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
2018-12-13 12:31:09	ga_ls8c_ard_3-2-1_122067_2018-12-13_final
2019-10-13 12:31:40	ga_ls8c_ard_3-2-1_122067_2019-10-13_final
2020-08-12 12:31:15	ga_ls8c_ard_3-2-1_122067_2020-08-12_final
2020-09-16 08:10:58	ga_ls8c_ard_3-2-1_079080_2020-09-15_final
2021-01-25 08:42:33	ga_ls8c_ard_3-2-1_084082_2021-01-24_final
2021-05-01 08:41:57	ga_ls8c_ard_3-2-1_084082_2021-04-30_final
2021-10-05 09:49:11	ga_ls8c_ard_3-2-0_095078_2021-10-05_final
2021-10-21 09:49:14	ga_ls8c_ard_3-2-0_095078_2021-10-21_final
2022-01-09 09:49:02	ga_ls8c_ard_3-2-1_095078_2022-01-09_final
2022-01-20 11:09:20	ga_ls8c_ard_3-2-1_108078_2022-01-20_final
2022-03-30 09:48:08	ga_ls8c_ard_3-2-1_095077_2022-03-30_final
2022-04-06 09:53:57	ga_ls8c_ard_3-2-1_096076_2022-04-06_final
2022-04-06 11:33:14	ga_ls8c_ard_3-2-1_112077_2022-04-06_final
2022-04-08 11:21:18	ga_ls8c_ard_3-2-1_110078_2022-04-08_final
2022-04-15 11:27:55	ga_ls8c_ard_3-2-1_111079_2022-04-15_final
2022-04-22 11:33:16	ga_ls8c_ard_3-2-1_112077_2022-04-22_final
2022-04-24 11:21:18	ga_ls8c_ard_3-2-1_110078_2022-04-24_final
2022-05-01 11:27:52	ga_ls8c_ard_3-2-1_111079_2022-05-01_final
2022-05-08 11:34:08	ga_ls8c_ard_3-2-1_112079_2022-05-08_final
2022-05-12 11:08:39	ga_ls8c_ard_3-2-1_108077_2022-05-12_final
2022-05-17 09:48:20	ga_ls8c_ard_3-2-1_095077_2022-05-17_final
2022-05-26 09:42:57	ga_ls8c_ard_3-2-1_094079_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
2022-06-22 11:03:11	ga_ls8c_ard_3-2-1_107078_2022-06-22_final
2022-07-04 09:48:39	ga_ls8c_ard_3-2-1_095077_2022-07-04_final
2022-07-08 11:03:12	ga_ls8c_ard_3-2-1_107078_2022-07-08_final
2022-07-13 11:21:44	ga_ls8c_ard_3-2-1_110078_2022-07-13_final
2022-07-13 11:22:08	ga_ls8c_ard_3-2-1_110079_2022-07-13_final
2022-07-27 11:34:38	ga_ls8c_ard_3-2-1_112079_2022-07-27_final
2022-08-02 12:31:43	ga_ls8c_ard_3-2-1_122067_2022-08-02_final
2022-08-12 11:33:34	ga_ls8c_ard_3-2-1_112076_2022-08-12_final
2022-08-12 11:33:58	ga_ls8c_ard_3-2-1_112077_2022-08-12_final
2022-08-12 11:34:46	ga_ls8c_ard_3-2-1_112079_2022-08-12_final
2022-08-14 09:43:08	ga_ls8c_ard_3-2-1_094078_2022-08-14_final
2022-08-28 11:33:36	ga_ls8c_ard_3-2-1_112076_2022-08-28_final
2022-09-06 09:48:57	ga_ls8c_ard_3-2-1_095077_2022-09-06_final
2022-09-06 09:49:21	ga_ls8c_ard_3-2-1_095078_2022-09-06_final
2022-09-22 09:49:27	ga_ls8c_ard_3-2-1_095078_2022-09-22_final
2022-09-22 11:28:20	ga_ls8c_ard_3-2-1_111078_2022-09-22_final
2022-09-22 11:28:44	ga_ls8c_ard_3-2-1_111079_2022-09-22_final
2022-10-08 08:11:17	ga_ls8c_ard_3-2-1_079080_2022-10-07_final
2022-10-16 10:40:21	ga_ls8c_ard_3-2-1_103082_2022-10-16_final
2022-10-19 11:09:42	ga_ls8c_ard_3-2-1_108078_2022-10-19_final
2022-11-25 09:49:21	ga_ls8c_ard_3-2-1_095078_2022-11-25_final
2022-12-11 09:49:19	ga_ls8c_ard_3-2-1_095078_2022-12-11_final
2023-02-13 09:49:05	ga_ls8c_ard_3-2-1_095078_2023-02-13_final
2023-02-19 10:50:48	ga_ls8c_ard_3-2-1_105078_2023-02-19_final
2023-02-24 11:09:13	ga_ls8c_ard_3-2-1_108078_2023-02-24_final
2023-03-08 11:33:27	ga_ls8c_ard_3-2-1_112077_2023-03-08_final
2023-03-17 11:27:37	ga_ls8c_ard_3-2-1_111078_2023-03-17_final
2023-03-31 10:01:45	ga_ls8c_ard_3-2-1_097080_2023-03-31_final
2023-04-09 11:33:04	ga_ls8c_ard_3-2-1_112077_2023-04-09_final
2023-04-11 09:42:11	ga_ls8c_ard_3-2-1_094078_2023-04-11_final
2023-04-18 09:47:55	ga_ls8c_ard_3-2-1_095077_2023-04-18_final
2023-04-25 11:32:35	ga_ls8c_ard_3-2-1_112076_2023-04-25_final
2023-05-11 09:53:30	ga_ls8c_ard_3-2-1_096076_2023-05-11_final
2023-05-11 09:53:54	ga_ls8c_ard_3-2-1_096077_2023-05-11_final
2023-05-11 11:32:47	ga_ls8c_ard_3-2-1_112077_2023-05-11_final
2023-05-11 11:33:11	ga_ls8c_ard_3-2-1_112078_2023-05-11_final
2023-05-14 10:25:34	ga_ls8c_ard_3-2-1_101079_2023-05-14_final
2023-05-27 09:53:29	ga_ls8c_ard_3-2-1_096076_2023-05-27_final
2023-05-27 09:53:53	ga_ls8c_ard_3-2-1_096077_2023-05-27_final
2023-05-27 11:32:22	ga_ls8c_ard_3-2-1_112076_2023-05-27_final
2023-05-27 11:32:46	ga_ls8c_ard_3-2-1_112077_2023-05-27_final
2023-05-29 09:42:20	ga_ls8c_ard_3-2-1_094079_2023-05-29_final
2023-06-05 09:47:45	ga_ls8c_ard_3-2-1_095077_2023-06-05_final
2023-06-12 11:32:30	ga_ls8c_ard_3-2-1_112076_2023-06-12_final
2023-06-12 11:32:54	ga_ls8c_ard_3-2-1_112077_2023-06-12_final
2023-06-12 11:33:18	ga_ls8c_ard_3-2-1_112078_2023-06-12_final
2023-06-14 11:21:21	ga_ls8c_ard_3-2-1_110079_2023-06-14_final
2023-06-21 09:47:52	ga_ls8c_ard_3-2-1_095077_2023-06-21_final
2023-06-28 09:53:45	ga_ls8c_ard_3-2-1_096076_2023-06-28_final
2023-06-30 11:21:30	ga_ls8c_ard_3-2-1_110079_2023-06-30_final
2023-07-07 11:27:45	ga_ls8c_ard_3-2-1_111079_2023-07-07_final
2023-07-14 11:32:46	ga_ls8c_ard_3-2-1_112076_2023-07-14_final
2023-07-14 11:33:10	ga_ls8c_ard_3-2-1_112077_2023-07-14_final
2023-07-25 11:15:29	ga_ls8c_ard_3-2-1_109079_2023-07-25_final
2023-07-30 09:54:24	ga_ls8c_ard_3-2-1_096077_2023-07-30_final
2023-07-30 11:33:41	ga_ls8c_ard_3-2-1_112078_2023-07-30_final
2023-08-01 09:42:51	ga_ls8c_ard_3-2-1_094079_2023-08-01_final
2023-08-15 09:54:06	ga_ls8c_ard_3-2-1_096076_2023-08-15_final
2023-08-15 11:32:59	ga_ls8c_ard_3-2-1_112076_2023-08-15_final
2023-08-15 11:33:23	ga_ls8c_ard_3-2-1_112077_2023-08-15_final
2023-08-24 09:49:11	ga_ls8c_ard_3-2-1_095079_2023-08-24_final
2023-08-31 09:54:11	ga_ls8c_ard_3-2-1_096076_2023-08-31_final
2023-08-31 11:33:04	ga_ls8c_ard_3-2-1_112076_2023-08-31_final
2023-08-31 11:33:28	ga_ls8c_ard_3-2-1_112077_2023-08-31_final
2023-09-02 09:42:36	ga_ls8c_ard_3-2-1_094078_2023-09-02_final
2023-09-02 11:21:29	ga_ls8c_ard_3-2-1_110078_2023-09-02_final
2023-09-09 09:49:11	ga_ls8c_ard_3-2-1_095079_2023-09-09_final
2023-09-16 11:33:08	ga_ls8c_ard_3-2-1_112076_2023-09-16_final
2023-09-16 11:33:55	ga_ls8c_ard_3-2-1_112078_2023-09-16_final
2023-09-18 09:42:41	ga_ls8c_ard_3-2-1_094078_2023-09-18_final
2023-09-25 09:48:29	ga_ls8c_ard_3-2-1_095077_2023-09-25_final
2023-10-02 09:54:18	ga_ls8c_ard_3-2-1_096076_2023-10-02_final
2023-10-11 09:48:34	ga_ls8c_ard_3-2-1_095077_2023-10-11_final
2023-11-07 11:08:55	ga_ls8c_ard_3-2-1_108077_2023-11-07_final
2023-11-28 09:49:02	ga_ls8c_ard_3-2-1_095078_2023-11-28_final
2024-01-26 11:08:45	ga_ls8c_ard_3-2-1_108077_2024-01-26_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