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
2020-01-24 12:37:35	ga_ls8c_ard_3-2-1_123067_2020-01-24_final
2020-03-24 08:10:29	ga_ls8c_ard_3-2-1_079080_2020-03-23_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
2022-05-12 11:09:03	ga_ls8c_ard_3-2-1_108078_2022-05-12_final
2022-05-17 09:48:20	ga_ls8c_ard_3-2-1_095077_2022-05-17_final
2022-05-26 11:24:13	ga_ls8c_ard_3-2-1_110085_2022-05-26_final
2022-06-18 11:27:29	ga_ls8c_ard_3-2-1_111077_2022-06-18_final
2022-06-25 11:33:18	ga_ls8c_ard_3-2-1_112076_2022-06-25_final
2022-06-25 11:34:06	ga_ls8c_ard_3-2-1_112078_2022-06-25_final
2022-07-02 11:39:29	ga_ls8c_ard_3-2-1_113076_2022-07-02_final
2022-07-05 10:32:42	ga_ls8c_ard_3-2-1_102079_2022-07-05_final
2022-07-15 11:09:21	ga_ls8c_ard_3-2-1_108078_2022-07-15_final
2022-07-18 11:39:30	ga_ls8c_ard_3-2-1_113076_2022-07-18_final
2022-07-27 11:33:26	ga_ls8c_ard_3-2-1_112076_2022-07-27_final
2022-07-27 11:33:50	ga_ls8c_ard_3-2-1_112077_2022-07-27_final
2022-07-27 11:34:14	ga_ls8c_ard_3-2-1_112078_2022-07-27_final
2022-08-03 10:03:12	ga_ls8c_ard_3-2-1_097082_2022-08-03_final
2022-08-06 10:32:56	ga_ls8c_ard_3-2-1_102079_2022-08-06_final
2022-08-16 11:09:40	ga_ls8c_ard_3-2-1_108078_2022-08-16_final
2022-08-19 11:39:47	ga_ls8c_ard_3-2-1_113076_2022-08-19_final
2022-08-21 09:48:56	ga_ls8c_ard_3-2-1_095077_2022-08-21_final
2022-08-21 11:28:37	ga_ls8c_ard_3-2-1_111079_2022-08-21_final
2022-08-22 10:31:48	ga_ls8c_ard_3-2-1_102076_2022-08-22_final
2022-08-22 10:33:00	ga_ls8c_ard_3-2-1_102079_2022-08-22_final
2022-09-01 11:09:16	ga_ls8c_ard_3-2-1_108077_2022-09-01_final
2022-09-23 10:33:30	ga_ls8c_ard_3-2-1_102080_2022-09-23_final
2022-10-07 10:46:12	ga_ls8c_ard_3-2-1_104081_2022-10-07_final
2022-10-13 10:08:38	ga_ls8c_ard_3-2-1_098080_2022-10-13_final
2022-10-30 10:52:50	ga_ls8c_ard_3-2-1_105082_2022-10-30_final
2022-11-04 09:35:17	ga_ls8c_ard_3-2-1_092089_2022-11-04_final
2022-12-17 10:49:04	ga_ls8c_ard_3-2-1_105073_2022-12-17_final
2022-12-21 10:27:05	ga_ls8c_ard_3-2-1_101080_2022-12-21_final
2023-01-09 10:58:46	ga_ls8c_ard_3-2-1_106082_2023-01-09_final
2023-02-07 10:27:02	ga_ls8c_ard_3-2-1_101080_2023-02-07_final
2023-02-11 11:40:46	ga_ls8c_ard_3-2-1_113079_2023-02-11_final
2023-02-19 10:50:48	ga_ls8c_ard_3-2-1_105078_2023-02-19_final
2023-02-27 11:39:42	ga_ls8c_ard_3-2-1_113077_2023-02-27_final
2023-03-07 10:50:36	ga_ls8c_ard_3-2-1_105078_2023-03-07_final
2023-03-15 10:02:43	ga_ls8c_ard_3-2-1_097082_2023-03-15_final
2023-03-16 10:44:46	ga_ls8c_ard_3-2-1_104079_2023-03-16_final
2023-04-06 11:04:14	ga_ls8c_ard_3-2-1_107082_2023-04-06_final
2023-04-18 11:27:36	ga_ls8c_ard_3-2-1_111079_2023-04-18_final
2023-04-19 10:30:46	ga_ls8c_ard_3-2-1_102076_2023-04-19_final
2023-04-19 10:33:10	ga_ls8c_ard_3-2-1_102082_2023-04-19_final
2023-04-29 11:08:38	ga_ls8c_ard_3-2-1_108078_2023-04-29_final
2023-05-02 10:02:13	ga_ls8c_ard_3-2-1_097082_2023-05-02_final
2023-05-04 11:27:31	ga_ls8c_ard_3-2-1_111079_2023-05-04_final
2023-05-05 10:31:53	ga_ls8c_ard_3-2-1_102079_2023-05-05_final
2023-05-11 09:53:54	ga_ls8c_ard_3-2-1_096077_2023-05-11_final
2023-05-11 11:33:11	ga_ls8c_ard_3-2-1_112078_2023-05-11_final
2023-05-20 11:27:21	ga_ls8c_ard_3-2-1_111079_2023-05-20_final
2023-05-27 09:53:53	ga_ls8c_ard_3-2-1_096077_2023-05-27_final
2023-06-03 10:02:05	ga_ls8c_ard_3-2-1_097082_2023-06-03_final
2023-06-05 11:27:26	ga_ls8c_ard_3-2-1_111079_2023-06-05_final
2023-06-06 10:31:50	ga_ls8c_ard_3-2-1_102079_2023-06-06_final
2023-06-12 09:53:37	ga_ls8c_ard_3-2-1_096076_2023-06-12_final
2023-06-12 11:33:18	ga_ls8c_ard_3-2-1_112078_2023-06-12_final
2023-06-28 09:53:45	ga_ls8c_ard_3-2-1_096076_2023-06-28_final
2023-06-28 11:33:26	ga_ls8c_ard_3-2-1_112078_2023-06-28_final
2023-07-07 09:48:28	ga_ls8c_ard_3-2-1_095078_2023-07-07_final
2023-07-07 11:27:45	ga_ls8c_ard_3-2-1_111079_2023-07-07_final
2023-07-23 09:48:08	ga_ls8c_ard_3-2-1_095077_2023-07-23_final
2023-07-23 09:49:20	ga_ls8c_ard_3-2-1_095080_2023-07-23_final
2023-07-23 11:27:49	ga_ls8c_ard_3-2-1_111079_2023-07-23_final
2023-07-30 09:54:24	ga_ls8c_ard_3-2-1_096077_2023-07-30_final
2023-08-03 11:09:00	ga_ls8c_ard_3-2-1_108078_2023-08-03_final
2023-08-06 10:02:37	ga_ls8c_ard_3-2-1_097082_2023-08-06_final
2023-08-15 11:33:47	ga_ls8c_ard_3-2-1_112078_2023-08-15_final
2023-08-24 09:49:11	ga_ls8c_ard_3-2-1_095079_2023-08-24_final
2023-08-24 11:28:04	ga_ls8c_ard_3-2-1_111079_2023-08-24_final
2023-08-25 10:32:27	ga_ls8c_ard_3-2-1_102079_2023-08-25_final
2023-08-29 10:08:32	ga_ls8c_ard_3-2-1_098081_2023-08-29_final
2023-08-29 10:08:56	ga_ls8c_ard_3-2-1_098082_2023-08-29_final
2023-08-31 09:54:11	ga_ls8c_ard_3-2-1_096076_2023-08-31_final
2023-08-31 11:33:52	ga_ls8c_ard_3-2-1_112078_2023-08-31_final
2023-09-03 10:22:40	ga_ls8c_ard_3-2-1_101070_2023-09-03_final
2023-09-07 10:00:43	ga_ls8c_ard_3-2-1_097077_2023-09-07_final
2023-09-09 09:48:23	ga_ls8c_ard_3-2-1_095077_2023-09-09_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
2023-09-20 11:09:13	ga_ls8c_ard_3-2-1_108078_2023-09-20_final
2023-09-23 10:02:49	ga_ls8c_ard_3-2-1_097082_2023-09-23_final
2023-09-23 11:39:19	ga_ls8c_ard_3-2-1_113076_2023-09-23_final
2023-09-23 11:40:31	ga_ls8c_ard_3-2-1_113079_2023-09-23_final
2023-10-02 09:54:18	ga_ls8c_ard_3-2-1_096076_2023-10-02_final
2023-10-05 10:26:47	ga_ls8c_ard_3-2-1_101080_2023-10-05_final
2023-10-06 11:09:15	ga_ls8c_ard_3-2-1_108078_2023-10-06_final
2023-10-21 10:26:50	ga_ls8c_ard_3-2-1_101080_2023-10-21_final
2023-11-06 10:26:52	ga_ls8c_ard_3-2-1_101080_2023-11-06_final
2023-11-12 08:10:52	ga_ls8c_ard_3-2-1_079080_2023-11-11_final
2023-12-07 09:45:06	ga_ls8c_ard_3-2-1_094084_2023-12-07_final
2023-12-10 10:16:02	ga_ls8c_ard_3-2-1_099084_2023-12-10_final
2024-01-10 11:09:15	ga_ls8c_ard_3-2-1_108078_2024-01-10_final
2024-01-16 10:30:59	ga_ls8c_ard_3-2-1_102075_2024-01-16_final
2024-02-10 10:26:47	ga_ls8c_ard_3-2-1_101080_2024-02-10_final
2024-02-11 11:09:14	ga_ls8c_ard_3-2-1_108078_2024-02-11_final
2024-02-26 10:26:42	ga_ls8c_ard_3-2-1_101080_2024-02-26_final
2024-03-17 11:39:03	ga_ls8c_ard_3-2-1_113076_2024-03-17_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