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
2019-07-19 11:31:01	ga_ls8c_ard_3-1-0_112071_2019-07-19_final
2019-07-19 11:31:25	ga_ls8c_ard_3-1-0_112072_2019-07-19_final
2019-07-19 11:31:49	ga_ls8c_ard_3-1-0_112073_2019-07-19_final
2019-07-19 11:32:13	ga_ls8c_ard_3-1-0_112074_2019-07-19_final
2019-07-19 11:32:37	ga_ls8c_ard_3-1-0_112075_2019-07-19_final
2019-07-19 11:33:01	ga_ls8c_ard_3-1-0_112076_2019-07-19_final
2019-07-21 11:22:16	ga_ls8c_ard_3-1-0_110080_2019-07-21_final
2019-07-21 11:22:40	ga_ls8c_ard_3-1-0_110081_2019-07-21_final
2019-07-21 11:23:04	ga_ls8c_ard_3-1-0_110082_2019-07-21_final
2019-07-21 11:23:28	ga_ls8c_ard_3-1-0_110083_2019-07-21_final
2019-07-21 11:23:52	ga_ls8c_ard_3-1-0_110084_2019-07-21_final
2019-07-21 11:24:16	ga_ls8c_ard_3-1-0_110085_2019-07-21_final
2019-09-05 11:31:17	ga_ls8c_ard_3-1-0_112071_2019-09-05_final
2019-09-05 11:31:41	ga_ls8c_ard_3-1-0_112072_2019-09-05_final
2019-09-05 11:32:05	ga_ls8c_ard_3-1-0_112073_2019-09-05_final
2019-09-05 11:32:28	ga_ls8c_ard_3-1-0_112074_2019-09-05_final
2019-09-05 11:32:52	ga_ls8c_ard_3-1-0_112075_2019-09-05_final
2019-09-05 11:33:16	ga_ls8c_ard_3-1-0_112076_2019-09-05_final
2019-09-07 11:22:31	ga_ls8c_ard_3-1-0_110080_2019-09-07_final
2019-09-07 11:22:55	ga_ls8c_ard_3-1-0_110081_2019-09-07_final
2019-09-07 11:23:19	ga_ls8c_ard_3-1-0_110082_2019-09-07_final
2019-09-07 11:23:43	ga_ls8c_ard_3-1-0_110083_2019-09-07_final
2019-09-07 11:24:07	ga_ls8c_ard_3-1-0_110084_2019-09-07_final
2019-09-07 11:24:31	ga_ls8c_ard_3-1-0_110085_2019-09-07_final
2019-09-16 11:18:00	ga_ls8c_ard_3-1-0_109084_2019-09-16_final
2019-09-16 11:18:24	ga_ls8c_ard_3-1-0_109085_2019-09-16_final
2019-10-09 11:22:41	ga_ls8c_ard_3-1-0_110080_2019-10-09_final
2019-10-09 11:23:05	ga_ls8c_ard_3-1-0_110081_2019-10-09_final
2019-10-09 11:23:29	ga_ls8c_ard_3-1-0_110082_2019-10-09_final
2019-10-09 11:23:52	ga_ls8c_ard_3-1-0_110083_2019-10-09_final
2019-10-09 11:24:16	ga_ls8c_ard_3-1-0_110084_2019-10-09_final
2019-10-09 11:24:40	ga_ls8c_ard_3-1-0_110085_2019-10-09_final
2019-10-16 11:26:53	ga_ls8c_ard_3-1-0_111075_2019-10-16_final
2019-10-16 11:27:17	ga_ls8c_ard_3-1-0_111076_2019-10-16_final
2019-10-16 11:27:40	ga_ls8c_ard_3-1-0_111077_2019-10-16_final
2019-10-16 11:28:04	ga_ls8c_ard_3-1-0_111078_2019-10-16_final
2019-10-16 11:28:28	ga_ls8c_ard_3-1-0_111079_2019-10-16_final
2019-10-16 11:28:52	ga_ls8c_ard_3-1-0_111080_2019-10-16_final
2019-10-16 11:29:16	ga_ls8c_ard_3-1-0_111081_2019-10-16_final
2019-10-18 11:18:07	ga_ls8c_ard_3-1-0_109084_2019-10-18_final
2019-10-18 11:18:31	ga_ls8c_ard_3-1-0_109085_2019-10-18_final
2019-10-23 11:31:28	ga_ls8c_ard_3-1-0_112071_2019-10-23_final
2019-10-23 11:31:52	ga_ls8c_ard_3-1-0_112072_2019-10-23_final
2019-10-23 11:32:16	ga_ls8c_ard_3-1-0_112073_2019-10-23_final
2019-10-23 11:32:40	ga_ls8c_ard_3-1-0_112074_2019-10-23_final
2019-10-23 11:33:04	ga_ls8c_ard_3-1-0_112075_2019-10-23_final
2019-10-23 11:33:28	ga_ls8c_ard_3-1-0_112076_2019-10-23_final
2019-10-25 11:22:42	ga_ls8c_ard_3-1-0_110080_2019-10-25_final
2019-10-25 11:23:06	ga_ls8c_ard_3-1-0_110081_2019-10-25_final
2019-10-25 11:23:30	ga_ls8c_ard_3-1-0_110082_2019-10-25_final
2019-10-25 11:23:54	ga_ls8c_ard_3-1-0_110083_2019-10-25_final
2019-10-25 11:24:18	ga_ls8c_ard_3-1-0_110084_2019-10-25_final
2019-10-25 11:24:41	ga_ls8c_ard_3-1-0_110085_2019-10-25_final
2021-11-04 11:36:04	ga_ls8c_ard_3-2-0_113067_2021-11-04_final
2021-11-04 11:38:04	ga_ls8c_ard_3-2-0_113072_2021-11-04_final
2021-11-06 11:26:53	ga_ls8c_ard_3-2-0_111075_2021-11-06_final
2021-11-06 11:27:17	ga_ls8c_ard_3-2-0_111076_2021-11-06_final
2021-11-06 11:27:41	ga_ls8c_ard_3-2-0_111077_2021-11-06_final
2021-11-06 11:28:05	ga_ls8c_ard_3-2-0_111078_2021-11-06_final
2021-11-06 11:28:29	ga_ls8c_ard_3-2-0_111079_2021-11-06_final
2021-11-06 11:28:53	ga_ls8c_ard_3-2-0_111080_2021-11-06_final
2021-11-06 11:29:17	ga_ls8c_ard_3-2-0_111081_2021-11-06_final
2022-04-24 11:22:06	ga_ls8c_ard_3-2-1_110080_2022-04-24_final
2022-04-24 11:22:30	ga_ls8c_ard_3-2-1_110081_2022-04-24_final
2022-04-24 11:22:54	ga_ls8c_ard_3-2-1_110082_2022-04-24_final
2022-04-24 11:23:18	ga_ls8c_ard_3-2-1_110083_2022-04-24_final
2022-04-24 11:23:42	ga_ls8c_ard_3-2-1_110084_2022-04-24_final
2022-04-24 11:24:05	ga_ls8c_ard_3-2-1_110085_2022-04-24_final
2022-04-29 11:37:24	ga_ls8c_ard_3-2-1_113072_2022-04-29_final
2022-05-01 11:26:16	ga_ls8c_ard_3-2-1_111075_2022-05-01_final
2022-05-01 11:26:40	ga_ls8c_ard_3-2-1_111076_2022-05-01_final
2022-05-01 11:27:04	ga_ls8c_ard_3-2-1_111077_2022-05-01_final
2022-05-01 11:27:28	ga_ls8c_ard_3-2-1_111078_2022-05-01_final
2022-05-01 11:27:52	ga_ls8c_ard_3-2-1_111079_2022-05-01_final
2022-05-01 11:28:16	ga_ls8c_ard_3-2-1_111080_2022-05-01_final
2022-05-01 11:28:40	ga_ls8c_ard_3-2-1_111081_2022-05-01_final
2022-05-03 11:17:08	ga_ls8c_ard_3-2-1_109083_2022-05-03_final
2022-05-03 11:17:32	ga_ls8c_ard_3-2-1_109084_2022-05-03_final
2022-05-08 11:31:20	ga_ls8c_ard_3-2-1_112072_2022-05-08_final
2022-05-08 11:31:44	ga_ls8c_ard_3-2-1_112073_2022-05-08_final
2022-05-08 11:32:08	ga_ls8c_ard_3-2-1_112074_2022-05-08_final
2022-05-08 11:32:32	ga_ls8c_ard_3-2-1_112075_2022-05-08_final
2022-05-08 11:32:56	ga_ls8c_ard_3-2-1_112076_2022-05-08_final
2022-05-10 11:22:11	ga_ls8c_ard_3-2-1_110080_2022-05-10_final
2022-05-10 11:22:35	ga_ls8c_ard_3-2-1_110081_2022-05-10_final
2022-05-10 11:22:59	ga_ls8c_ard_3-2-1_110082_2022-05-10_final
2022-05-10 11:23:23	ga_ls8c_ard_3-2-1_110083_2022-05-10_final
2022-05-10 11:23:47	ga_ls8c_ard_3-2-1_110084_2022-05-10_final
2022-05-10 11:24:11	ga_ls8c_ard_3-2-1_110085_2022-05-10_final
2022-07-27 11:31:50	ga_ls8c_ard_3-2-1_112072_2022-07-27_final
2022-07-27 11:32:14	ga_ls8c_ard_3-2-1_112073_2022-07-27_final
2022-07-27 11:32:38	ga_ls8c_ard_3-2-1_112074_2022-07-27_final
2022-07-27 11:33:02	ga_ls8c_ard_3-2-1_112075_2022-07-27_final
2022-07-27 11:33:26	ga_ls8c_ard_3-2-1_112076_2022-07-27_final
2022-07-29 11:22:42	ga_ls8c_ard_3-2-1_110080_2022-07-29_final
2022-07-29 11:23:06	ga_ls8c_ard_3-2-1_110081_2022-07-29_final
2022-07-29 11:23:29	ga_ls8c_ard_3-2-1_110082_2022-07-29_final
2022-07-29 11:23:53	ga_ls8c_ard_3-2-1_110083_2022-07-29_final
2022-07-29 11:24:17	ga_ls8c_ard_3-2-1_110084_2022-07-29_final
2022-07-29 11:24:41	ga_ls8c_ard_3-2-1_110085_2022-07-29_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