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
2022-03-20 10:50:05	ga_ls8c_ard_3-2-1_105077_2022-03-20_final
2022-03-25 09:31:40	ga_ls8c_ard_3-2-1_092082_2022-03-25_final
2022-04-14 10:45:27	ga_ls8c_ard_3-2-1_104081_2022-04-14_final
2022-04-22 09:55:59	ga_ls8c_ard_3-2-1_096081_2022-04-22_final
2022-04-23 10:37:15	ga_ls8c_ard_3-2-1_103076_2022-04-23_final
2022-04-24 09:44:25	ga_ls8c_ard_3-2-1_094083_2022-04-24_final
2022-04-25 10:23:16	ga_ls8c_ard_3-2-1_101072_2022-04-25_final
2022-04-29 10:00:07	ga_ls8c_ard_3-2-1_097076_2022-04-29_final
2022-05-07 10:50:52	ga_ls8c_ard_3-2-1_105079_2022-05-07_final
2022-05-20 10:18:27	ga_ls8c_ard_3-2-1_100075_2022-05-20_final
2022-05-25 10:38:34	ga_ls8c_ard_3-2-1_103079_2022-05-25_final
2022-05-25 10:38:58	ga_ls8c_ard_3-2-1_103080_2022-05-25_final
2022-05-27 10:23:24	ga_ls8c_ard_3-2-1_101072_2022-05-27_final
2022-06-04 09:38:28	ga_ls8c_ard_3-2-1_093083_2022-06-04_final
2022-06-08 10:47:54	ga_ls8c_ard_3-2-1_105071_2022-06-08_final
2022-06-15 10:56:33	ga_ls8c_ard_3-2-1_106077_2022-06-15_final
2022-06-16 10:03:20	ga_ls8c_ard_3-2-1_097083_2022-06-16_final
2022-06-17 10:45:24	ga_ls8c_ard_3-2-1_104080_2022-06-17_final
2022-06-24 10:50:50	ga_ls8c_ard_3-2-1_105078_2022-06-24_final
2022-06-25 09:53:13	ga_ls8c_ard_3-2-1_096073_2022-06-25_final
2022-07-06 09:38:17	ga_ls8c_ard_3-2-1_093082_2022-07-06_final
2022-07-08 11:03:36	ga_ls8c_ard_3-2-1_107079_2022-07-08_final
2022-07-09 10:05:35	ga_ls8c_ard_3-2-1_098073_2022-07-09_final
2022-07-11 09:54:01	ga_ls8c_ard_3-2-1_096075_2022-07-11_final
2022-07-13 09:43:14	ga_ls8c_ard_3-2-1_094079_2022-07-13_final
2022-07-17 09:18:08	ga_ls8c_ard_3-2-1_090078_2022-07-16_final
2022-07-17 09:19:20	ga_ls8c_ard_3-2-1_090081_2022-07-16_final
2022-07-21 10:33:09	ga_ls8c_ard_3-2-1_102080_2022-07-21_final
2022-07-30 10:27:29	ga_ls8c_ard_3-2-1_101081_2022-07-30_final
2022-07-31 11:07:10	ga_ls8c_ard_3-2-1_108072_2022-07-31_final
2022-08-11 10:51:54	ga_ls8c_ard_3-2-1_105080_2022-08-11_final
2022-08-18 10:57:43	ga_ls8c_ard_3-2-1_106079_2022-08-18_final
2022-08-19 11:39:23	ga_ls8c_ard_3-2-1_113075_2022-08-19_final
2022-08-21 11:29:01	ga_ls8c_ard_3-2-1_111080_2022-08-21_final
2022-08-22 10:33:24	ga_ls8c_ard_3-2-1_102080_2022-08-22_final
2022-08-23 09:36:58	ga_ls8c_ard_3-2-1_093078_2022-08-23_final
2022-08-29 10:39:34	ga_ls8c_ard_3-2-1_103080_2022-08-29_final
2022-09-10 11:05:09	ga_ls8c_ard_3-2-1_107082_2022-09-10_final
2022-09-17 11:10:35	ga_ls8c_ard_3-2-1_108080_2022-09-17_final
2022-09-19 10:59:25	ga_ls8c_ard_3-2-1_106083_2022-09-19_final
2022-09-24 09:36:41	ga_ls8c_ard_3-2-1_093077_2022-09-24_final
2022-09-27 10:07:11	ga_ls8c_ard_3-2-1_098076_2022-09-27_final
2022-09-28 10:48:03	ga_ls8c_ard_3-2-1_105070_2022-09-28_final
2022-09-29 09:54:25	ga_ls8c_ard_3-2-1_096075_2022-09-29_final
2022-09-29 09:56:25	ga_ls8c_ard_3-2-1_096080_2022-09-29_final
2022-10-05 10:58:35	ga_ls8c_ard_3-2-1_106081_2022-10-05_final
2022-10-07 10:46:12	ga_ls8c_ard_3-2-1_104081_2022-10-07_final
2022-10-13 10:06:14	ga_ls8c_ard_3-2-1_098074_2022-10-13_final
2022-10-14 10:51:53	ga_ls8c_ard_3-2-1_105080_2022-10-14_final
2022-10-14 10:53:05	ga_ls8c_ard_3-2-1_105083_2022-10-14_final
2022-10-19 11:08:54	ga_ls8c_ard_3-2-1_108076_2022-10-19_final
2022-10-26 09:36:40	ga_ls8c_ard_3-2-1_093077_2022-10-26_final
2022-11-05 10:12:10	ga_ls8c_ard_3-2-1_099073_2022-11-05_final
2022-11-09 09:48:37	ga_ls8c_ard_3-2-1_095076_2022-11-09_final
2022-11-11 09:38:38	ga_ls8c_ard_3-2-1_093082_2022-11-11_final
2022-11-18 09:42:20	ga_ls8c_ard_3-2-1_094076_2022-11-18_final
2022-11-18 09:42:44	ga_ls8c_ard_3-2-1_094077_2022-11-18_final
2022-11-21 10:13:15	ga_ls8c_ard_3-2-1_099076_2022-11-21_final
2022-11-24 10:42:10	ga_ls8c_ard_3-2-1_104071_2022-11-24_final
2022-11-25 09:50:09	ga_ls8c_ard_3-2-1_095080_2022-11-25_final
2022-11-29 11:05:07	ga_ls8c_ard_3-2-1_107082_2022-11-29_final
2022-11-30 10:09:30	ga_ls8c_ard_3-2-1_098082_2022-11-30_final
2022-12-10 10:42:10	ga_ls8c_ard_3-2-1_104071_2022-12-10_final
2022-12-11 11:28:12	ga_ls8c_ard_3-2-1_111078_2022-12-11_final
2022-12-11 11:29:48	ga_ls8c_ard_3-2-1_111082_2022-12-11_final
2022-12-18 09:57:01	ga_ls8c_ard_3-2-1_096082_2022-12-18_final
2022-12-18 11:35:30	ga_ls8c_ard_3-2-1_112081_2022-12-18_final
2022-12-27 11:28:53	ga_ls8c_ard_3-2-1_111080_2022-12-27_final
2023-01-12 11:28:02	ga_ls8c_ard_3-2-1_111078_2023-01-12_final
2023-01-12 11:28:50	ga_ls8c_ard_3-2-1_111080_2023-01-12_final
2023-01-16 09:25:58	ga_ls8c_ard_3-2-1_091082_2023-01-15_final
2023-02-05 10:40:13	ga_ls8c_ard_3-2-1_103082_2023-02-05_final
2023-02-07 10:25:27	ga_ls8c_ard_3-2-1_101076_2023-02-07_final
2023-02-11 11:39:34	ga_ls8c_ard_3-2-1_113076_2023-02-11_final
2023-02-17 09:25:55	ga_ls8c_ard_3-2-1_091082_2023-02-16_final
2023-02-21 10:36:48	ga_ls8c_ard_3-2-1_103074_2023-02-21_final
2023-03-01 09:49:15	ga_ls8c_ard_3-2-1_095079_2023-03-01_final
2023-03-05 09:25:42	ga_ls8c_ard_3-2-1_091082_2023-03-04_final
2023-03-14 10:56:21	ga_ls8c_ard_3-2-1_106077_2023-03-14_final
2023-03-15 11:38:48	ga_ls8c_ard_3-2-1_113075_2023-03-15_final
2023-03-16 10:45:10	ga_ls8c_ard_3-2-1_104080_2023-03-16_final
2023-03-16 10:45:34	ga_ls8c_ard_3-2-1_104081_2023-03-16_final
2023-03-17 09:47:56	ga_ls8c_ard_3-2-1_095076_2023-03-17_final
2023-03-21 09:23:58	ga_ls8c_ard_3-2-1_091078_2023-03-20_final
2023-03-28 11:08:57	ga_ls8c_ard_3-2-1_108078_2023-03-28_final
2023-04-06 11:03:26	ga_ls8c_ard_3-2-1_107080_2023-04-06_final
2023-04-09 09:54:59	ga_ls8c_ard_3-2-1_096079_2023-04-09_final
2023-04-14 10:11:29	ga_ls8c_ard_3-2-1_099074_2023-04-14_final
2023-04-15 10:58:20	ga_ls8c_ard_3-2-1_106083_2023-04-15_final
2023-04-16 11:38:47	ga_ls8c_ard_3-2-1_113076_2023-04-16_final
2023-04-20 09:38:20	ga_ls8c_ard_3-2-1_093084_2023-04-20_final
2023-04-24 10:50:55	ga_ls8c_ard_3-2-1_105080_2023-04-24_final
2023-04-25 11:33:23	ga_ls8c_ard_3-2-1_112078_2023-04-25_final
2023-05-01 09:19:22	ga_ls8c_ard_3-2-1_090083_2023-04-30_final
2023-05-06 09:37:27	ga_ls8c_ard_3-2-1_093082_2023-05-06_final
2023-05-08 11:02:44	ga_ls8c_ard_3-2-1_107079_2023-05-08_final
2023-05-09 10:05:30	ga_ls8c_ard_3-2-1_098075_2023-05-09_final
2023-05-09 11:44:47	ga_ls8c_ard_3-2-1_114076_2023-05-09_final
2023-05-11 11:34:22	ga_ls8c_ard_3-2-1_112081_2023-05-11_final
2023-05-15 09:31:32	ga_ls8c_ard_3-2-1_092083_2023-05-15_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