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
2021-09-30 09:32:36	ga_ls8c_ard_3-2-0_092083_2021-09-30_final
2021-10-03 11:39:37	ga_ls8c_ard_3-2-0_113076_2021-10-03_final
2021-10-05 09:48:47	ga_ls8c_ard_3-2-0_095077_2021-10-05_final
2021-10-05 09:49:35	ga_ls8c_ard_3-2-0_095079_2021-10-05_final
2021-10-05 11:28:04	ga_ls8c_ard_3-2-0_111078_2021-10-05_final
2021-10-05 11:28:28	ga_ls8c_ard_3-2-0_111079_2021-10-05_final
2021-10-11 10:51:00	ga_ls8c_ard_3-2-0_105078_2021-10-11_final
2021-10-13 10:39:03	ga_ls8c_ard_3-2-0_103079_2021-10-13_final
2021-10-19 10:03:11	ga_ls8c_ard_3-2-0_097082_2021-10-19_final
2021-10-24 11:58:37	ga_ls8c_ard_3-2-0_116077_2021-10-24_final
2021-10-29 10:39:04	ga_ls8c_ard_3-2-0_103079_2021-10-29_final
2021-11-01 11:08:46	ga_ls8c_ard_3-2-0_108076_2021-11-01_final
2021-11-04 11:40:51	ga_ls8c_ard_3-2-0_113079_2021-11-04_final
2021-11-13 09:51:45	ga_ls8c_ard_3-2-0_096069_2021-11-13_final
2021-11-20 10:00:18	ga_ls8c_ard_3-2-0_097075_2021-11-20_final
2021-11-20 11:40:47	ga_ls8c_ard_3-2-0_113079_2021-11-20_final
2021-11-21 10:41:58	ga_ls8c_ard_3-2-0_104071_2021-11-21_final
2021-11-23 10:34:00	ga_ls8c_ard_3-2-0_102082_2021-11-23_final
2021-11-28 10:50:57	ga_ls8c_ard_3-2-0_105078_2021-11-28_final
2021-12-17 09:42:57	ga_ls8c_ard_3-2-1_094078_2021-12-17_final
2021-12-23 10:45:55	ga_ls8c_ard_3-2-1_104081_2021-12-23_final
2022-01-04 11:08:59	ga_ls8c_ard_3-2-1_108077_2022-01-04_final
2022-01-08 10:45:51	ga_ls8c_ard_3-2-1_104081_2022-01-08_final
2022-02-20 10:22:43	ga_ls8c_ard_3-2-1_101070_2022-02-20_final
2022-02-24 09:59:59	ga_ls8c_ard_3-2-1_097075_2022-02-24_final
2022-02-25 10:42:03	ga_ls8c_ard_3-2-1_104072_2022-02-25_final
2022-03-05 09:54:11	ga_ls8c_ard_3-2-1_096076_2022-03-05_final
2022-03-15 10:32:00	ga_ls8c_ard_3-2-1_102078_2022-03-15_final
2022-03-20 10:50:29	ga_ls8c_ard_3-2-1_105078_2022-03-20_final
2022-03-21 11:32:56	ga_ls8c_ard_3-2-1_112076_2022-03-21_final
2022-03-22 10:38:29	ga_ls8c_ard_3-2-1_103079_2022-03-22_final
2022-03-25 11:08:57	ga_ls8c_ard_3-2-1_108078_2022-03-25_final
2022-03-29 10:41:22	ga_ls8c_ard_3-2-1_104071_2022-03-29_final
2022-04-06 09:54:21	ga_ls8c_ard_3-2-1_096077_2022-04-06_final
2022-04-13 09:59:48	ga_ls8c_ard_3-2-1_097075_2022-04-13_final
2022-04-16 10:31:54	ga_ls8c_ard_3-2-1_102078_2022-04-16_final
2022-04-20 10:08:45	ga_ls8c_ard_3-2-1_098082_2022-04-20_final
2022-04-22 09:54:23	ga_ls8c_ard_3-2-1_096077_2022-04-22_final
2022-04-26 11:08:55	ga_ls8c_ard_3-2-1_108078_2022-04-26_final
2022-05-02 10:31:51	ga_ls8c_ard_3-2-1_102078_2022-05-02_final
2022-05-07 10:50:04	ga_ls8c_ard_3-2-1_105077_2022-05-07_final
2022-05-08 09:56:51	ga_ls8c_ard_3-2-1_096083_2022-05-08_final
2022-05-15 10:02:41	ga_ls8c_ard_3-2-1_097082_2022-05-15_final
2022-06-09 11:33:34	ga_ls8c_ard_3-2-1_112077_2022-06-09_final
2022-06-22 11:03:11	ga_ls8c_ard_3-2-1_107078_2022-06-22_final
2022-06-27 11:22:32	ga_ls8c_ard_3-2-1_110080_2022-06-27_final
2022-06-29 11:09:23	ga_ls8c_ard_3-2-1_108078_2022-06-29_final
2022-07-02 11:40:17	ga_ls8c_ard_3-2-1_113078_2022-07-02_final
2022-07-08 11:03:12	ga_ls8c_ard_3-2-1_107078_2022-07-08_final
2022-07-18 11:40:18	ga_ls8c_ard_3-2-1_113078_2022-07-18_final
2022-07-20 09:48:41	ga_ls8c_ard_3-2-1_095077_2022-07-20_final
2022-07-20 11:28:22	ga_ls8c_ard_3-2-1_111079_2022-07-20_final
2022-07-28 10:39:25	ga_ls8c_ard_3-2-1_103080_2022-07-28_final
2022-07-31 11:09:33	ga_ls8c_ard_3-2-1_108078_2022-07-31_final
2022-08-01 10:15:08	ga_ls8c_ard_3-2-1_099081_2022-08-01_final
2022-08-05 09:48:51	ga_ls8c_ard_3-2-1_095077_2022-08-05_final
2022-08-08 11:58:40	ga_ls8c_ard_3-2-1_116077_2022-08-08_final
2022-08-14 09:41:56	ga_ls8c_ard_3-2-1_094075_2022-08-14_final
2022-08-16 11:09:16	ga_ls8c_ard_3-2-1_108077_2022-08-16_final
2022-08-19 10:00:30	ga_ls8c_ard_3-2-1_097075_2022-08-19_final
2022-08-19 10:03:17	ga_ls8c_ard_3-2-1_097082_2022-08-19_final
2022-08-28 09:55:07	ga_ls8c_ard_3-2-1_096077_2022-08-28_final
2022-09-04 10:00:30	ga_ls8c_ard_3-2-1_097075_2022-09-04_final
2022-09-04 11:40:35	ga_ls8c_ard_3-2-1_113078_2022-09-04_final
2022-09-06 09:48:57	ga_ls8c_ard_3-2-1_095077_2022-09-06_final
2022-09-07 10:33:02	ga_ls8c_ard_3-2-1_102079_2022-09-07_final
2022-09-17 11:09:47	ga_ls8c_ard_3-2-1_108078_2022-09-17_final
2022-09-20 10:00:36	ga_ls8c_ard_3-2-1_097075_2022-09-20_final
2022-09-20 10:03:24	ga_ls8c_ard_3-2-1_097082_2022-09-20_final
2022-09-21 10:45:28	ga_ls8c_ard_3-2-1_104079_2022-09-21_final
2022-09-22 11:28:44	ga_ls8c_ard_3-2-1_111079_2022-09-22_final
2022-09-28 10:51:15	ga_ls8c_ard_3-2-1_105078_2022-09-28_final
2022-10-06 10:00:34	ga_ls8c_ard_3-2-1_097075_2022-10-06_final
2022-10-06 10:03:21	ga_ls8c_ard_3-2-1_097082_2022-10-06_final
2022-10-06 11:39:51	ga_ls8c_ard_3-2-1_113076_2022-10-06_final
2022-10-14 10:51:06	ga_ls8c_ard_3-2-1_105078_2022-10-14_final
2022-10-22 10:00:33	ga_ls8c_ard_3-2-1_097075_2022-10-22_final
2022-11-19 10:23:12	ga_ls8c_ard_3-2-1_101070_2022-11-19_final
2022-11-23 11:40:59	ga_ls8c_ard_3-2-1_113079_2022-11-23_final
2022-12-06 11:09:42	ga_ls8c_ard_3-2-1_108078_2022-12-06_final
2022-12-09 11:40:59	ga_ls8c_ard_3-2-1_113079_2022-12-09_final
2022-12-10 10:46:09	ga_ls8c_ard_3-2-1_104081_2022-12-10_final
2022-12-22 11:09:31	ga_ls8c_ard_3-2-1_108078_2022-12-22_final
2023-02-15 09:38:18	ga_ls8c_ard_3-2-1_093082_2023-02-15_final
2023-02-21 10:39:59	ga_ls8c_ard_3-2-1_103082_2023-02-21_final
2023-02-27 10:02:49	ga_ls8c_ard_3-2-1_097082_2023-02-27_final
2023-03-09 10:38:37	ga_ls8c_ard_3-2-1_103079_2023-03-09_final
2023-03-10 09:44:35	ga_ls8c_ard_3-2-1_094083_2023-03-10_final
2023-03-15 11:39:12	ga_ls8c_ard_3-2-1_113076_2023-03-15_final
2023-03-18 10:31:59	ga_ls8c_ard_3-2-1_102078_2023-03-18_final
2023-03-24 11:33:42	ga_ls8c_ard_3-2-1_112078_2023-03-24_final
2023-04-02 09:47:46	ga_ls8c_ard_3-2-1_095076_2023-04-02_final
2023-04-09 09:54:11	ga_ls8c_ard_3-2-1_096077_2023-04-09_final
2023-04-11 09:42:11	ga_ls8c_ard_3-2-1_094078_2023-04-11_final
2023-04-20 09:35:33	ga_ls8c_ard_3-2-1_093077_2023-04-20_final
2023-04-25 09:53:18	ga_ls8c_ard_3-2-1_096075_2023-04-25_final
2023-04-25 11:33:47	ga_ls8c_ard_3-2-1_112079_2023-04-25_final
2023-05-14 10:25:34	ga_ls8c_ard_3-2-1_101079_2023-05-14_final
2023-05-16 10:13:59	ga_ls8c_ard_3-2-1_099081_2023-05-16_final
2023-05-18 11:39:18	ga_ls8c_ard_3-2-1_113078_2023-05-18_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