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
2022-07-06 11:13:34	ga_ls8c_ard_3-2-1_109073_2022-07-06_final
2022-07-09 10:07:11	ga_ls8c_ard_3-2-1_098077_2022-07-09_final
2022-07-10 09:14:45	ga_ls8c_ard_3-2-1_089085_2022-07-09_final
2022-07-17 10:54:13	ga_ls8c_ard_3-2-1_106071_2022-07-17_final
2022-07-19 10:41:30	ga_ls8c_ard_3-2-1_104070_2022-07-19_final
2022-07-23 10:17:38	ga_ls8c_ard_3-2-1_100072_2022-07-23_final
2022-07-25 10:05:17	ga_ls8c_ard_3-2-1_098072_2022-07-25_final
2022-07-25 11:47:46	ga_ls8c_ard_3-2-1_114081_2022-07-25_final
2022-07-26 10:46:34	ga_ls8c_ard_3-2-1_105067_2022-07-26_final
2022-07-26 10:46:58	ga_ls8c_ard_3-2-1_105068_2022-07-26_final
2022-07-29 09:45:24	ga_ls8c_ard_3-2-1_094084_2022-07-29_final
2022-07-31 11:11:57	ga_ls8c_ard_3-2-1_108084_2022-07-31_final
2022-08-02 10:54:25	ga_ls8c_ard_3-2-1_106071_2022-08-02_final
2022-08-05 11:24:09	ga_ls8c_ard_3-2-1_111068_2022-08-05_final
2022-08-06 10:29:20	ga_ls8c_ard_3-2-1_102070_2022-08-06_final
2022-08-10 11:47:07	ga_ls8c_ard_3-2-1_114079_2022-08-10_final
2022-08-11 09:14:13	ga_ls8c_ard_3-2-1_089083_2022-08-10_final
2022-08-11 10:52:42	ga_ls8c_ard_3-2-1_105082_2022-08-11_final
2022-08-18 09:20:25	ga_ls8c_ard_3-2-1_090083_2022-08-17_final
2022-08-22 10:29:24	ga_ls8c_ard_3-2-1_102070_2022-08-22_final
2022-08-26 10:04:17	ga_ls8c_ard_3-2-1_098069_2022-08-26_final
2022-08-27 09:13:03	ga_ls8c_ard_3-2-1_089080_2022-08-26_final
2022-08-29 10:40:22	ga_ls8c_ard_3-2-1_103082_2022-08-29_final
2022-09-01 09:32:23	ga_ls8c_ard_3-2-1_092082_2022-09-01_final
2022-09-13 09:52:48	ga_ls8c_ard_3-2-1_096071_2022-09-13_final
2022-09-24 09:38:17	ga_ls8c_ard_3-2-1_093081_2022-09-24_final
2022-09-24 11:15:58	ga_ls8c_ard_3-2-1_109078_2022-09-24_final
2022-09-30 10:35:41	ga_ls8c_ard_3-2-1_103070_2022-09-30_final
2022-10-03 09:32:29	ga_ls8c_ard_3-2-1_092082_2022-10-03_final
2022-10-03 11:06:58	ga_ls8c_ard_3-2-1_108071_2022-10-03_final
2022-10-03 11:07:22	ga_ls8c_ard_3-2-1_108072_2022-10-03_final
2022-10-07 10:41:25	ga_ls8c_ard_3-2-1_104069_2022-10-07_final
2022-10-10 11:15:28	ga_ls8c_ard_3-2-1_109077_2022-10-10_final
2022-10-14 09:15:24	ga_ls8c_ard_3-2-1_089086_2022-10-13_final
2022-10-24 09:46:37	ga_ls8c_ard_3-2-1_095071_2022-10-24_final
2022-10-25 10:31:29	ga_ls8c_ard_3-2-1_102075_2022-10-25_final
2022-10-27 11:59:13	ga_ls8c_ard_3-2-1_116078_2022-10-27_final
2022-10-28 09:26:18	ga_ls8c_ard_3-2-1_091082_2022-10-27_final
2022-10-28 11:05:59	ga_ls8c_ard_3-2-1_107084_2022-10-28_final
2022-10-29 11:45:40	ga_ls8c_ard_3-2-1_114075_2022-10-29_final
2022-10-30 09:13:57	ga_ls8c_ard_3-2-1_089082_2022-10-29_final
2022-11-03 10:23:20	ga_ls8c_ard_3-2-1_101070_2022-11-03_final
2022-11-03 10:27:43	ga_ls8c_ard_3-2-1_101081_2022-11-03_final
2022-11-04 09:32:30	ga_ls8c_ard_3-2-1_092082_2022-11-04_final
2022-11-04 11:06:59	ga_ls8c_ard_3-2-1_108071_2022-11-04_final
2022-11-05 10:13:22	ga_ls8c_ard_3-2-1_099076_2022-11-05_final
2022-11-05 10:16:09	ga_ls8c_ard_3-2-1_099083_2022-11-05_final
2022-11-06 09:20:56	ga_ls8c_ard_3-2-1_090084_2022-11-05_final
2022-11-07 10:02:11	ga_ls8c_ard_3-2-1_097079_2022-11-07_final
2022-11-08 10:41:27	ga_ls8c_ard_3-2-1_104069_2022-11-08_final
2022-11-10 10:30:16	ga_ls8c_ard_3-2-1_102072_2022-11-10_final
2022-11-11 11:13:55	ga_ls8c_ard_3-2-1_109073_2022-11-11_final
2022-11-15 09:13:28	ga_ls8c_ard_3-2-1_089081_2022-11-14_final
2022-11-27 09:38:35	ga_ls8c_ard_3-2-1_093082_2022-11-27_final
2022-11-28 11:59:09	ga_ls8c_ard_3-2-1_116078_2022-11-28_final
2022-11-29 11:05:31	ga_ls8c_ard_3-2-1_107083_2022-11-29_final
2022-11-30 10:05:54	ga_ls8c_ard_3-2-1_098073_2022-11-30_final
2022-12-02 09:58:20	ga_ls8c_ard_3-2-1_096085_2022-12-02_final
2022-12-06 11:10:06	ga_ls8c_ard_3-2-1_108079_2022-12-06_final
2022-12-11 09:51:43	ga_ls8c_ard_3-2-1_095084_2022-12-11_final
2022-12-14 10:18:12	ga_ls8c_ard_3-2-1_100073_2022-12-14_final
2022-12-15 11:04:39	ga_ls8c_ard_3-2-1_107081_2022-12-15_final
2022-12-17 10:47:28	ga_ls8c_ard_3-2-1_105069_2022-12-17_final
2022-12-18 09:52:14	ga_ls8c_ard_3-2-1_096070_2022-12-18_final
2022-12-22 11:11:07	ga_ls8c_ard_3-2-1_108082_2022-12-22_final
2022-12-24 09:22:40	ga_ls8c_ard_3-2-1_090089_2022-12-23_final
2022-12-27 09:52:48	ga_ls8c_ard_3-2-1_095087_2022-12-27_final
2022-12-30 11:59:00	ga_ls8c_ard_3-2-1_116078_2022-12-30_final
2023-01-03 11:35:05	ga_ls8c_ard_3-2-1_112080_2023-01-03_final
2023-01-05 09:45:49	ga_ls8c_ard_3-2-1_094085_2023-01-05_final
2023-01-06 10:24:41	ga_ls8c_ard_3-2-1_101074_2023-01-06_final
2023-01-07 09:35:27	ga_ls8c_ard_3-2-1_092090_2023-01-07_final
2023-01-08 10:12:19	ga_ls8c_ard_3-2-1_099074_2023-01-08_final
2023-01-13 10:30:49	ga_ls8c_ard_3-2-1_102074_2023-01-13_final
2023-01-14 11:17:39	ga_ls8c_ard_3-2-1_109083_2023-01-14_final
2023-01-17 10:07:37	ga_ls8c_ard_3-2-1_098078_2023-01-17_final
2023-01-18 09:13:35	ga_ls8c_ard_3-2-1_089082_2023-01-17_final
2023-01-19 09:52:52	ga_ls8c_ard_3-2-1_096072_2023-01-19_final
2023-01-20 10:36:33	ga_ls8c_ard_3-2-1_103073_2023-01-20_final
2023-01-22 10:24:37	ga_ls8c_ard_3-2-1_101074_2023-01-22_final
2023-01-23 09:31:24	ga_ls8c_ard_3-2-1_092080_2023-01-23_final
2023-01-23 11:05:54	ga_ls8c_ard_3-2-1_108069_2023-01-23_final
2023-01-24 11:51:58	ga_ls8c_ard_3-2-1_115076_2023-01-24_final
2023-01-25 10:57:56	ga_ls8c_ard_3-2-1_106080_2023-01-25_final
2023-01-26 11:41:37	ga_ls8c_ard_3-2-1_113081_2023-01-26_final
2023-01-30 11:18:06	ga_ls8c_ard_3-2-1_109084_2023-01-30_final
2023-02-06 11:21:28	ga_ls8c_ard_3-2-1_110077_2023-02-06_final
2023-02-07 10:24:39	ga_ls8c_ard_3-2-1_101074_2023-02-07_final
2023-02-11 09:59:29	ga_ls8c_ard_3-2-1_097073_2023-02-11_final
2023-02-15 11:17:35	ga_ls8c_ard_3-2-1_109083_2023-02-15_final
2023-02-16 10:19:09	ga_ls8c_ard_3-2-1_100076_2023-02-16_final
2023-02-17 09:26:18	ga_ls8c_ard_3-2-1_091083_2023-02-16_final
2023-02-19 09:15:06	ga_ls8c_ard_3-2-1_089086_2023-02-18_final
2023-02-20 11:32:02	ga_ls8c_ard_3-2-1_112073_2023-02-20_final
2023-02-22 09:46:20	ga_ls8c_ard_3-2-1_094087_2023-02-22_final
2023-02-26 09:20:21	ga_ls8c_ard_3-2-1_090084_2023-02-25_final
2023-03-05 09:23:42	ga_ls8c_ard_3-2-1_091077_2023-03-04_final
2023-03-06 10:07:21	ga_ls8c_ard_3-2-1_098078_2023-03-06_final
2023-03-07 09:14:31	ga_ls8c_ard_3-2-1_089085_2023-03-06_final
2023-03-07 10:47:48	ga_ls8c_ard_3-2-1_105071_2023-03-07_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