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:

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First 100 results (query limit)

Time (local)	Label
2022-08-26 10:06:17	ga_ls8c_ard_3-2-1_098074_2022-08-26_final
2022-08-26 10:07:05	ga_ls8c_ard_3-2-1_098076_2022-08-26_final
2022-09-11 10:09:08	ga_ls8c_ard_3-2-1_098081_2022-09-11_final
2022-09-14 10:38:52	ga_ls8c_ard_3-2-1_103078_2022-09-14_final
2022-09-17 11:10:35	ga_ls8c_ard_3-2-1_108080_2022-09-17_final
2022-09-20 11:40:17	ga_ls8c_ard_3-2-1_113077_2022-09-20_final
2022-09-21 10:42:16	ga_ls8c_ard_3-2-1_104071_2022-09-21_final
2022-09-21 10:44:40	ga_ls8c_ard_3-2-1_104077_2022-09-21_final
2022-09-23 10:33:30	ga_ls8c_ard_3-2-1_102080_2022-09-23_final
2022-09-26 11:03:37	ga_ls8c_ard_3-2-1_107078_2022-09-26_final
2022-09-27 10:07:11	ga_ls8c_ard_3-2-1_098076_2022-09-27_final
2022-09-27 10:09:35	ga_ls8c_ard_3-2-1_098082_2022-09-27_final
2022-09-28 10:48:03	ga_ls8c_ard_3-2-1_105070_2022-09-28_final
2022-09-28 10:51:39	ga_ls8c_ard_3-2-1_105079_2022-09-28_final
2022-09-29 11:34:06	ga_ls8c_ard_3-2-1_112077_2022-09-29_final
2022-09-30 10:37:41	ga_ls8c_ard_3-2-1_103075_2022-09-30_final
2022-10-01 09:42:03	ga_ls8c_ard_3-2-1_094075_2022-10-01_final
2022-10-04 10:13:20	ga_ls8c_ard_3-2-1_099076_2022-10-04_final
2022-10-06 11:40:38	ga_ls8c_ard_3-2-1_113078_2022-10-06_final
2022-10-06 11:41:02	ga_ls8c_ard_3-2-1_113079_2022-10-06_final
2022-10-07 10:45:24	ga_ls8c_ard_3-2-1_104079_2022-10-07_final
2022-10-08 11:28:15	ga_ls8c_ard_3-2-1_111078_2022-10-08_final
2022-10-08 11:29:03	ga_ls8c_ard_3-2-1_111080_2022-10-08_final
2022-10-09 10:33:01	ga_ls8c_ard_3-2-1_102079_2022-10-09_final
2022-10-14 10:51:29	ga_ls8c_ard_3-2-1_105079_2022-10-14_final
2022-10-15 09:54:17	ga_ls8c_ard_3-2-1_096075_2022-10-15_final
2022-10-15 11:33:34	ga_ls8c_ard_3-2-1_112076_2022-10-15_final
2022-10-17 11:22:02	ga_ls8c_ard_3-2-1_110078_2022-10-17_final
2022-10-17 11:22:26	ga_ls8c_ard_3-2-1_110079_2022-10-17_final
2022-10-17 11:24:02	ga_ls8c_ard_3-2-1_110083_2022-10-17_final
2022-10-18 10:23:14	ga_ls8c_ard_3-2-1_101070_2022-10-18_final
2022-10-20 10:12:53	ga_ls8c_ard_3-2-1_099075_2022-10-20_final
2022-10-23 10:42:14	ga_ls8c_ard_3-2-1_104071_2022-10-23_final
2022-10-24 11:28:17	ga_ls8c_ard_3-2-1_111078_2022-10-24_final
2022-10-25 10:32:16	ga_ls8c_ard_3-2-1_102077_2022-10-25_final
2022-10-31 09:55:13	ga_ls8c_ard_3-2-1_096077_2022-10-31_final
2022-10-31 11:35:18	ga_ls8c_ard_3-2-1_112080_2022-10-31_final
2022-11-06 10:59:25	ga_ls8c_ard_3-2-1_106083_2022-11-06_final
2022-11-07 10:00:35	ga_ls8c_ard_3-2-1_097075_2022-11-07_final
2022-11-07 11:40:40	ga_ls8c_ard_3-2-1_113078_2022-11-07_final
2022-11-08 10:42:15	ga_ls8c_ard_3-2-1_104071_2022-11-08_final
2022-11-08 10:42:39	ga_ls8c_ard_3-2-1_104072_2022-11-08_final
2022-11-08 10:46:14	ga_ls8c_ard_3-2-1_104081_2022-11-08_final
2022-11-09 09:49:01	ga_ls8c_ard_3-2-1_095077_2022-11-09_final
2022-11-09 09:49:49	ga_ls8c_ard_3-2-1_095079_2022-11-09_final
2022-11-09 09:50:13	ga_ls8c_ard_3-2-1_095080_2022-11-09_final
2022-11-11 11:12:44	ga_ls8c_ard_3-2-1_109070_2022-11-11_final
2022-11-13 11:03:32	ga_ls8c_ard_3-2-1_107078_2022-11-13_final
2022-11-15 10:51:33	ga_ls8c_ard_3-2-1_105079_2022-11-15_final
2022-11-16 11:34:00	ga_ls8c_ard_3-2-1_112077_2022-11-16_final
2022-11-18 09:41:56	ga_ls8c_ard_3-2-1_094075_2022-11-18_final
2022-11-23 11:40:11	ga_ls8c_ard_3-2-1_113077_2022-11-23_final
2022-11-24 10:42:34	ga_ls8c_ard_3-2-1_104072_2022-11-24_final
2022-11-24 10:46:10	ga_ls8c_ard_3-2-1_104081_2022-11-24_final
2022-11-25 09:50:09	ga_ls8c_ard_3-2-1_095080_2022-11-25_final
2022-11-28 10:19:04	ga_ls8c_ard_3-2-1_100075_2022-11-28_final
2022-11-29 11:03:31	ga_ls8c_ard_3-2-1_107078_2022-11-29_final
2022-12-02 09:54:21	ga_ls8c_ard_3-2-1_096075_2022-12-02_final
2022-12-02 11:35:13	ga_ls8c_ard_3-2-1_112080_2022-12-02_final
2022-12-03 10:39:12	ga_ls8c_ard_3-2-1_103079_2022-12-03_final
2022-12-06 11:09:18	ga_ls8c_ard_3-2-1_108077_2022-12-06_final
2022-12-10 10:43:45	ga_ls8c_ard_3-2-1_104075_2022-12-10_final
2022-12-10 10:45:21	ga_ls8c_ard_3-2-1_104079_2022-12-10_final
2022-12-11 09:49:43	ga_ls8c_ard_3-2-1_095079_2022-12-11_final
2022-12-11 09:50:07	ga_ls8c_ard_3-2-1_095080_2022-12-11_final
2022-12-11 11:28:36	ga_ls8c_ard_3-2-1_111079_2022-12-11_final
2022-12-18 11:34:42	ga_ls8c_ard_3-2-1_112079_2022-12-18_final
2022-12-19 10:39:04	ga_ls8c_ard_3-2-1_103079_2022-12-19_final
2022-12-25 11:40:50	ga_ls8c_ard_3-2-1_113079_2022-12-25_final
2022-12-26 10:45:13	ga_ls8c_ard_3-2-1_104079_2022-12-26_final
2022-12-27 09:48:00	ga_ls8c_ard_3-2-1_095075_2022-12-27_final
2022-12-29 09:38:27	ga_ls8c_ard_3-2-1_093082_2022-12-29_final
2023-01-03 11:34:41	ga_ls8c_ard_3-2-1_112079_2023-01-03_final
2023-01-04 10:39:03	ga_ls8c_ard_3-2-1_103079_2023-01-04_final
2023-01-05 11:22:19	ga_ls8c_ard_3-2-1_110079_2023-01-05_final
2023-01-05 11:23:55	ga_ls8c_ard_3-2-1_110083_2023-01-05_final
2023-01-10 11:40:01	ga_ls8c_ard_3-2-1_113077_2023-01-10_final
2023-01-12 09:49:09	ga_ls8c_ard_3-2-1_095078_2023-01-12_final
2023-01-17 10:08:49	ga_ls8c_ard_3-2-1_098081_2023-01-17_final
2023-01-19 11:34:33	ga_ls8c_ard_3-2-1_112079_2023-01-19_final
2023-01-20 10:37:21	ga_ls8c_ard_3-2-1_103075_2023-01-20_final
2023-01-21 09:42:56	ga_ls8c_ard_3-2-1_094078_2023-01-21_final
2023-01-26 11:39:37	ga_ls8c_ard_3-2-1_113076_2023-01-26_final
2023-02-05 10:39:01	ga_ls8c_ard_3-2-1_103079_2023-02-05_final
2023-02-06 09:42:59	ga_ls8c_ard_3-2-1_094078_2023-02-06_final
2023-02-06 09:44:59	ga_ls8c_ard_3-2-1_094083_2023-02-06_final
2023-02-06 11:22:16	ga_ls8c_ard_3-2-1_110079_2023-02-06_final
2023-02-14 10:32:20	ga_ls8c_ard_3-2-1_102078_2023-02-14_final
2023-02-14 10:33:08	ga_ls8c_ard_3-2-1_102080_2023-02-14_final
2023-02-17 11:03:12	ga_ls8c_ard_3-2-1_107078_2023-02-17_final
2023-02-18 10:09:09	ga_ls8c_ard_3-2-1_098082_2023-02-18_final
2023-02-19 10:51:12	ga_ls8c_ard_3-2-1_105079_2023-02-19_final
2023-02-20 09:56:45	ga_ls8c_ard_3-2-1_096082_2023-02-20_final
2023-02-22 09:41:33	ga_ls8c_ard_3-2-1_094075_2023-02-22_final
2023-02-22 11:22:02	ga_ls8c_ard_3-2-1_110079_2023-02-22_final
2023-02-23 10:26:23	ga_ls8c_ard_3-2-1_101079_2023-02-23_final
2023-02-27 10:03:13	ga_ls8c_ard_3-2-1_097083_2023-02-27_final
2023-02-27 11:40:06	ga_ls8c_ard_3-2-1_113078_2023-02-27_final
2023-03-02 10:32:31	ga_ls8c_ard_3-2-1_102079_2023-03-02_final
2023-03-03 09:37:17	ga_ls8c_ard_3-2-1_093080_2023-03-03_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