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
2013-11-07 09:55:32	ga_ls8c_ard_3-1-0_096075_2013-11-07_final
2016-10-23 11:28:02	ga_ls8c_ard_3-1-0_111078_2016-10-23_final
2016-11-08 11:28:01	ga_ls8c_ard_3-1-0_111078_2016-11-08_final
2019-03-10 09:24:06	ga_ls8c_ard_3-1-0_091079_2019-03-09_final
2019-03-12 10:51:01	ga_ls8c_ard_3-1-0_105080_2019-03-12_final
2019-03-13 09:53:47	ga_ls8c_ard_3-1-0_096076_2019-03-13_final
2019-03-17 11:08:44	ga_ls8c_ard_3-1-0_108078_2019-03-17_final
2019-03-22 09:47:35	ga_ls8c_ard_3-1-0_095076_2019-03-22_final
2019-03-22 09:47:59	ga_ls8c_ard_3-1-0_095077_2019-03-22_final
2019-03-28 10:50:33	ga_ls8c_ard_3-1-0_105079_2019-03-28_final
2019-04-02 11:08:41	ga_ls8c_ard_3-1-0_108078_2019-04-02_final
2019-04-07 09:47:55	ga_ls8c_ard_3-1-0_095077_2019-04-07_final
2019-04-18 11:08:35	ga_ls8c_ard_3-1-0_108078_2019-04-18_final
2019-06-16 10:51:38	ga_ls8c_ard_3-1-0_105081_2019-06-16_final
2019-06-17 09:54:01	ga_ls8c_ard_3-1-0_096076_2019-06-17_final
2019-06-17 09:54:25	ga_ls8c_ard_3-1-0_096077_2019-06-17_final
2019-07-03 09:54:29	ga_ls8c_ard_3-1-0_096077_2019-07-03_final
2019-07-07 11:08:40	ga_ls8c_ard_3-1-0_108077_2019-07-07_final
2019-07-07 11:09:04	ga_ls8c_ard_3-1-0_108078_2019-07-07_final
2019-07-23 11:08:44	ga_ls8c_ard_3-1-0_108077_2019-07-23_final
2019-07-23 11:09:08	ga_ls8c_ard_3-1-0_108078_2019-07-23_final
2019-07-28 09:49:13	ga_ls8c_ard_3-1-0_095079_2019-07-28_final
2019-08-08 11:08:50	ga_ls8c_ard_3-1-0_108077_2019-08-08_final
2019-08-08 11:09:14	ga_ls8c_ard_3-1-0_108078_2019-08-08_final
2019-08-24 11:09:19	ga_ls8c_ard_3-1-0_108078_2019-08-24_final
2019-08-29 09:48:35	ga_ls8c_ard_3-1-0_095077_2019-08-29_final
2019-08-29 09:49:23	ga_ls8c_ard_3-1-0_095079_2019-08-29_final
2019-09-05 09:54:47	ga_ls8c_ard_3-1-0_096077_2019-09-05_final
2019-09-14 09:48:40	ga_ls8c_ard_3-1-0_095077_2019-09-14_final
2019-09-14 09:49:28	ga_ls8c_ard_3-1-0_095079_2019-09-14_final
2019-09-20 10:51:42	ga_ls8c_ard_3-1-0_105080_2019-09-20_final
2019-09-20 10:52:06	ga_ls8c_ard_3-1-0_105081_2019-09-20_final
2019-09-21 09:54:53	ga_ls8c_ard_3-1-0_096077_2019-09-21_final
2019-09-25 11:09:28	ga_ls8c_ard_3-1-0_108078_2019-09-25_final
2019-09-30 09:48:21	ga_ls8c_ard_3-1-0_095076_2019-09-30_final
2019-09-30 09:49:09	ga_ls8c_ard_3-1-0_095078_2019-09-30_final
2019-09-30 09:49:33	ga_ls8c_ard_3-1-0_095079_2019-09-30_final
2019-10-06 10:50:58	ga_ls8c_ard_3-1-0_105078_2019-10-06_final
2019-10-07 09:54:57	ga_ls8c_ard_3-1-0_096077_2019-10-07_final
2019-10-11 11:09:31	ga_ls8c_ard_3-1-0_108078_2019-10-11_final
2019-10-22 10:51:00	ga_ls8c_ard_3-1-0_105078_2019-10-22_final
2019-10-22 10:51:24	ga_ls8c_ard_3-1-0_105079_2019-10-22_final
2019-10-23 09:54:35	ga_ls8c_ard_3-1-0_096076_2019-10-23_final
2019-11-07 10:50:58	ga_ls8c_ard_3-1-0_105078_2019-11-07_final
2019-11-08 09:54:33	ga_ls8c_ard_3-1-0_096076_2019-11-08_final
2019-11-24 09:54:30	ga_ls8c_ard_3-1-0_096076_2019-11-24_final
2019-12-03 09:49:31	ga_ls8c_ard_3-1-0_095079_2019-12-03_final
2020-01-11 09:54:22	ga_ls8c_ard_3-1-0_096076_2020-01-11_final
2020-01-24 09:28:12	ga_ls8c_ard_3-1-0_091088_2020-01-23_final
2020-02-21 09:48:48	ga_ls8c_ard_3-1-0_095078_2020-02-21_final
2020-02-21 09:49:12	ga_ls8c_ard_3-1-0_095079_2020-02-21_final
2020-03-14 10:50:28	ga_ls8c_ard_3-1-0_105078_2020-03-14_final
2020-04-04 11:08:25	ga_ls8c_ard_3-1-0_108077_2020-04-04_final
2020-04-04 11:08:48	ga_ls8c_ard_3-1-0_108078_2020-04-04_final
2020-04-16 09:54:10	ga_ls8c_ard_3-1-0_096077_2020-04-16_final
2020-05-02 09:53:38	ga_ls8c_ard_3-1-0_096076_2020-05-02_final
2020-05-02 09:54:02	ga_ls8c_ard_3-1-0_096077_2020-05-02_final
2020-05-06 11:08:33	ga_ls8c_ard_3-1-0_108078_2020-05-06_final
2022-03-30 09:48:32	ga_ls8c_ard_3-2-1_095078_2022-03-30_final
2022-03-30 09:48:56	ga_ls8c_ard_3-2-1_095079_2022-03-30_final
2022-03-31 10:31:00	ga_ls8c_ard_3-2-1_102076_2022-03-31_final
2022-03-31 10:31:48	ga_ls8c_ard_3-2-1_102078_2022-03-31_final
2022-03-31 10:32:36	ga_ls8c_ard_3-2-1_102080_2022-03-31_final
2022-04-04 10:08:41	ga_ls8c_ard_3-2-1_098082_2022-04-04_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
2022-04-13 10:02:35	ga_ls8c_ard_3-2-1_097082_2022-04-13_final
2022-04-13 11:39:05	ga_ls8c_ard_3-2-1_113076_2022-04-13_final
2022-04-13 11:39:28	ga_ls8c_ard_3-2-1_113077_2022-04-13_final
2022-04-15 09:48:14	ga_ls8c_ard_3-2-1_095077_2022-04-15_final
2022-04-15 09:48:38	ga_ls8c_ard_3-2-1_095078_2022-04-15_final
2022-04-15 11:27:55	ga_ls8c_ard_3-2-1_111079_2022-04-15_final
2022-04-16 10:31:06	ga_ls8c_ard_3-2-1_102076_2022-04-16_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 09:53:59	ga_ls8c_ard_3-2-1_096076_2022-04-22_final
2022-04-22 11:32:52	ga_ls8c_ard_3-2-1_112076_2022-04-22_final
2022-04-22 11:33:40	ga_ls8c_ard_3-2-1_112078_2022-04-22_final
2022-04-26 11:08:55	ga_ls8c_ard_3-2-1_108078_2022-04-26_final
2022-04-29 11:38:36	ga_ls8c_ard_3-2-1_113075_2022-04-29_final
2022-04-30 10:42:36	ga_ls8c_ard_3-2-1_104074_2022-04-30_final
2022-04-30 10:43:47	ga_ls8c_ard_3-2-1_104077_2022-04-30_final
2022-05-01 09:48:35	ga_ls8c_ard_3-2-1_095078_2022-05-01_final
2022-05-01 11:27:28	ga_ls8c_ard_3-2-1_111078_2022-05-01_final
2022-05-01 11:27:52	ga_ls8c_ard_3-2-1_111079_2022-05-01_final
2022-05-02 10:31:51	ga_ls8c_ard_3-2-1_102078_2022-05-02_final
2022-05-02 10:32:15	ga_ls8c_ard_3-2-1_102079_2022-05-02_final
2022-05-08 11:34:08	ga_ls8c_ard_3-2-1_112079_2022-05-08_final
2022-05-09 10:36:55	ga_ls8c_ard_3-2-1_103075_2022-05-09_final
2022-05-11 10:26:11	ga_ls8c_ard_3-2-1_101079_2022-05-11_final
2022-05-12 11:09:03	ga_ls8c_ard_3-2-1_108078_2022-05-12_final
2022-05-13 10:14:38	ga_ls8c_ard_3-2-1_099081_2022-05-13_final
2022-05-15 10:02:41	ga_ls8c_ard_3-2-1_097082_2022-05-15_final
2022-05-15 11:38:46	ga_ls8c_ard_3-2-1_113075_2022-05-15_final
2022-05-15 11:39:58	ga_ls8c_ard_3-2-1_113078_2022-05-15_final
2022-05-17 09:48:20	ga_ls8c_ard_3-2-1_095077_2022-05-17_final
2022-05-17 09:48:44	ga_ls8c_ard_3-2-1_095078_2022-05-17_final
2022-05-26 11:24:13	ga_ls8c_ard_3-2-1_110085_2022-05-26_final
2022-06-02 11:28:05	ga_ls8c_ard_3-2-1_111079_2022-06-02_final
2022-06-04 11:16:09	ga_ls8c_ard_3-2-1_109080_2022-06-04_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