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
2023-02-01 11:04:32	ga_ls8c_ard_3-2-1_107081_2023-02-01_final
2023-02-03 10:50:35	ga_ls8c_ard_3-2-1_105077_2023-02-03_final
2023-02-03 10:51:47	ga_ls8c_ard_3-2-1_105080_2023-02-03_final
2023-02-26 09:19:33	ga_ls8c_ard_3-2-1_090082_2023-02-25_final
2023-03-20 10:18:24	ga_ls8c_ard_3-2-1_100075_2023-03-20_final
2023-03-21 11:03:38	ga_ls8c_ard_3-2-1_107080_2023-03-21_final
2023-03-22 10:05:12	ga_ls8c_ard_3-2-1_098073_2023-03-22_final
2023-03-22 11:46:29	ga_ls8c_ard_3-2-1_114079_2023-03-22_final
2023-06-26 10:05:16	ga_ls8c_ard_3-2-1_098074_2023-06-26_final
2023-06-27 09:12:04	ga_ls8c_ard_3-2-1_089080_2023-06-26_final
2023-06-27 09:12:28	ga_ls8c_ard_3-2-1_089081_2023-06-26_final
2023-06-27 09:13:39	ga_ls8c_ard_3-2-1_089084_2023-06-26_final
2023-06-29 10:38:37	ga_ls8c_ard_3-2-1_103080_2023-06-29_final
2023-07-02 09:30:40	ga_ls8c_ard_3-2-1_092080_2023-07-02_final
2023-07-06 10:41:41	ga_ls8c_ard_3-2-1_104072_2023-07-06_final
2023-07-09 09:34:31	ga_ls8c_ard_3-2-1_093074_2023-07-09_final
2023-07-09 09:36:07	ga_ls8c_ard_3-2-1_093078_2023-07-09_final
2023-07-11 09:23:22	ga_ls8c_ard_3-2-1_091077_2023-07-10_final
2023-07-11 09:24:58	ga_ls8c_ard_3-2-1_091081_2023-07-10_final
2023-07-14 09:51:53	ga_ls8c_ard_3-2-1_096071_2023-07-14_final
2023-07-14 09:52:41	ga_ls8c_ard_3-2-1_096073_2023-07-14_final
2023-07-15 10:37:33	ga_ls8c_ard_3-2-1_103077_2023-07-15_final
2023-07-21 10:00:51	ga_ls8c_ard_3-2-1_097078_2023-07-21_final
2023-07-21 10:01:15	ga_ls8c_ard_3-2-1_097079_2023-07-21_final
2023-07-21 11:40:32	ga_ls8c_ard_3-2-1_113080_2023-07-21_final
2023-07-25 09:35:24	ga_ls8c_ard_3-2-1_093076_2023-07-25_final
2023-07-26 10:18:17	ga_ls8c_ard_3-2-1_100075_2023-07-26_final
2023-07-26 10:20:17	ga_ls8c_ard_3-2-1_100080_2023-07-26_final
2023-07-27 09:24:40	ga_ls8c_ard_3-2-1_091080_2023-07-26_final
2023-07-27 09:25:28	ga_ls8c_ard_3-2-1_091082_2023-07-26_final
2023-07-27 11:02:21	ga_ls8c_ard_3-2-1_107077_2023-07-27_final
2023-07-28 10:03:57	ga_ls8c_ard_3-2-1_098070_2023-07-28_final
2023-07-28 11:46:26	ga_ls8c_ard_3-2-1_114079_2023-07-28_final
2023-07-30 09:55:12	ga_ls8c_ard_3-2-1_096079_2023-07-30_final
2023-07-31 10:34:53	ga_ls8c_ard_3-2-1_103070_2023-07-31_final
2023-08-05 09:19:21	ga_ls8c_ard_3-2-1_090082_2023-08-04_final
2023-08-05 10:54:15	ga_ls8c_ard_3-2-1_106072_2023-08-05_final
2023-08-06 10:01:01	ga_ls8c_ard_3-2-1_097078_2023-08-06_final
2023-08-06 10:01:25	ga_ls8c_ard_3-2-1_097079_2023-08-06_final
2023-08-07 10:41:29	ga_ls8c_ard_3-2-1_104071_2023-08-07_final
2023-08-07 10:41:53	ga_ls8c_ard_3-2-1_104072_2023-08-07_final
2023-08-08 09:47:04	ga_ls8c_ard_3-2-1_095074_2023-08-08_final
2023-08-10 11:14:46	ga_ls8c_ard_3-2-1_109077_2023-08-10_final
2023-08-12 11:05:13	ga_ls8c_ard_3-2-1_107084_2023-08-12_final
2023-08-13 10:05:38	ga_ls8c_ard_3-2-1_098074_2023-08-13_final
2023-08-13 10:08:25	ga_ls8c_ard_3-2-1_098081_2023-08-13_final
2023-08-14 10:50:30	ga_ls8c_ard_3-2-1_105078_2023-08-14_final
2023-08-14 10:52:30	ga_ls8c_ard_3-2-1_105083_2023-08-14_final
2023-08-20 11:51:34	ga_ls8c_ard_3-2-1_115076_2023-08-20_final
2023-08-21 10:54:22	ga_ls8c_ard_3-2-1_106072_2023-08-21_final
2023-08-23 10:41:37	ga_ls8c_ard_3-2-1_104071_2023-08-23_final
2023-08-24 09:47:36	ga_ls8c_ard_3-2-1_095075_2023-08-24_final
2023-08-24 11:23:41	ga_ls8c_ard_3-2-1_111068_2023-08-24_final
2023-08-28 09:24:53	ga_ls8c_ard_3-2-1_091080_2023-08-27_final
2023-08-31 11:35:03	ga_ls8c_ard_3-2-1_112081_2023-08-31_final
2023-09-04 09:32:14	ga_ls8c_ard_3-2-1_092083_2023-09-04_final
2023-09-11 11:17:20	ga_ls8c_ard_3-2-1_109083_2023-09-11_final
2023-09-13 09:24:55	ga_ls8c_ard_3-2-1_091080_2023-09-12_final
2023-09-13 11:03:24	ga_ls8c_ard_3-2-1_107079_2023-09-13_final
2023-09-14 10:07:47	ga_ls8c_ard_3-2-1_098079_2023-09-14_final
2023-09-14 11:44:41	ga_ls8c_ard_3-2-1_114074_2023-09-14_final
2023-09-15 09:12:34	ga_ls8c_ard_3-2-1_089080_2023-09-14_final
2023-09-17 10:36:43	ga_ls8c_ard_3-2-1_103074_2023-09-17_final
2023-09-20 11:05:37	ga_ls8c_ard_3-2-1_108069_2023-09-20_final
2023-09-20 11:08:25	ga_ls8c_ard_3-2-1_108076_2023-09-20_final
2023-09-21 11:52:04	ga_ls8c_ard_3-2-1_115077_2023-09-21_final
2023-09-22 10:57:39	ga_ls8c_ard_3-2-1_106080_2023-09-22_final
2023-09-29 09:25:24	ga_ls8c_ard_3-2-1_091081_2023-09-28_final
2023-09-29 11:04:41	ga_ls8c_ard_3-2-1_107082_2023-09-29_final
2023-10-02 09:53:30	ga_ls8c_ard_3-2-1_096074_2023-10-02_final
2023-10-08 10:58:31	ga_ls8c_ard_3-2-1_106082_2023-10-08_final
2023-10-09 09:59:19	ga_ls8c_ard_3-2-1_097073_2023-10-09_final
2023-10-11 09:51:21	ga_ls8c_ard_3-2-1_095084_2023-10-11_final
2023-10-12 10:31:50	ga_ls8c_ard_3-2-1_102077_2023-10-12_final
2023-10-13 09:35:01	ga_ls8c_ard_3-2-1_093074_2023-10-13_final
2023-10-13 09:38:36	ga_ls8c_ard_3-2-1_093083_2023-10-13_final
2023-10-13 11:13:06	ga_ls8c_ard_3-2-1_109072_2023-10-13_final
2023-10-13 11:17:29	ga_ls8c_ard_3-2-1_109083_2023-10-13_final
2023-10-14 10:20:16	ga_ls8c_ard_3-2-1_100079_2023-10-14_final
2023-10-16 10:04:18	ga_ls8c_ard_3-2-1_098070_2023-10-16_final
2023-10-16 11:46:47	ga_ls8c_ard_3-2-1_114079_2023-10-16_final
2023-10-17 10:51:33	ga_ls8c_ard_3-2-1_105080_2023-10-17_final
2023-10-18 09:54:44	ga_ls8c_ard_3-2-1_096077_2023-10-18_final
2023-10-21 10:22:50	ga_ls8c_ard_3-2-1_101070_2023-10-21_final
2023-10-27 09:50:12	ga_ls8c_ard_3-2-1_095081_2023-10-27_final
2023-10-27 11:27:05	ga_ls8c_ard_3-2-1_111076_2023-10-27_final
2023-10-31 09:25:53	ga_ls8c_ard_3-2-1_091082_2023-10-30_final
2023-11-01 10:04:22	ga_ls8c_ard_3-2-1_098070_2023-11-01_final
2023-11-04 10:37:39	ga_ls8c_ard_3-2-1_103076_2023-11-04_final
2023-11-04 10:38:03	ga_ls8c_ard_3-2-1_103077_2023-11-04_final
2023-11-07 11:06:55	ga_ls8c_ard_3-2-1_108072_2023-11-07_final
2023-11-09 10:58:30	ga_ls8c_ard_3-2-1_106082_2023-11-09_final
2023-11-10 10:01:17	ga_ls8c_ard_3-2-1_097078_2023-11-10_final
2023-11-10 10:01:41	ga_ls8c_ard_3-2-1_097079_2023-11-10_final
2023-11-11 10:42:10	ga_ls8c_ard_3-2-1_104072_2023-11-11_final
2023-11-14 11:15:06	ga_ls8c_ard_3-2-1_109077_2023-11-14_final
2023-11-15 10:18:42	ga_ls8c_ard_3-2-1_100075_2023-11-15_final
2023-11-16 11:03:34	ga_ls8c_ard_3-2-1_107079_2023-11-16_final
2023-11-18 10:47:38	ga_ls8c_ard_3-2-1_105070_2023-11-18_final
2023-11-23 11:05:48	ga_ls8c_ard_3-2-1_108069_2023-11-23_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