023-12-23_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