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
2022-08-21 11:28:13	ga_ls8c_ard_3-2-1_111078_2022-08-21_final
2022-08-22 10:32:36	ga_ls8c_ard_3-2-1_102078_2022-08-22_final
2022-08-30 11:22:02	ga_ls8c_ard_3-2-1_110078_2022-08-30_final
2022-09-13 11:34:05	ga_ls8c_ard_3-2-1_112077_2022-09-13_final
2022-09-15 09:44:27	ga_ls8c_ard_3-2-1_094081_2022-09-15_final
2022-09-15 11:22:08	ga_ls8c_ard_3-2-1_110078_2022-09-15_final
2022-09-27 10:09:11	ga_ls8c_ard_3-2-1_098081_2022-09-27_final
2022-09-29 09:54:49	ga_ls8c_ard_3-2-1_096076_2022-09-29_final
2022-10-14 09:13:48	ga_ls8c_ard_3-2-1_089082_2022-10-13_final
2022-10-16 10:40:21	ga_ls8c_ard_3-2-1_103082_2022-10-16_final
2022-10-19 11:09:18	ga_ls8c_ard_3-2-1_108077_2022-10-19_final
2022-10-22 10:00:33	ga_ls8c_ard_3-2-1_097075_2022-10-22_final
2022-10-24 09:49:00	ga_ls8c_ard_3-2-1_095077_2022-10-24_final
2022-10-25 10:32:16	ga_ls8c_ard_3-2-1_102077_2022-10-25_final
2022-10-31 09:54:49	ga_ls8c_ard_3-2-1_096076_2022-10-31_final
2022-10-31 11:34:06	ga_ls8c_ard_3-2-1_112077_2022-10-31_final
2022-11-02 09:43:16	ga_ls8c_ard_3-2-1_094078_2022-11-02_final
2022-11-04 11:09:23	ga_ls8c_ard_3-2-1_108077_2022-11-04_final
2022-11-04 11:09:47	ga_ls8c_ard_3-2-1_108078_2022-11-04_final
2022-11-06 10:59:01	ga_ls8c_ard_3-2-1_106082_2022-11-06_final
2022-11-12 11:58:46	ga_ls8c_ard_3-2-1_116077_2022-11-12_final
2022-11-16 09:54:43	ga_ls8c_ard_3-2-1_096076_2022-11-16_final
2022-11-16 11:34:00	ga_ls8c_ard_3-2-1_112077_2022-11-16_final
2022-11-18 09:43:08	ga_ls8c_ard_3-2-1_094078_2022-11-18_final
2022-11-23 11:40:11	ga_ls8c_ard_3-2-1_113077_2022-11-23_final
2022-11-25 09:48:57	ga_ls8c_ard_3-2-1_095077_2022-11-25_final
2022-11-25 09:49:21	ga_ls8c_ard_3-2-1_095078_2022-11-25_final
2022-12-02 09:54:45	ga_ls8c_ard_3-2-1_096076_2022-12-02_final
2022-12-06 11:09:42	ga_ls8c_ard_3-2-1_108078_2022-12-06_final
2022-12-11 09:48:32	ga_ls8c_ard_3-2-1_095076_2022-12-11_final
2022-12-11 09:48:55	ga_ls8c_ard_3-2-1_095077_2022-12-11_final
2022-12-11 09:49:19	ga_ls8c_ard_3-2-1_095078_2022-12-11_final
2022-12-21 10:27:05	ga_ls8c_ard_3-2-1_101080_2022-12-21_final
2022-12-27 09:48:48	ga_ls8c_ard_3-2-1_095077_2022-12-27_final
2022-12-30 11:58:36	ga_ls8c_ard_3-2-1_116077_2022-12-30_final
2023-01-03 09:54:36	ga_ls8c_ard_3-2-1_096076_2023-01-03_final
2023-01-03 11:34:17	ga_ls8c_ard_3-2-1_112078_2023-01-03_final
2023-01-06 10:27:05	ga_ls8c_ard_3-2-1_101080_2023-01-06_final
2023-01-07 11:09:09	ga_ls8c_ard_3-2-1_108077_2023-01-07_final
2023-01-09 10:59:10	ga_ls8c_ard_3-2-1_106083_2023-01-09_final
2023-01-10 11:40:01	ga_ls8c_ard_3-2-1_113077_2023-01-10_final
2023-01-10 11:40:49	ga_ls8c_ard_3-2-1_113079_2023-01-10_final
2023-01-12 09:49:09	ga_ls8c_ard_3-2-1_095078_2023-01-12_final
2023-01-19 11:34:33	ga_ls8c_ard_3-2-1_112079_2023-01-19_final
2023-01-23 11:09:05	ga_ls8c_ard_3-2-1_108077_2023-01-23_final
2023-02-01 09:24:28	ga_ls8c_ard_3-2-1_091078_2023-01-31_final
2023-02-07 10:27:02	ga_ls8c_ard_3-2-1_101080_2023-02-07_final
2023-02-08 11:09:06	ga_ls8c_ard_3-2-1_108077_2023-02-08_final
2023-02-11 11:40:46	ga_ls8c_ard_3-2-1_113079_2023-02-11_final
2023-02-13 09:48:41	ga_ls8c_ard_3-2-1_095077_2023-02-13_final
2023-02-13 09:49:05	ga_ls8c_ard_3-2-1_095078_2023-02-13_final
2023-02-13 11:27:34	ga_ls8c_ard_3-2-1_111077_2023-02-13_final
2023-02-20 11:33:38	ga_ls8c_ard_3-2-1_112077_2023-02-20_final
2023-02-22 09:41:33	ga_ls8c_ard_3-2-1_094075_2023-02-22_final
2023-02-23 10:26:23	ga_ls8c_ard_3-2-1_101079_2023-02-23_final
2023-02-24 09:35:07	ga_ls8c_ard_3-2-1_092090_2023-02-24_final
2023-03-01 09:48:27	ga_ls8c_ard_3-2-1_095077_2023-03-01_final
2023-03-01 09:48:51	ga_ls8c_ard_3-2-1_095078_2023-03-01_final
2023-03-04 11:58:13	ga_ls8c_ard_3-2-1_116077_2023-03-04_final
2023-03-06 10:08:33	ga_ls8c_ard_3-2-1_098081_2023-03-06_final
2023-03-07 10:50:36	ga_ls8c_ard_3-2-1_105078_2023-03-07_final
2023-03-08 11:33:51	ga_ls8c_ard_3-2-1_112078_2023-03-08_final
2023-03-08 11:34:15	ga_ls8c_ard_3-2-1_112079_2023-03-08_final
2023-03-11 10:26:15	ga_ls8c_ard_3-2-1_101079_2023-03-11_final
2023-03-11 10:26:39	ga_ls8c_ard_3-2-1_101080_2023-03-11_final
2023-03-12 11:08:43	ga_ls8c_ard_3-2-1_108077_2023-03-12_final
2023-03-15 10:02:43	ga_ls8c_ard_3-2-1_097082_2023-03-15_final
2023-03-17 09:48:20	ga_ls8c_ard_3-2-1_095077_2023-03-17_final
2023-03-26 09:42:27	ga_ls8c_ard_3-2-1_094078_2023-03-26_final
2023-03-26 09:42:51	ga_ls8c_ard_3-2-1_094079_2023-03-26_final
2023-03-26 09:43:15	ga_ls8c_ard_3-2-1_094080_2023-03-26_final
2023-03-26 11:21:20	ga_ls8c_ard_3-2-1_110078_2023-03-26_final
2023-03-31 11:39:02	ga_ls8c_ard_3-2-1_113076_2023-03-31_final
2023-04-01 10:45:23	ga_ls8c_ard_3-2-1_104081_2023-04-01_final
2023-04-02 09:47:46	ga_ls8c_ard_3-2-1_095076_2023-04-02_final
2023-04-02 11:27:50	ga_ls8c_ard_3-2-1_111079_2023-04-02_final
2023-04-04 11:15:03	ga_ls8c_ard_3-2-1_109078_2023-04-04_final
2023-04-05 10:19:24	ga_ls8c_ard_3-2-1_100078_2023-04-05_final
2023-04-09 11:32:40	ga_ls8c_ard_3-2-1_112076_2023-04-09_final
2023-04-09 11:33:04	ga_ls8c_ard_3-2-1_112077_2023-04-09_final
2023-04-11 09:40:59	ga_ls8c_ard_3-2-1_094075_2023-04-11_final
2023-04-11 09:42:11	ga_ls8c_ard_3-2-1_094078_2023-04-11_final
2023-04-11 09:42:35	ga_ls8c_ard_3-2-1_094079_2023-04-11_final
2023-04-12 10:25:50	ga_ls8c_ard_3-2-1_101079_2023-04-12_final
2023-04-18 09:47:55	ga_ls8c_ard_3-2-1_095077_2023-04-18_final
2023-04-18 09:48:19	ga_ls8c_ard_3-2-1_095078_2023-04-18_final
2023-04-25 09:53:42	ga_ls8c_ard_3-2-1_096076_2023-04-25_final
2023-04-25 11:33:47	ga_ls8c_ard_3-2-1_112079_2023-04-25_final
2023-04-27 09:42:07	ga_ls8c_ard_3-2-1_094078_2023-04-27_final
2023-04-30 10:14:12	ga_ls8c_ard_3-2-1_099081_2023-04-30_final
2023-05-02 09:59:49	ga_ls8c_ard_3-2-1_097076_2023-05-02_final
2023-05-04 09:47:26	ga_ls8c_ard_3-2-1_095076_2023-05-04_final
2023-05-09 10:07:54	ga_ls8c_ard_3-2-1_098081_2023-05-09_final
2023-05-11 09:53:30	ga_ls8c_ard_3-2-1_096076_2023-05-11_final
2023-05-11 11:31:11	ga_ls8c_ard_3-2-1_112073_2023-05-11_final
2023-05-11 11:32:23	ga_ls8c_ard_3-2-1_112076_2023-05-11_final
2023-05-13 09:41:54	ga_ls8c_ard_3-2-1_094078_2023-05-13_final
2023-05-15 11:08:25	ga_ls8c_ard_3-2-1_108078_2023-05-15_final
2023-05-16 10:13:59	ga_ls8c_ard_3-2-1_099081_2023-05-16_final
2023-05-17 10:58:02	ga_ls8c_ard_3-2-1_106083_2023-05-17_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