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
2021-12-20 11:52:20	ga_ls8c_ard_3-2-1_115077_2021-12-20_final
2021-12-31 11:32:55	ga_ls8c_ard_3-2-1_112075_2021-12-31_final
2022-01-05 10:14:58	ga_ls8c_ard_3-2-1_099081_2022-01-05_final
2022-01-07 09:59:24	ga_ls8c_ard_3-2-1_097073_2022-01-07_final
2022-01-12 10:20:20	ga_ls8c_ard_3-2-1_100079_2022-01-12_final
2022-01-13 09:25:54	ga_ls8c_ard_3-2-1_091082_2022-01-12_final
2022-01-13 11:00:48	ga_ls8c_ard_3-2-1_107072_2022-01-13_final
2022-01-18 11:22:54	ga_ls8c_ard_3-2-1_110081_2022-01-18_final
2022-01-19 10:26:53	ga_ls8c_ard_3-2-1_101080_2022-01-19_final
2022-01-25 11:26:39	ga_ls8c_ard_3-2-1_111075_2022-01-25_final
2022-01-28 11:57:55	ga_ls8c_ard_3-2-1_116076_2022-01-28_final
2022-02-05 11:09:40	ga_ls8c_ard_3-2-1_108079_2022-02-05_final
2022-02-06 10:12:27	ga_ls8c_ard_3-2-1_099075_2022-02-06_final
2022-02-07 10:56:30	ga_ls8c_ard_3-2-1_106077_2022-02-07_final
2022-02-16 10:52:16	ga_ls8c_ard_3-2-1_105082_2022-02-16_final
2022-02-17 09:55:02	ga_ls8c_ard_3-2-1_096078_2022-02-17_final
2022-02-17 09:55:26	ga_ls8c_ard_3-2-1_096079_2022-02-17_final
2022-02-25 10:43:15	ga_ls8c_ard_3-2-1_104075_2022-02-25_final
2022-02-27 10:30:29	ga_ls8c_ard_3-2-1_102074_2022-02-27_final
2022-03-03 11:46:38	ga_ls8c_ard_3-2-1_114079_2022-03-03_final
2022-03-07 09:43:49	ga_ls8c_ard_3-2-1_094081_2022-03-07_final
2022-03-10 10:11:30	ga_ls8c_ard_3-2-1_099073_2022-03-10_final
2022-03-11 09:19:28	ga_ls8c_ard_3-2-1_090082_2022-03-10_final
2022-03-11 10:57:33	ga_ls8c_ard_3-2-1_106080_2022-03-11_final
2022-03-12 09:57:32	ga_ls8c_ard_3-2-1_097069_2022-03-12_final
2022-03-29 10:43:22	ga_ls8c_ard_3-2-1_104076_2022-03-29_final
2022-04-06 11:34:02	ga_ls8c_ard_3-2-1_112079_2022-04-06_final
2022-04-13 11:40:16	ga_ls8c_ard_3-2-1_113079_2022-04-13_final
2022-04-17 09:34:41	ga_ls8c_ard_3-2-1_093074_2022-04-17_final
2022-04-26 11:08:07	ga_ls8c_ard_3-2-1_108076_2022-04-26_final
2022-04-29 11:41:24	ga_ls8c_ard_3-2-1_113082_2022-04-29_final
2022-05-02 10:31:04	ga_ls8c_ard_3-2-1_102076_2022-05-02_final
2022-05-09 10:36:07	ga_ls8c_ard_3-2-1_103073_2022-05-09_final
2022-05-17 11:27:37	ga_ls8c_ard_3-2-1_111078_2022-05-17_final
2022-05-21 11:00:31	ga_ls8c_ard_3-2-1_107072_2022-05-21_final
2022-05-23 10:48:33	ga_ls8c_ard_3-2-1_105073_2022-05-23_final
2022-06-04 09:35:17	ga_ls8c_ard_3-2-1_093075_2022-06-04_final
2022-06-08 09:12:36	ga_ls8c_ard_3-2-1_089080_2022-06-07_final
2022-06-13 09:34:48	ga_ls8c_ard_3-2-1_092089_2022-06-13_final
2022-06-27 11:23:20	ga_ls8c_ard_3-2-1_110082_2022-06-27_final
2022-06-28 10:24:55	ga_ls8c_ard_3-2-1_101075_2022-06-28_final
2022-07-01 10:57:01	ga_ls8c_ard_3-2-1_106078_2022-07-01_final
2022-07-09 10:06:23	ga_ls8c_ard_3-2-1_098075_2022-07-09_final
2022-07-11 11:35:18	ga_ls8c_ard_3-2-1_112081_2022-07-11_final
2022-07-19 10:41:06	ga_ls8c_ard_3-2-1_104069_2022-07-19_final
2022-07-23 11:58:07	ga_ls8c_ard_3-2-1_116076_2022-07-23_final
2022-07-24 09:22:01	ga_ls8c_ard_3-2-1_091072_2022-07-23_final
2022-07-26 10:47:46	ga_ls8c_ard_3-2-1_105070_2022-07-26_final
2022-08-09 09:26:10	ga_ls8c_ard_3-2-1_091082_2022-08-08_final
2022-08-14 11:24:01	ga_ls8c_ard_3-2-1_110083_2022-08-14_final
2022-08-16 09:29:59	ga_ls8c_ard_3-2-1_092076_2022-08-15_final
2022-08-16 11:06:04	ga_ls8c_ard_3-2-1_108069_2022-08-16_final
2022-08-16 11:08:52	ga_ls8c_ard_3-2-1_108076_2022-08-16_final
2022-08-18 10:57:19	ga_ls8c_ard_3-2-1_106078_2022-08-18_final
2022-08-21 09:48:32	ga_ls8c_ard_3-2-1_095076_2022-08-21_final
2022-08-21 11:27:49	ga_ls8c_ard_3-2-1_111077_2022-08-21_final
2022-08-21 11:29:25	ga_ls8c_ard_3-2-1_111081_2022-08-21_final
2022-08-23 09:36:35	ga_ls8c_ard_3-2-1_093077_2022-08-23_final
2022-08-28 09:58:18	ga_ls8c_ard_3-2-1_096085_2022-08-28_final
2022-09-05 10:43:46	ga_ls8c_ard_3-2-1_104075_2022-09-05_final
2022-09-05 10:44:10	ga_ls8c_ard_3-2-1_104076_2022-09-05_final
2022-09-09 11:58:22	ga_ls8c_ard_3-2-1_116076_2022-09-09_final
2022-09-13 09:56:00	ga_ls8c_ard_3-2-1_096079_2022-09-13_final
2022-09-13 11:35:41	ga_ls8c_ard_3-2-1_112081_2022-09-13_final
2022-09-19 09:18:56	ga_ls8c_ard_3-2-1_090079_2022-09-18_final
2022-09-19 10:57:02	ga_ls8c_ard_3-2-1_106077_2022-09-19_final
2022-10-08 11:29:51	ga_ls8c_ard_3-2-1_111082_2022-10-08_final
2022-10-13 11:47:31	ga_ls8c_ard_3-2-1_114080_2022-10-13_final
2022-10-17 11:24:50	ga_ls8c_ard_3-2-1_110085_2022-10-17_final
2022-10-28 11:01:36	ga_ls8c_ard_3-2-1_107073_2022-10-28_final
2022-10-31 09:56:49	ga_ls8c_ard_3-2-1_096081_2022-10-31_final
2022-11-04 11:08:59	ga_ls8c_ard_3-2-1_108076_2022-11-04_final
2022-11-04 11:11:23	ga_ls8c_ard_3-2-1_108082_2022-11-04_final
2022-11-07 11:39:29	ga_ls8c_ard_3-2-1_113075_2022-11-07_final
2022-11-11 09:36:14	ga_ls8c_ard_3-2-1_093076_2022-11-11_final
2022-11-18 09:40:20	ga_ls8c_ard_3-2-1_094071_2022-11-18_final
2022-11-20 09:31:11	ga_ls8c_ard_3-2-1_092079_2022-11-20_final
2022-11-29 11:04:43	ga_ls8c_ard_3-2-1_107081_2022-11-29_final
2022-11-30 10:06:42	ga_ls8c_ard_3-2-1_098075_2022-11-30_final
2022-12-03 10:38:48	ga_ls8c_ard_3-2-1_103078_2022-12-03_final
2022-12-03 10:39:36	ga_ls8c_ard_3-2-1_103080_2022-12-03_final
2022-12-07 10:12:52	ga_ls8c_ard_3-2-1_099075_2022-12-07_final
2022-12-10 10:44:33	ga_ls8c_ard_3-2-1_104077_2022-12-10_final
2022-12-14 11:58:41	ga_ls8c_ard_3-2-1_116077_2022-12-14_final
2023-01-01 11:45:50	ga_ls8c_ard_3-2-1_114076_2023-01-01_final
2023-01-17 10:08:01	ga_ls8c_ard_3-2-1_098079_2023-01-17_final
2023-02-27 10:00:49	ga_ls8c_ard_3-2-1_097077_2023-02-27_final
2023-03-05 11:02:59	ga_ls8c_ard_3-2-1_107078_2023-03-05_final
2023-03-05 11:04:35	ga_ls8c_ard_3-2-1_107082_2023-03-05_final
2023-03-19 09:37:33	ga_ls8c_ard_3-2-1_093081_2023-03-19_final
2023-03-30 09:18:06	ga_ls8c_ard_3-2-1_090079_2023-03-29_final
2023-04-17 10:41:10	ga_ls8c_ard_3-2-1_104071_2023-04-17_final
2023-04-20 09:35:33	ga_ls8c_ard_3-2-1_093077_2023-04-20_final
2023-04-20 11:14:26	ga_ls8c_ard_3-2-1_109077_2023-04-20_final
2023-04-21 11:57:42	ga_ls8c_ard_3-2-1_116077_2023-04-21_final
2023-04-27 11:23:48	ga_ls8c_ard_3-2-1_110085_2023-04-27_final
2023-05-07 10:20:17	ga_ls8c_ard_3-2-1_100081_2023-05-07_final
2023-05-08 11:00:20	ga_ls8c_ard_3-2-1_107073_2023-05-08_final
2023-05-09 11:44:23	ga_ls8c_ard_3-2-1_114075_2023-05-09_final
2023-05-13 11:21:35	ga_ls8c_ard_3-2-1_110080_2023-05-13_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