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
2022-05-11 10:26:11	ga_ls8c_ard_3-2-1_101079_2022-05-11_final
2022-05-11 10:26:35	ga_ls8c_ard_3-2-1_101080_2022-05-11_final
2022-05-19 11:15:40	ga_ls8c_ard_3-2-1_109079_2022-05-19_final
2022-05-19 11:16:04	ga_ls8c_ard_3-2-1_109080_2022-05-19_final
2022-06-09 09:56:41	ga_ls8c_ard_3-2-1_096082_2022-06-09_final
2022-06-09 11:33:34	ga_ls8c_ard_3-2-1_112077_2022-06-09_final
2022-06-15 10:58:57	ga_ls8c_ard_3-2-1_106083_2022-06-15_final
2022-06-18 09:49:23	ga_ls8c_ard_3-2-1_095079_2022-06-18_final
2022-06-22 11:03:11	ga_ls8c_ard_3-2-1_107078_2022-06-22_final
2022-06-24 09:14:20	ga_ls8c_ard_3-2-1_089084_2022-06-23_final
2022-06-25 09:54:25	ga_ls8c_ard_3-2-1_096076_2022-06-25_final
2022-07-02 10:03:00	ga_ls8c_ard_3-2-1_097082_2022-07-02_final
2022-07-02 11:39:05	ga_ls8c_ard_3-2-1_113075_2022-07-02_final
2022-07-04 11:27:56	ga_ls8c_ard_3-2-1_111078_2022-07-04_final
2022-07-04 11:28:20	ga_ls8c_ard_3-2-1_111079_2022-07-04_final
2022-07-04 11:28:43	ga_ls8c_ard_3-2-1_111080_2022-07-04_final
2022-07-05 10:32:18	ga_ls8c_ard_3-2-1_102078_2022-07-05_final
2022-07-06 11:15:58	ga_ls8c_ard_3-2-1_109079_2022-07-06_final
2022-07-08 11:03:12	ga_ls8c_ard_3-2-1_107078_2022-07-08_final
2022-07-09 10:09:10	ga_ls8c_ard_3-2-1_098082_2022-07-09_final
2022-07-11 09:54:49	ga_ls8c_ard_3-2-1_096077_2022-07-11_final
2022-07-11 11:34:54	ga_ls8c_ard_3-2-1_112080_2022-07-11_final
2022-07-12 10:37:40	ga_ls8c_ard_3-2-1_103076_2022-07-12_final
2022-07-13 09:42:51	ga_ls8c_ard_3-2-1_094078_2022-07-13_final
2022-07-13 11:22:08	ga_ls8c_ard_3-2-1_110079_2022-07-13_final
2022-07-21 10:32:21	ga_ls8c_ard_3-2-1_102078_2022-07-21_final
2022-07-22 09:38:21	ga_ls8c_ard_3-2-1_093082_2022-07-22_final
2022-07-25 10:08:53	ga_ls8c_ard_3-2-1_098081_2022-07-25_final
2022-07-27 09:54:33	ga_ls8c_ard_3-2-1_096076_2022-07-27_final
2022-08-05 11:28:08	ga_ls8c_ard_3-2-1_111078_2022-08-05_final
2022-08-06 10:32:56	ga_ls8c_ard_3-2-1_102079_2022-08-06_final
2022-08-07 11:16:12	ga_ls8c_ard_3-2-1_109079_2022-08-07_final
2022-08-12 11:35:10	ga_ls8c_ard_3-2-1_112080_2022-08-12_final
2022-08-13 10:37:33	ga_ls8c_ard_3-2-1_103075_2022-08-13_final
2022-08-14 09:43:08	ga_ls8c_ard_3-2-1_094078_2022-08-14_final
2022-08-14 11:22:25	ga_ls8c_ard_3-2-1_110079_2022-08-14_final
2022-08-14 11:22:49	ga_ls8c_ard_3-2-1_110080_2022-08-14_final
2022-08-15 10:26:48	ga_ls8c_ard_3-2-1_101079_2022-08-15_final
2022-08-15 10:27:12	ga_ls8c_ard_3-2-1_101080_2022-08-15_final
2022-08-17 10:12:51	ga_ls8c_ard_3-2-1_099075_2022-08-17_final
2022-08-19 10:03:17	ga_ls8c_ard_3-2-1_097082_2022-08-19_final
2022-08-19 11:40:11	ga_ls8c_ard_3-2-1_113077_2022-08-19_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
2022-08-28 09:55:07	ga_ls8c_ard_3-2-1_096077_2022-08-28_final
2022-08-28 11:33:12	ga_ls8c_ard_3-2-1_112075_2022-08-28_final
2022-08-29 10:39:10	ga_ls8c_ard_3-2-1_103079_2022-08-29_final
2022-09-01 11:09:16	ga_ls8c_ard_3-2-1_108077_2022-09-01_final
2022-09-04 10:00:30	ga_ls8c_ard_3-2-1_097075_2022-09-04_final
2022-09-05 10:44:58	ga_ls8c_ard_3-2-1_104078_2022-09-05_final
2022-09-06 09:49:21	ga_ls8c_ard_3-2-1_095078_2022-09-06_final
2022-09-11 10:09:32	ga_ls8c_ard_3-2-1_098082_2022-09-11_final
2022-09-13 09:54:48	ga_ls8c_ard_3-2-1_096076_2022-09-13_final
2022-09-13 11:33:41	ga_ls8c_ard_3-2-1_112076_2022-09-13_final
2022-09-13 11:34:53	ga_ls8c_ard_3-2-1_112079_2022-09-13_final
2022-09-20 10:00:36	ga_ls8c_ard_3-2-1_097075_2022-09-20_final
2022-09-21 10:45:28	ga_ls8c_ard_3-2-1_104079_2022-09-21_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
2022-09-29 09:55:13	ga_ls8c_ard_3-2-1_096077_2022-09-29_final
2022-10-02 10:23:19	ga_ls8c_ard_3-2-1_101070_2022-10-02_final
2022-10-06 11:39:51	ga_ls8c_ard_3-2-1_113076_2022-10-06_final
2022-10-07 10:46:12	ga_ls8c_ard_3-2-1_104081_2022-10-07_final
2022-10-08 11:28:39	ga_ls8c_ard_3-2-1_111079_2022-10-08_final
2022-10-14 10:51:06	ga_ls8c_ard_3-2-1_105078_2022-10-14_final
2022-10-15 11:34:22	ga_ls8c_ard_3-2-1_112078_2022-10-15_final
2022-10-16 10:40:21	ga_ls8c_ard_3-2-1_103082_2022-10-16_final
2022-10-17 09:43:09	ga_ls8c_ard_3-2-1_094078_2022-10-17_final
2022-10-18 10:25:38	ga_ls8c_ard_3-2-1_101076_2022-10-18_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
2022-11-02 11:22:09	ga_ls8c_ard_3-2-1_110078_2022-11-02_final
2022-11-07 11:41:04	ga_ls8c_ard_3-2-1_113079_2022-11-07_final
2022-11-08 10:45:27	ga_ls8c_ard_3-2-1_104079_2022-11-08_final
2022-11-12 10:18:41	ga_ls8c_ard_3-2-1_100074_2022-11-12_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
2022-11-18 09:43:08	ga_ls8c_ard_3-2-1_094078_2022-11-18_final
2022-11-23 11:40:59	ga_ls8c_ard_3-2-1_113079_2022-11-23_final
2022-11-25 09:49:45	ga_ls8c_ard_3-2-1_095079_2022-11-25_final
2022-12-02 09:54:45	ga_ls8c_ard_3-2-1_096076_2022-12-02_final
2022-12-09 10:00:30	ga_ls8c_ard_3-2-1_097075_2022-12-09_final
2022-12-09 11:40:59	ga_ls8c_ard_3-2-1_113079_2022-12-09_final
2022-12-11 09:49:19	ga_ls8c_ard_3-2-1_095078_2022-12-11_final
2022-12-20 09:43:02	ga_ls8c_ard_3-2-1_094078_2022-12-20_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
2023-01-15 11:58:30	ga_ls8c_ard_3-2-1_116077_2023-01-15_final
2023-01-19 09:54:28	ga_ls8c_ard_3-2-1_096076_2023-01-19_final
2023-02-08 09:31:25	ga_ls8c_ard_3-2-1_092080_2023-02-08_final
2023-02-13 09:49:29	ga_ls8c_ard_3-2-1_095079_2023-02-13_final
2023-02-13 11:27:34	ga_ls8c_ard_3-2-1_111077_2023-02-13_final
2023-02-15 09:38:18	ga_ls8c_ard_3-2-1_093082_2023-02-15_final
2023-02-18 10:08:45	ga_ls8c_ard_3-2-1_098081_2023-02-18_final
2023-02-22 09:42:45	ga_ls8c_ard_3-2-1_094078_2023-02-22_final
2023-02-27 10:02:49	ga_ls8c_ard_3-2-1_097082_2023-02-27_final
2023-03-01 09:48:03	ga_ls8c_ard_3-2-1_095076_2023-03-01_final
2023-03-01 09:48:27	ga_ls8c_ard_3-2-1_095077_2023-03-01_final
2023-03-04 10:20:56	ga_ls8c_ard_3-2-1_100081_2023-03-04_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