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
2019-03-10 09:24:06	ga_ls8c_ard_3-1-0_091079_2019-03-09_final
2019-03-12 10:50:37	ga_ls8c_ard_3-1-0_105079_2019-03-12_final
2019-03-13 09:54:59	ga_ls8c_ard_3-1-0_096079_2019-03-13_final
2019-03-22 09:47:35	ga_ls8c_ard_3-1-0_095076_2019-03-22_final
2019-06-17 09:54:49	ga_ls8c_ard_3-1-0_096078_2019-06-17_final
2019-06-17 09:56:49	ga_ls8c_ard_3-1-0_096083_2019-06-17_final
2019-06-30 09:24:22	ga_ls8c_ard_3-1-0_091079_2019-06-29_final
2019-07-18 10:50:09	ga_ls8c_ard_3-1-0_105077_2019-07-18_final
2019-08-17 09:24:13	ga_ls8c_ard_3-1-0_091078_2019-08-16_final
2019-08-17 09:24:37	ga_ls8c_ard_3-1-0_091079_2019-08-16_final
2019-08-24 11:09:19	ga_ls8c_ard_3-1-0_108078_2019-08-24_final
2019-08-29 09:48:11	ga_ls8c_ard_3-1-0_095076_2019-08-29_final
2019-09-02 09:24:17	ga_ls8c_ard_3-1-0_091078_2019-09-01_final
2019-09-05 09:55:35	ga_ls8c_ard_3-1-0_096079_2019-09-05_final
2019-09-14 09:48:16	ga_ls8c_ard_3-1-0_095076_2019-09-14_final
2019-09-21 09:53:17	ga_ls8c_ard_3-1-0_096073_2019-09-21_final
2019-10-06 10:51:22	ga_ls8c_ard_3-1-0_105079_2019-10-06_final
2019-10-07 09:53:21	ga_ls8c_ard_3-1-0_096073_2019-10-07_final
2019-10-07 09:55:45	ga_ls8c_ard_3-1-0_096079_2019-10-07_final
2019-10-16 09:49:35	ga_ls8c_ard_3-1-0_095079_2019-10-16_final
2019-10-20 09:24:52	ga_ls8c_ard_3-1-0_091079_2019-10-19_final
2019-10-22 10:51:24	ga_ls8c_ard_3-1-0_105079_2019-10-22_final
2019-10-27 11:08:44	ga_ls8c_ard_3-1-0_108076_2019-10-27_final
2019-11-01 09:49:35	ga_ls8c_ard_3-1-0_095079_2019-11-01_final
2019-11-23 10:52:55	ga_ls8c_ard_3-1-0_105083_2019-11-23_final
2019-11-24 09:54:06	ga_ls8c_ard_3-1-0_096075_2019-11-24_final
2020-01-04 09:49:24	ga_ls8c_ard_3-1-0_095079_2020-01-04_final
2020-01-31 11:09:14	ga_ls8c_ard_3-1-0_108078_2020-01-31_final
2020-02-16 11:09:10	ga_ls8c_ard_3-1-0_108078_2020-02-16_final
2020-02-27 10:50:59	ga_ls8c_ard_3-1-0_105079_2020-02-27_final
2020-02-28 09:55:21	ga_ls8c_ard_3-1-0_096079_2020-02-28_final
2020-03-08 09:49:07	ga_ls8c_ard_3-1-0_095079_2020-03-08_final
2020-03-08 09:51:30	ga_ls8c_ard_3-1-0_095085_2020-03-08_final
2020-03-14 10:50:52	ga_ls8c_ard_3-1-0_105079_2020-03-14_final
2020-03-15 09:54:50	ga_ls8c_ard_3-1-0_096078_2020-03-15_final
2020-03-19 11:06:34	ga_ls8c_ard_3-1-0_108072_2020-03-19_final
2020-04-04 11:06:25	ga_ls8c_ard_3-1-0_108072_2020-04-04_final
2020-04-04 11:08:48	ga_ls8c_ard_3-1-0_108078_2020-04-04_final
2020-04-16 09:51:47	ga_ls8c_ard_3-1-0_096071_2020-04-16_final
2020-05-02 09:52:50	ga_ls8c_ard_3-1-0_096074_2020-05-02_final
2022-03-30 09:47:44	ga_ls8c_ard_3-2-1_095076_2022-03-30_final
2022-04-01 09:38:10	ga_ls8c_ard_3-2-1_093083_2022-04-01_final
2022-04-03 11:00:18	ga_ls8c_ard_3-2-1_107072_2022-04-03_final
2022-04-04 10:05:53	ga_ls8c_ard_3-2-1_098075_2022-04-04_final
2022-04-05 10:47:34	ga_ls8c_ard_3-2-1_105071_2022-04-05_final
2022-04-06 11:32:26	ga_ls8c_ard_3-2-1_112075_2022-04-06_final
2022-04-08 09:43:12	ga_ls8c_ard_3-2-1_094080_2022-04-08_final
2022-04-09 10:24:53	ga_ls8c_ard_3-2-1_101076_2022-04-09_final
2022-04-10 09:32:04	ga_ls8c_ard_3-2-1_092083_2022-04-10_final
2022-04-11 10:11:20	ga_ls8c_ard_3-2-1_099073_2022-04-11_final
2022-04-12 09:17:43	ga_ls8c_ard_3-2-1_090078_2022-04-11_final
2022-04-13 10:00:35	ga_ls8c_ard_3-2-1_097077_2022-04-13_final
2022-04-13 11:40:16	ga_ls8c_ard_3-2-1_113079_2022-04-13_final
2022-04-14 10:43:51	ga_ls8c_ard_3-2-1_104077_2022-04-14_final
2022-04-15 09:47:50	ga_ls8c_ard_3-2-1_095076_2022-04-15_final
2022-04-15 09:49:26	ga_ls8c_ard_3-2-1_095080_2022-04-15_final
2022-04-17 11:15:33	ga_ls8c_ard_3-2-1_109079_2022-04-17_final
2022-04-19 11:02:47	ga_ls8c_ard_3-2-1_107078_2022-04-19_final
2022-04-20 10:05:10	ga_ls8c_ard_3-2-1_098073_2022-04-20_final
2022-04-20 10:05:58	ga_ls8c_ard_3-2-1_098075_2022-04-20_final
2022-04-22 09:55:11	ga_ls8c_ard_3-2-1_096079_2022-04-22_final
2022-04-23 10:37:15	ga_ls8c_ard_3-2-1_103076_2022-04-23_final
2022-04-23 10:38:03	ga_ls8c_ard_3-2-1_103078_2022-04-23_final
2022-04-24 09:42:01	ga_ls8c_ard_3-2-1_094077_2022-04-24_final
2022-04-24 09:42:25	ga_ls8c_ard_3-2-1_094078_2022-04-24_final
2022-04-24 11:22:06	ga_ls8c_ard_3-2-1_110080_2022-04-24_final
2022-04-28 09:18:27	ga_ls8c_ard_3-2-1_090080_2022-04-27_final
2022-04-29 09:59:43	ga_ls8c_ard_3-2-1_097075_2022-04-29_final
2022-04-29 11:40:12	ga_ls8c_ard_3-2-1_113079_2022-04-29_final
2022-05-03 11:11:56	ga_ls8c_ard_3-2-1_109070_2022-05-03_final
2022-05-08 09:55:15	ga_ls8c_ard_3-2-1_096079_2022-05-08_final
2022-05-08 09:56:03	ga_ls8c_ard_3-2-1_096081_2022-05-08_final
2022-05-08 09:56:51	ga_ls8c_ard_3-2-1_096083_2022-05-08_final
2022-05-10 11:22:11	ga_ls8c_ard_3-2-1_110080_2022-05-10_final
2022-05-14 09:18:37	ga_ls8c_ard_3-2-1_090080_2022-05-13_final
2022-05-16 10:45:09	ga_ls8c_ard_3-2-1_104080_2022-05-16_final
2022-05-19 11:16:04	ga_ls8c_ard_3-2-1_109080_2022-05-19_final
2022-05-24 09:52:07	ga_ls8c_ard_3-2-1_096071_2022-05-24_final
2022-05-24 09:53:43	ga_ls8c_ard_3-2-1_096075_2022-05-24_final
2022-05-24 09:54:07	ga_ls8c_ard_3-2-1_096076_2022-05-24_final
2022-05-24 11:34:12	ga_ls8c_ard_3-2-1_112079_2022-05-24_final
2022-05-25 10:38:10	ga_ls8c_ard_3-2-1_103078_2022-05-25_final
2022-05-25 10:38:34	ga_ls8c_ard_3-2-1_103079_2022-05-25_final
2022-05-31 10:00:44	ga_ls8c_ard_3-2-1_097077_2022-05-31_final
2022-06-02 11:28:53	ga_ls8c_ard_3-2-1_111081_2022-06-02_final
2022-06-03 10:29:41	ga_ls8c_ard_3-2-1_102072_2022-06-03_final
2022-06-04 11:12:10	ga_ls8c_ard_3-2-1_109070_2022-06-04_final
2022-06-07 10:08:37	ga_ls8c_ard_3-2-1_098081_2022-06-07_final
2022-06-08 10:47:30	ga_ls8c_ard_3-2-1_105070_2022-06-08_final
2022-06-08 10:50:41	ga_ls8c_ard_3-2-1_105078_2022-06-08_final
2022-06-15 10:58:57	ga_ls8c_ard_3-2-1_106083_2022-06-15_final
2022-06-16 10:00:08	ga_ls8c_ard_3-2-1_097075_2022-06-16_final
2022-06-16 10:00:32	ga_ls8c_ard_3-2-1_097076_2022-06-16_final
2022-06-16 10:02:32	ga_ls8c_ard_3-2-1_097081_2022-06-16_final
2022-06-17 10:41:01	ga_ls8c_ard_3-2-1_104069_2022-06-17_final
2022-06-17 10:43:25	ga_ls8c_ard_3-2-1_104075_2022-06-17_final
2022-06-17 10:44:36	ga_ls8c_ard_3-2-1_104078_2022-06-17_final
2022-06-18 09:49:47	ga_ls8c_ard_3-2-1_095080_2022-06-18_final
2022-06-19 10:29:52	ga_ls8c_ard_3-2-1_102072_2022-06-19_final
2022-06-20 09:37:03	ga_ls8c_ard_3-2-1_093079_2022-06-20_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