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
2021-09-23 11:04:51	ga_ls8c_ard_3-2-0_107082_2021-09-23_final
2021-09-24 10:09:14	ga_ls8c_ard_3-2-0_098082_2021-09-24_final
2021-09-26 09:54:06	ga_ls8c_ard_3-2-0_096075_2021-09-26_final
2021-09-26 09:55:18	ga_ls8c_ard_3-2-0_096078_2021-09-26_final
2021-09-27 10:37:22	ga_ls8c_ard_3-2-0_103075_2021-09-27_final
2021-09-27 10:40:10	ga_ls8c_ard_3-2-0_103082_2021-09-27_final
2021-10-04 10:46:00	ga_ls8c_ard_3-2-0_104081_2021-10-04_final
2021-10-11 10:51:24	ga_ls8c_ard_3-2-0_105079_2021-10-11_final
2021-10-14 09:42:14	ga_ls8c_ard_3-2-0_094076_2021-10-14_final
2021-10-14 11:22:19	ga_ls8c_ard_3-2-0_110079_2021-10-14_final
2021-10-18 09:18:19	ga_ls8c_ard_3-2-0_090078_2021-10-17_final
2021-10-21 09:49:38	ga_ls8c_ard_3-2-0_095079_2021-10-21_final
2021-10-24 11:58:37	ga_ls8c_ard_3-2-0_116077_2021-10-24_final
2021-10-25 11:04:59	ga_ls8c_ard_3-2-0_107082_2021-10-25_final
2021-10-28 11:33:54	ga_ls8c_ard_3-2-0_112077_2021-10-28_final
2021-10-29 10:39:04	ga_ls8c_ard_3-2-0_103079_2021-10-29_final
2021-11-04 10:03:34	ga_ls8c_ard_3-2-0_097083_2021-11-04_final
2021-11-06 09:49:36	ga_ls8c_ard_3-2-0_095079_2021-11-06_final
2021-11-13 11:35:01	ga_ls8c_ard_3-2-0_112080_2021-11-13_final
2021-11-20 10:00:18	ga_ls8c_ard_3-2-0_097075_2021-11-20_final
2021-11-22 11:28:25	ga_ls8c_ard_3-2-0_111079_2021-11-22_final
2021-11-23 10:32:00	ga_ls8c_ard_3-2-0_102077_2021-11-23_final
2021-11-25 11:58:32	ga_ls8c_ard_3-2-0_116077_2021-11-25_final
2021-11-28 10:50:57	ga_ls8c_ard_3-2-0_105078_2021-11-28_final
2021-12-02 10:27:02	ga_ls8c_ard_3-2-0_101080_2021-12-02_final
2021-12-10 09:38:23	ga_ls8c_ard_3-2-1_093082_2021-12-10_final
2021-12-15 11:35:00	ga_ls8c_ard_3-2-1_112080_2021-12-15_final
2021-12-16 10:37:23	ga_ls8c_ard_3-2-1_103075_2021-12-16_final
2021-12-19 11:09:28	ga_ls8c_ard_3-2-1_108078_2021-12-19_final
2021-12-28 11:05:13	ga_ls8c_ard_3-2-1_107083_2021-12-28_final
2021-12-31 09:54:02	ga_ls8c_ard_3-2-1_096075_2021-12-31_final
2021-12-31 09:54:25	ga_ls8c_ard_3-2-1_096076_2021-12-31_final
2022-01-02 11:21:45	ga_ls8c_ard_3-2-1_110078_2022-01-02_final
2022-01-16 09:54:48	ga_ls8c_ard_3-2-1_096077_2022-01-16_final
2022-01-16 09:55:12	ga_ls8c_ard_3-2-1_096078_2022-01-16_final
2022-01-18 09:42:49	ga_ls8c_ard_3-2-1_094078_2022-01-18_final
2022-01-22 10:58:09	ga_ls8c_ard_3-2-1_106081_2022-01-22_final
2022-02-03 09:42:45	ga_ls8c_ard_3-2-1_094078_2022-02-03_final
2022-02-17 09:54:14	ga_ls8c_ard_3-2-1_096076_2022-02-17_final
2022-02-17 11:33:31	ga_ls8c_ard_3-2-1_112077_2022-02-17_final
2022-02-17 11:34:19	ga_ls8c_ard_3-2-1_112079_2022-02-17_final
2022-02-17 11:34:43	ga_ls8c_ard_3-2-1_112080_2022-02-17_final
2022-02-18 10:37:05	ga_ls8c_ard_3-2-1_103075_2022-02-18_final
2022-02-19 09:43:03	ga_ls8c_ard_3-2-1_094079_2022-02-19_final
2022-02-24 09:59:59	ga_ls8c_ard_3-2-1_097075_2022-02-24_final
2022-02-28 11:14:57	ga_ls8c_ard_3-2-1_109077_2022-02-28_final
2022-03-05 09:54:11	ga_ls8c_ard_3-2-1_096076_2022-03-05_final
2022-03-05 09:54:59	ga_ls8c_ard_3-2-1_096078_2022-03-05_final
2022-03-05 11:33:04	ga_ls8c_ard_3-2-1_112076_2022-03-05_final
2022-03-05 11:34:16	ga_ls8c_ard_3-2-1_112079_2022-03-05_final
2022-03-09 11:09:55	ga_ls8c_ard_3-2-1_108080_2022-03-09_final
2022-03-13 10:45:34	ga_ls8c_ard_3-2-1_104081_2022-03-13_final
2022-03-14 09:48:21	ga_ls8c_ard_3-2-1_095077_2022-03-14_final
2022-03-14 09:49:32	ga_ls8c_ard_3-2-1_095080_2022-03-14_final
2022-03-20 10:50:05	ga_ls8c_ard_3-2-1_105077_2022-03-20_final
2022-03-21 09:54:51	ga_ls8c_ard_3-2-1_096078_2022-03-21_final
2022-03-23 09:42:03	ga_ls8c_ard_3-2-1_094077_2022-03-23_final
2022-03-26 10:14:31	ga_ls8c_ard_3-2-1_099081_2022-03-26_final
2022-03-30 09:49:20	ga_ls8c_ard_3-2-1_095080_2022-03-30_final
2022-04-06 09:53:33	ga_ls8c_ard_3-2-1_096075_2022-04-06_final
2022-04-07 10:36:26	ga_ls8c_ard_3-2-1_103074_2022-04-07_final
2022-04-07 10:38:25	ga_ls8c_ard_3-2-1_103079_2022-04-07_final
2022-04-09 10:26:05	ga_ls8c_ard_3-2-1_101079_2022-04-09_final
2022-04-10 11:08:09	ga_ls8c_ard_3-2-1_108076_2022-04-10_final
2022-04-14 10:43:51	ga_ls8c_ard_3-2-1_104077_2022-04-14_final
2022-04-15 11:28:19	ga_ls8c_ard_3-2-1_111080_2022-04-15_final
2022-04-16 10:31:06	ga_ls8c_ard_3-2-1_102076_2022-04-16_final
2022-04-17 09:37:28	ga_ls8c_ard_3-2-1_093081_2022-04-17_final
2022-04-22 11:34:28	ga_ls8c_ard_3-2-1_112080_2022-04-22_final
2022-04-23 10:38:03	ga_ls8c_ard_3-2-1_103078_2022-04-23_final
2022-05-01 11:28:16	ga_ls8c_ard_3-2-1_111080_2022-05-01_final
2023-03-14 10:58:21	ga_ls8c_ard_3-2-1_106082_2023-03-14_final
2023-03-18 10:32:47	ga_ls8c_ard_3-2-1_102080_2023-03-18_final
2023-03-20 10:17:36	ga_ls8c_ard_3-2-1_100073_2023-03-20_final
2023-03-24 09:54:01	ga_ls8c_ard_3-2-1_096076_2023-03-24_final
2023-03-24 09:54:25	ga_ls8c_ard_3-2-1_096077_2023-03-24_final
2023-03-24 11:32:30	ga_ls8c_ard_3-2-1_112075_2023-03-24_final
2023-03-26 09:43:15	ga_ls8c_ard_3-2-1_094080_2023-03-26_final
2023-03-31 09:59:45	ga_ls8c_ard_3-2-1_097075_2023-03-31_final
2023-04-02 09:47:46	ga_ls8c_ard_3-2-1_095076_2023-04-02_final
2023-04-03 10:30:36	ga_ls8c_ard_3-2-1_102075_2023-04-03_final
2023-04-04 09:36:34	ga_ls8c_ard_3-2-1_093079_2023-04-04_final
2023-04-09 09:53:23	ga_ls8c_ard_3-2-1_096075_2023-04-09_final
2023-04-09 11:33:28	ga_ls8c_ard_3-2-1_112078_2023-04-09_final
2023-04-10 10:37:01	ga_ls8c_ard_3-2-1_103076_2023-04-10_final
2023-04-11 09:44:10	ga_ls8c_ard_3-2-1_094083_2023-04-11_final
2023-04-18 09:49:31	ga_ls8c_ard_3-2-1_095081_2023-04-18_final
2023-04-20 11:15:14	ga_ls8c_ard_3-2-1_109079_2023-04-20_final
2023-04-29 11:07:50	ga_ls8c_ard_3-2-1_108076_2023-04-29_final
2023-05-02 10:02:13	ga_ls8c_ard_3-2-1_097082_2023-05-02_final
2023-05-02 11:38:42	ga_ls8c_ard_3-2-1_113076_2023-05-02_final
2023-05-03 10:44:16	ga_ls8c_ard_3-2-1_104079_2023-05-03_final
2023-05-05 10:31:53	ga_ls8c_ard_3-2-1_102079_2023-05-05_final
2023-05-11 09:54:41	ga_ls8c_ard_3-2-1_096079_2023-05-11_final
2023-05-11 11:31:59	ga_ls8c_ard_3-2-1_112075_2023-05-11_final
2023-05-13 09:41:07	ga_ls8c_ard_3-2-1_094076_2023-05-13_final
2023-05-13 09:42:18	ga_ls8c_ard_3-2-1_094079_2023-05-13_final
2023-05-13 09:43:54	ga_ls8c_ard_3-2-1_094083_2023-05-13_final
2023-05-15 09:31:32	ga_ls8c_ard_3-2-1_092083_2023-05-15_final
2023-05-20 09:48:28	ga_ls8c_ard_3-2-1_095079_2023-05-20_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