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
2022-04-06 11:33:38	ga_ls8c_ard_3-2-1_112078_2022-04-06_final
2022-04-06 11:34:02	ga_ls8c_ard_3-2-1_112079_2022-04-06_final
2022-04-06 11:34:26	ga_ls8c_ard_3-2-1_112080_2022-04-06_final
2022-04-07 10:36:50	ga_ls8c_ard_3-2-1_103075_2022-04-07_final
2022-04-07 10:38:25	ga_ls8c_ard_3-2-1_103079_2022-04-07_final
2022-04-09 10:26:05	ga_ls8c_ard_3-2-1_101079_2022-04-09_final
2022-04-11 10:14:32	ga_ls8c_ard_3-2-1_099081_2022-04-11_final
2022-04-15 11:27:07	ga_ls8c_ard_3-2-1_111077_2022-04-15_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
2022-04-21 10:50:25	ga_ls8c_ard_3-2-1_105078_2022-04-21_final
2022-04-23 10:36:51	ga_ls8c_ard_3-2-1_103075_2022-04-23_final
2022-04-26 11:06:31	ga_ls8c_ard_3-2-1_108072_2022-04-26_final
2022-04-30 10:43:47	ga_ls8c_ard_3-2-1_104077_2022-04-30_final
2022-05-01 11:28:16	ga_ls8c_ard_3-2-1_111080_2022-05-01_final
2022-05-09 10:38:31	ga_ls8c_ard_3-2-1_103079_2022-05-09_final
2022-05-11 10:26:11	ga_ls8c_ard_3-2-1_101079_2022-05-11_final
2022-05-13 10:14:38	ga_ls8c_ard_3-2-1_099081_2022-05-13_final
2022-05-17 09:49:08	ga_ls8c_ard_3-2-1_095079_2022-05-17_final
2022-05-18 10:31:12	ga_ls8c_ard_3-2-1_102076_2022-05-18_final
2022-05-24 11:34:12	ga_ls8c_ard_3-2-1_112079_2022-05-24_final
2022-05-27 10:26:12	ga_ls8c_ard_3-2-1_101079_2022-05-27_final
2022-06-09 09:54:17	ga_ls8c_ard_3-2-1_096076_2022-06-09_final
2022-06-11 09:42:45	ga_ls8c_ard_3-2-1_094078_2022-06-11_final
2022-06-16 10:00:08	ga_ls8c_ard_3-2-1_097075_2022-06-16_final
2022-06-18 09:49:47	ga_ls8c_ard_3-2-1_095080_2022-06-18_final
2022-06-19 10:31:28	ga_ls8c_ard_3-2-1_102076_2022-06-19_final
2022-06-20 11:15:56	ga_ls8c_ard_3-2-1_109079_2022-06-20_final
2022-06-22 11:04:47	ga_ls8c_ard_3-2-1_107082_2022-06-22_final
2022-06-25 09:54:49	ga_ls8c_ard_3-2-1_096077_2022-06-25_final
2022-06-25 11:34:54	ga_ls8c_ard_3-2-1_112080_2022-06-25_final
2022-06-26 10:37:41	ga_ls8c_ard_3-2-1_103076_2022-06-26_final
2022-07-02 11:39:29	ga_ls8c_ard_3-2-1_113076_2022-07-02_final
2022-07-11 09:54:25	ga_ls8c_ard_3-2-1_096076_2022-07-11_final
2022-07-11 09:54:49	ga_ls8c_ard_3-2-1_096077_2022-07-11_final
2022-07-19 10:43:53	ga_ls8c_ard_3-2-1_104076_2022-07-19_final
2022-07-19 10:44:17	ga_ls8c_ard_3-2-1_104077_2022-07-19_final
2022-07-19 10:44:41	ga_ls8c_ard_3-2-1_104078_2022-07-19_final
2022-07-20 11:28:22	ga_ls8c_ard_3-2-1_111079_2022-07-20_final
2022-07-28 10:39:25	ga_ls8c_ard_3-2-1_103080_2022-07-28_final
2022-08-01 10:12:45	ga_ls8c_ard_3-2-1_099075_2022-08-01_final
2022-08-03 10:03:12	ga_ls8c_ard_3-2-1_097082_2022-08-03_final
2022-08-04 10:44:52	ga_ls8c_ard_3-2-1_104078_2022-08-04_final
2022-08-05 09:49:15	ga_ls8c_ard_3-2-1_095078_2022-08-05_final
2022-08-07 11:16:36	ga_ls8c_ard_3-2-1_109080_2022-08-07_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
2022-08-16 11:10:28	ga_ls8c_ard_3-2-1_108080_2022-08-16_final
2022-08-19 10:00:54	ga_ls8c_ard_3-2-1_097076_2022-08-19_final
2022-08-28 09:54:19	ga_ls8c_ard_3-2-1_096075_2022-08-28_final
2022-08-28 09:56:19	ga_ls8c_ard_3-2-1_096080_2022-08-28_final
2022-08-28 11:34:24	ga_ls8c_ard_3-2-1_112078_2022-08-28_final
2022-08-31 10:26:48	ga_ls8c_ard_3-2-1_101079_2022-08-31_final
2022-09-01 11:10:28	ga_ls8c_ard_3-2-1_108080_2022-09-01_final
2022-09-05 10:44:34	ga_ls8c_ard_3-2-1_104077_2022-09-05_final
2022-09-05 10:46:10	ga_ls8c_ard_3-2-1_104081_2022-09-05_final
2022-09-13 09:54:24	ga_ls8c_ard_3-2-1_096075_2022-09-13_final
2022-09-13 11:33:17	ga_ls8c_ard_3-2-1_112075_2022-09-13_final
2022-09-16 10:27:19	ga_ls8c_ard_3-2-1_101080_2022-09-16_final
2022-09-17 11:10:35	ga_ls8c_ard_3-2-1_108080_2022-09-17_final
2022-09-18 10:12:58	ga_ls8c_ard_3-2-1_099075_2022-09-18_final
2022-09-20 11:39:53	ga_ls8c_ard_3-2-1_113076_2022-09-20_final
2022-09-21 10:46:16	ga_ls8c_ard_3-2-1_104081_2022-09-21_final
2022-09-22 11:29:08	ga_ls8c_ard_3-2-1_111080_2022-09-22_final
2022-09-23 10:33:30	ga_ls8c_ard_3-2-1_102080_2022-09-23_final
2022-09-27 10:09:11	ga_ls8c_ard_3-2-1_098081_2022-09-27_final
2022-09-28 10:51:39	ga_ls8c_ard_3-2-1_105079_2022-09-28_final
2022-09-30 10:37:41	ga_ls8c_ard_3-2-1_103075_2022-09-30_final
2022-10-01 09:43:15	ga_ls8c_ard_3-2-1_094078_2022-10-01_final
2022-10-06 10:03:21	ga_ls8c_ard_3-2-1_097082_2022-10-06_final
2022-10-08 11:29:03	ga_ls8c_ard_3-2-1_111080_2022-10-08_final
2022-10-09 10:33:25	ga_ls8c_ard_3-2-1_102080_2022-10-09_final
2022-10-15 11:34:22	ga_ls8c_ard_3-2-1_112078_2022-10-15_final
2022-10-15 11:35:10	ga_ls8c_ard_3-2-1_112080_2022-10-15_final
2022-10-24 11:28:17	ga_ls8c_ard_3-2-1_111078_2022-10-24_final
2022-10-31 11:35:18	ga_ls8c_ard_3-2-1_112080_2022-10-31_final
2022-11-16 09:54:43	ga_ls8c_ard_3-2-1_096076_2022-11-16_final
2022-11-18 11:22:01	ga_ls8c_ard_3-2-1_110078_2022-11-18_final
2022-11-23 10:00:30	ga_ls8c_ard_3-2-1_097075_2022-11-23_final
2022-11-25 09:48:57	ga_ls8c_ard_3-2-1_095077_2022-11-25_final
2022-11-25 11:28:38	ga_ls8c_ard_3-2-1_111079_2022-11-25_final
2022-11-29 11:03:31	ga_ls8c_ard_3-2-1_107078_2022-11-29_final
2022-12-11 09:48:55	ga_ls8c_ard_3-2-1_095077_2022-12-11_final
2022-12-15 11:03:27	ga_ls8c_ard_3-2-1_107078_2022-12-15_final
2022-12-18 09:55:25	ga_ls8c_ard_3-2-1_096078_2022-12-18_final
2022-12-27 09:49:12	ga_ls8c_ard_3-2-1_095078_2022-12-27_final
2023-01-03 09:55:00	ga_ls8c_ard_3-2-1_096077_2023-01-03_final
2023-01-05 11:22:19	ga_ls8c_ard_3-2-1_110079_2023-01-05_final
2023-01-19 09:54:28	ga_ls8c_ard_3-2-1_096076_2023-01-19_final
2023-02-16 10:20:45	ga_ls8c_ard_3-2-1_100080_2023-02-16_final
2023-02-17 11:03:12	ga_ls8c_ard_3-2-1_107078_2023-02-17_final
2023-02-20 09:56:21	ga_ls8c_ard_3-2-1_096081_2023-02-20_final
2023-02-20 11:34:26	ga_ls8c_ard_3-2-1_112079_2023-02-20_final
2023-02-24 09:35:07	ga_ls8c_ard_3-2-1_092090_2023-02-24_final
2023-02-24 11:08:49	ga_ls8c_ard_3-2-1_108077_2023-02-24_final
2023-03-01 09:49:39	ga_ls8c_ard_3-2-1_095080_2023-03-01_final
2023-03-09 10:38:37	ga_ls8c_ard_3-2-1_103079_2023-03-09_final
2023-03-15 10:02:43	ga_ls8c_ard_3-2-1_097082_2023-03-15_final
2023-03-15 11:39:12	ga_ls8c_ard_3-2-1_113076_2023-03-15_final
2023-03-17 09:49:32	ga_ls8c_ard_3-2-1_095080_2023-03-17_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