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
2022-06-15 09:19:40	ga_ls8c_ard_3-2-1_090082_2022-06-14_final
2022-07-01 10:56:37	ga_ls8c_ard_3-2-1_106077_2022-07-01_final
2022-07-04 09:49:50	ga_ls8c_ard_3-2-1_095080_2022-07-04_final
2022-07-04 11:27:08	ga_ls8c_ard_3-2-1_111076_2022-07-04_final
2022-07-05 10:31:30	ga_ls8c_ard_3-2-1_102076_2022-07-05_final
2022-07-12 10:36:52	ga_ls8c_ard_3-2-1_103074_2022-07-12_final
2022-07-13 09:42:27	ga_ls8c_ard_3-2-1_094077_2022-07-13_final
2022-07-17 10:56:37	ga_ls8c_ard_3-2-1_106077_2022-07-17_final
2022-07-17 10:57:01	ga_ls8c_ard_3-2-1_106078_2022-07-17_final
2022-07-19 10:41:06	ga_ls8c_ard_3-2-1_104069_2022-07-19_final
2022-07-19 10:43:05	ga_ls8c_ard_3-2-1_104074_2022-07-19_final
2022-07-19 10:43:29	ga_ls8c_ard_3-2-1_104075_2022-07-19_final
2022-07-19 10:45:05	ga_ls8c_ard_3-2-1_104079_2022-07-19_final
2022-07-20 09:47:53	ga_ls8c_ard_3-2-1_095075_2022-07-20_final
2022-07-24 11:03:18	ga_ls8c_ard_3-2-1_107078_2022-07-24_final
2022-07-24 11:03:42	ga_ls8c_ard_3-2-1_107079_2022-07-24_final
2022-07-25 10:09:17	ga_ls8c_ard_3-2-1_098082_2022-07-25_final
2022-07-26 10:51:22	ga_ls8c_ard_3-2-1_105079_2022-07-26_final
2022-07-27 09:56:33	ga_ls8c_ard_3-2-1_096081_2022-07-27_final
2022-07-29 09:42:13	ga_ls8c_ard_3-2-1_094076_2022-07-29_final
2022-07-29 09:42:37	ga_ls8c_ard_3-2-1_094077_2022-07-29_final
2022-07-31 11:07:10	ga_ls8c_ard_3-2-1_108072_2022-07-31_final
2022-08-03 11:39:41	ga_ls8c_ard_3-2-1_113076_2022-08-03_final
2022-08-04 10:44:28	ga_ls8c_ard_3-2-1_104077_2022-08-04_final
2022-08-05 09:48:27	ga_ls8c_ard_3-2-1_095076_2022-08-05_final
2022-08-05 11:28:56	ga_ls8c_ard_3-2-1_111080_2022-08-05_final
2022-08-07 09:36:55	ga_ls8c_ard_3-2-1_093078_2022-08-07_final
2022-08-09 11:01:03	ga_ls8c_ard_3-2-1_107072_2022-08-09_final
2022-08-09 11:05:03	ga_ls8c_ard_3-2-1_107082_2022-08-09_final
2022-08-10 10:07:02	ga_ls8c_ard_3-2-1_098076_2022-08-10_final
2022-08-12 09:57:05	ga_ls8c_ard_3-2-1_096082_2022-08-12_final
2022-08-21 09:50:32	ga_ls8c_ard_3-2-1_095081_2022-08-21_final
2022-08-22 10:33:24	ga_ls8c_ard_3-2-1_102080_2022-08-22_final
2022-08-25 09:24:37	ga_ls8c_ard_3-2-1_091078_2022-08-24_final
2022-08-27 10:51:56	ga_ls8c_ard_3-2-1_105080_2022-08-27_final
2022-08-29 10:38:46	ga_ls8c_ard_3-2-1_103078_2022-08-29_final
2022-08-31 10:23:13	ga_ls8c_ard_3-2-1_101070_2022-08-31_final
2022-09-03 10:57:18	ga_ls8c_ard_3-2-1_106078_2022-09-03_final
2022-09-04 10:03:41	ga_ls8c_ard_3-2-1_097083_2022-09-04_final
2022-09-15 09:44:27	ga_ls8c_ard_3-2-1_094081_2022-09-15_final
2022-09-20 10:01:00	ga_ls8c_ard_3-2-1_097076_2022-09-20_final
2022-09-20 11:40:41	ga_ls8c_ard_3-2-1_113078_2022-09-20_final
2022-09-21 10:44:16	ga_ls8c_ard_3-2-1_104076_2022-09-21_final
2022-09-24 09:38:41	ga_ls8c_ard_3-2-1_093082_2022-09-24_final
2022-09-27 10:09:35	ga_ls8c_ard_3-2-1_098082_2022-09-27_final
2022-09-28 10:50:51	ga_ls8c_ard_3-2-1_105077_2022-09-28_final
2022-09-28 10:52:03	ga_ls8c_ard_3-2-1_105080_2022-09-28_final
2022-09-29 09:56:01	ga_ls8c_ard_3-2-1_096079_2022-09-29_final
2022-09-29 09:56:49	ga_ls8c_ard_3-2-1_096081_2022-09-29_final
2022-09-30 10:38:05	ga_ls8c_ard_3-2-1_103076_2022-09-30_final
2022-10-01 09:42:03	ga_ls8c_ard_3-2-1_094075_2022-10-01_final
2022-10-06 10:03:45	ga_ls8c_ard_3-2-1_097083_2022-10-06_final
2022-10-06 11:40:14	ga_ls8c_ard_3-2-1_113077_2022-10-06_final
2022-10-09 10:32:37	ga_ls8c_ard_3-2-1_102078_2022-10-09_final
2022-10-09 10:33:01	ga_ls8c_ard_3-2-1_102079_2022-10-09_final
2022-10-10 09:38:35	ga_ls8c_ard_3-2-1_093082_2022-10-10_final
2022-10-16 10:37:58	ga_ls8c_ard_3-2-1_103076_2022-10-16_final
2022-10-16 10:38:46	ga_ls8c_ard_3-2-1_103078_2022-10-16_final
2022-10-22 11:39:50	ga_ls8c_ard_3-2-1_113076_2022-10-22_final
2022-10-25 10:32:16	ga_ls8c_ard_3-2-1_102077_2022-10-25_final
2022-10-30 10:51:38	ga_ls8c_ard_3-2-1_105079_2022-10-30_final
2022-10-31 11:33:42	ga_ls8c_ard_3-2-1_112076_2022-10-31_final
2022-11-01 10:38:53	ga_ls8c_ard_3-2-1_103078_2022-11-01_final
2022-11-05 10:12:34	ga_ls8c_ard_3-2-1_099074_2022-11-05_final
2022-11-09 09:50:13	ga_ls8c_ard_3-2-1_095080_2022-11-09_final
2022-11-15 10:51:33	ga_ls8c_ard_3-2-1_105079_2022-11-15_final
2022-11-18 09:42:20	ga_ls8c_ard_3-2-1_094076_2022-11-18_final
2022-11-19 10:27:36	ga_ls8c_ard_3-2-1_101081_2022-11-19_final
2022-11-28 11:58:45	ga_ls8c_ard_3-2-1_116077_2022-11-28_final
2022-11-29 11:04:19	ga_ls8c_ard_3-2-1_107080_2022-11-29_final
2022-12-02 11:34:02	ga_ls8c_ard_3-2-1_112077_2022-12-02_final
2022-12-02 11:34:49	ga_ls8c_ard_3-2-1_112079_2022-12-02_final
2022-12-09 10:01:18	ga_ls8c_ard_3-2-1_097077_2022-12-09_final
2022-12-09 11:40:59	ga_ls8c_ard_3-2-1_113079_2022-12-09_final
2022-12-12 10:33:22	ga_ls8c_ard_3-2-1_102080_2022-12-12_final
2022-12-14 10:21:24	ga_ls8c_ard_3-2-1_100081_2022-12-14_final
2022-12-18 11:35:06	ga_ls8c_ard_3-2-1_112080_2022-12-18_final
2022-12-30 10:20:55	ga_ls8c_ard_3-2-1_100080_2022-12-30_final
2023-01-30 09:37:13	ga_ls8c_ard_3-2-1_093079_2023-01-30_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
2023-02-13 11:27:10	ga_ls8c_ard_3-2-1_111076_2023-02-13_final
2023-02-13 11:28:46	ga_ls8c_ard_3-2-1_111080_2023-02-13_final
2023-02-14 10:33:08	ga_ls8c_ard_3-2-1_102080_2023-02-14_final
2023-02-15 11:15:59	ga_ls8c_ard_3-2-1_109079_2023-02-15_final
2023-02-15 11:16:23	ga_ls8c_ard_3-2-1_109080_2023-02-15_final
2023-02-19 10:51:12	ga_ls8c_ard_3-2-1_105079_2023-02-19_final
2023-02-20 09:53:57	ga_ls8c_ard_3-2-1_096075_2023-02-20_final
2023-02-20 09:55:09	ga_ls8c_ard_3-2-1_096078_2023-02-20_final
2023-02-22 09:43:33	ga_ls8c_ard_3-2-1_094080_2023-02-22_final
2023-02-27 11:40:06	ga_ls8c_ard_3-2-1_113078_2023-02-27_final
2023-03-01 09:50:03	ga_ls8c_ard_3-2-1_095081_2023-03-01_final
2023-03-02 10:32:31	ga_ls8c_ard_3-2-1_102079_2023-03-02_final
2023-03-03 09:36:53	ga_ls8c_ard_3-2-1_093079_2023-03-03_final
2023-03-03 11:14:58	ga_ls8c_ard_3-2-1_109077_2023-03-03_final
2023-03-03 11:15:46	ga_ls8c_ard_3-2-1_109079_2023-03-03_final
2023-03-05 09:24:06	ga_ls8c_ard_3-2-1_091078_2023-03-04_final
2023-03-07 10:51:24	ga_ls8c_ard_3-2-1_105080_2023-03-07_final
2023-03-09 10:37:01	ga_ls8c_ard_3-2-1_103075_2023-03-09_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