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
2022-04-29 11:39:48	ga_ls8c_ard_3-2-1_113078_2022-04-29_final
2022-04-30 10:41:48	ga_ls8c_ard_3-2-1_104072_2022-04-30_final
2022-05-07 10:52:27	ga_ls8c_ard_3-2-1_105083_2022-05-07_final
2022-05-08 09:54:03	ga_ls8c_ard_3-2-1_096076_2022-05-08_final
2022-05-08 09:54:51	ga_ls8c_ard_3-2-1_096078_2022-05-08_final
2022-05-08 09:55:39	ga_ls8c_ard_3-2-1_096080_2022-05-08_final
2022-05-13 10:12:14	ga_ls8c_ard_3-2-1_099075_2022-05-13_final
2022-05-15 10:03:05	ga_ls8c_ard_3-2-1_097083_2022-05-15_final
2022-05-21 11:05:18	ga_ls8c_ard_3-2-1_107084_2022-05-21_final
2022-05-31 11:40:01	ga_ls8c_ard_3-2-1_113078_2022-05-31_final
2022-06-02 11:28:29	ga_ls8c_ard_3-2-1_111080_2022-06-02_final
2022-06-08 10:50:41	ga_ls8c_ard_3-2-1_105078_2022-06-08_final
2022-06-09 09:54:17	ga_ls8c_ard_3-2-1_096076_2022-06-09_final
2022-06-11 11:22:02	ga_ls8c_ard_3-2-1_110079_2022-06-11_final
2022-06-16 10:00:08	ga_ls8c_ard_3-2-1_097075_2022-06-16_final
2022-06-16 11:39:02	ga_ls8c_ard_3-2-1_113075_2022-06-16_final
2022-06-22 11:03:11	ga_ls8c_ard_3-2-1_107078_2022-06-22_final
2022-06-22 11:04:47	ga_ls8c_ard_3-2-1_107082_2022-06-22_final
2022-06-23 10:05:58	ga_ls8c_ard_3-2-1_098074_2022-06-23_final
2022-06-23 10:06:46	ga_ls8c_ard_3-2-1_098076_2022-06-23_final
2022-06-24 10:50:26	ga_ls8c_ard_3-2-1_105077_2022-06-24_final
2022-06-24 10:50:50	ga_ls8c_ard_3-2-1_105078_2022-06-24_final
2022-06-25 09:54:49	ga_ls8c_ard_3-2-1_096077_2022-06-25_final
2022-06-26 10:37:41	ga_ls8c_ard_3-2-1_103076_2022-06-26_final
2022-06-27 11:18:33	ga_ls8c_ard_3-2-1_110070_2022-06-27_final
2022-07-11 09:54:01	ga_ls8c_ard_3-2-1_096075_2022-07-11_final
2022-07-11 11:32:54	ga_ls8c_ard_3-2-1_112075_2022-07-11_final
2022-07-18 10:03:00	ga_ls8c_ard_3-2-1_097082_2022-07-18_final
2022-07-18 11:39:06	ga_ls8c_ard_3-2-1_113075_2022-07-18_final
2022-07-19 10:43:53	ga_ls8c_ard_3-2-1_104076_2022-07-19_final
2022-07-20 11:27:58	ga_ls8c_ard_3-2-1_111078_2022-07-20_final
2022-07-21 10:32:45	ga_ls8c_ard_3-2-1_102079_2022-07-21_final
2022-07-22 09:38:45	ga_ls8c_ard_3-2-1_093083_2022-07-22_final
2022-07-25 10:05:41	ga_ls8c_ard_3-2-1_098073_2022-07-25_final
2022-07-26 10:50:34	ga_ls8c_ard_3-2-1_105077_2022-07-26_final
2022-07-27 09:52:57	ga_ls8c_ard_3-2-1_096072_2022-07-27_final
2022-07-27 09:54:57	ga_ls8c_ard_3-2-1_096077_2022-07-27_final
2022-07-28 10:37:02	ga_ls8c_ard_3-2-1_103074_2022-07-28_final
2022-07-28 10:37:49	ga_ls8c_ard_3-2-1_103076_2022-07-28_final
2022-08-01 10:11:57	ga_ls8c_ard_3-2-1_099073_2022-08-01_final
2022-08-01 10:12:45	ga_ls8c_ard_3-2-1_099075_2022-08-01_final
2022-08-03 11:39:17	ga_ls8c_ard_3-2-1_113075_2022-08-03_final
2022-08-06 10:31:44	ga_ls8c_ard_3-2-1_102076_2022-08-06_final
2022-08-10 10:06:14	ga_ls8c_ard_3-2-1_098074_2022-08-10_final
2022-08-10 11:45:55	ga_ls8c_ard_3-2-1_114076_2022-08-10_final
2022-08-12 11:35:10	ga_ls8c_ard_3-2-1_112080_2022-08-12_final
2022-08-14 11:22:49	ga_ls8c_ard_3-2-1_110080_2022-08-14_final
2022-08-17 10:12:03	ga_ls8c_ard_3-2-1_099073_2022-08-17_final
2022-08-19 10:00:54	ga_ls8c_ard_3-2-1_097076_2022-08-19_final
2022-08-19 10:03:17	ga_ls8c_ard_3-2-1_097082_2022-08-19_final
2022-08-19 11:39:23	ga_ls8c_ard_3-2-1_113075_2022-08-19_final
2022-08-21 11:28:13	ga_ls8c_ard_3-2-1_111078_2022-08-21_final
2022-08-22 10:31:48	ga_ls8c_ard_3-2-1_102076_2022-08-22_final
2022-08-26 10:07:05	ga_ls8c_ard_3-2-1_098076_2022-08-26_final
2022-08-27 10:50:44	ga_ls8c_ard_3-2-1_105077_2022-08-27_final
2022-08-28 09:56:19	ga_ls8c_ard_3-2-1_096080_2022-08-28_final
2022-08-28 11:33:12	ga_ls8c_ard_3-2-1_112075_2022-08-28_final
2022-09-01 09:29:59	ga_ls8c_ard_3-2-1_092076_2022-08-31_final
2022-09-13 09:54:24	ga_ls8c_ard_3-2-1_096075_2022-09-13_final
2022-09-21 10:42:16	ga_ls8c_ard_3-2-1_104071_2022-09-21_final
2022-09-22 11:27:56	ga_ls8c_ard_3-2-1_111077_2022-09-22_final
2022-09-22 11:28:20	ga_ls8c_ard_3-2-1_111078_2022-09-22_final
2022-09-29 09:55:13	ga_ls8c_ard_3-2-1_096077_2022-09-29_final
2022-10-10 09:38:35	ga_ls8c_ard_3-2-1_093082_2022-10-10_final
2022-10-13 10:05:50	ga_ls8c_ard_3-2-1_098073_2022-10-13_final
2022-10-26 09:38:39	ga_ls8c_ard_3-2-1_093082_2022-10-26_final
2022-10-31 09:54:25	ga_ls8c_ard_3-2-1_096075_2022-10-31_final
2022-11-07 11:40:40	ga_ls8c_ard_3-2-1_113078_2022-11-07_final
2022-11-12 10:18:41	ga_ls8c_ard_3-2-1_100074_2022-11-12_final
2022-11-19 10:26:48	ga_ls8c_ard_3-2-1_101079_2022-11-19_final
2022-11-20 09:30:23	ga_ls8c_ard_3-2-1_092077_2022-11-20_final
2022-11-20 11:09:16	ga_ls8c_ard_3-2-1_108077_2022-11-20_final
2022-11-21 10:13:15	ga_ls8c_ard_3-2-1_099076_2022-11-21_final
2022-12-02 11:33:38	ga_ls8c_ard_3-2-1_112076_2022-12-02_final
2022-12-09 10:01:18	ga_ls8c_ard_3-2-1_097077_2022-12-09_final
2022-12-09 10:03:18	ga_ls8c_ard_3-2-1_097082_2022-12-09_final
2022-12-09 11:40:35	ga_ls8c_ard_3-2-1_113078_2022-12-09_final
2022-12-10 10:45:21	ga_ls8c_ard_3-2-1_104079_2022-12-10_final
2022-12-12 10:32:35	ga_ls8c_ard_3-2-1_102078_2022-12-12_final
2022-12-12 10:32:59	ga_ls8c_ard_3-2-1_102079_2022-12-12_final
2022-12-13 09:38:32	ga_ls8c_ard_3-2-1_093082_2022-12-13_final
2022-12-16 10:05:49	ga_ls8c_ard_3-2-1_098073_2022-12-16_final
2022-12-18 09:55:02	ga_ls8c_ard_3-2-1_096077_2022-12-18_final
2022-12-18 09:55:25	ga_ls8c_ard_3-2-1_096078_2022-12-18_final
2022-12-18 11:33:31	ga_ls8c_ard_3-2-1_112076_2022-12-18_final
2023-01-05 11:22:19	ga_ls8c_ard_3-2-1_110079_2023-01-05_final
2023-01-12 09:49:33	ga_ls8c_ard_3-2-1_095079_2023-01-12_final
2023-01-26 10:03:31	ga_ls8c_ard_3-2-1_097083_2023-01-26_final
2023-02-01 09:23:40	ga_ls8c_ard_3-2-1_091076_2023-01-31_final
2023-02-07 10:26:38	ga_ls8c_ard_3-2-1_101079_2023-02-07_final
2023-02-08 09:31:25	ga_ls8c_ard_3-2-1_092080_2023-02-08_final
2023-02-12 10:44:43	ga_ls8c_ard_3-2-1_104078_2023-02-12_final
2023-02-16 10:21:09	ga_ls8c_ard_3-2-1_100081_2023-02-16_final
2023-02-18 10:09:09	ga_ls8c_ard_3-2-1_098082_2023-02-18_final
2023-02-20 09:55:57	ga_ls8c_ard_3-2-1_096080_2023-02-20_final
2023-02-20 09:56:21	ga_ls8c_ard_3-2-1_096081_2023-02-20_final
2023-02-22 09:42:45	ga_ls8c_ard_3-2-1_094078_2023-02-22_final
2023-03-01 11:27:20	ga_ls8c_ard_3-2-1_111077_2023-03-01_final
2023-03-04 10:20:56	ga_ls8c_ard_3-2-1_100081_2023-03-04_final
2023-03-06 11:47:26	ga_ls8c_ard_3-2-1_114081_2023-03-06_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