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
2022-03-17 11:58:06	ga_ls8c_ard_3-2-1_116077_2022-03-17_final
2022-04-10 11:07:21	ga_ls8c_ard_3-2-1_108074_2022-04-10_final
2022-04-13 11:40:40	ga_ls8c_ard_3-2-1_113080_2022-04-13_final
2022-04-15 09:47:26	ga_ls8c_ard_3-2-1_095075_2022-04-15_final
2022-04-17 09:36:40	ga_ls8c_ard_3-2-1_093079_2022-04-17_final
2022-04-26 09:34:50	ga_ls8c_ard_3-2-1_092090_2022-04-26_final
2022-04-26 11:11:19	ga_ls8c_ard_3-2-1_108084_2022-04-26_final
2022-05-04 11:58:25	ga_ls8c_ard_3-2-1_116078_2022-05-04_final
2022-05-10 11:23:23	ga_ls8c_ard_3-2-1_110083_2022-05-10_final
2022-05-16 10:43:09	ga_ls8c_ard_3-2-1_104075_2022-05-16_final
2022-05-17 09:49:08	ga_ls8c_ard_3-2-1_095079_2022-05-17_final
2022-05-20 10:21:14	ga_ls8c_ard_3-2-1_100082_2022-05-20_final
2022-05-23 10:52:32	ga_ls8c_ard_3-2-1_105083_2022-05-23_final
2022-05-24 09:54:07	ga_ls8c_ard_3-2-1_096076_2022-05-24_final
2022-05-28 11:11:28	ga_ls8c_ard_3-2-1_108084_2022-05-28_final
2022-05-30 10:57:56	ga_ls8c_ard_3-2-1_106081_2022-05-30_final
2022-06-03 10:32:05	ga_ls8c_ard_3-2-1_102078_2022-06-03_final
2022-06-06 11:03:25	ga_ls8c_ard_3-2-1_107079_2022-06-06_final
2022-06-11 11:18:26	ga_ls8c_ard_3-2-1_110070_2022-06-11_final
2022-06-16 10:00:56	ga_ls8c_ard_3-2-1_097077_2022-06-16_final
2022-06-18 11:29:04	ga_ls8c_ard_3-2-1_111081_2022-06-18_final
2022-06-21 10:18:43	ga_ls8c_ard_3-2-1_100075_2022-06-21_final
2022-06-22 09:25:54	ga_ls8c_ard_3-2-1_091082_2022-06-21_final
2022-06-22 09:27:05	ga_ls8c_ard_3-2-1_091085_2022-06-21_final
2022-06-26 10:35:17	ga_ls8c_ard_3-2-1_103070_2022-06-26_final
2022-06-27 09:43:15	ga_ls8c_ard_3-2-1_094079_2022-06-27_final
2022-06-30 10:11:46	ga_ls8c_ard_3-2-1_099073_2022-06-30_final
2022-07-03 10:44:40	ga_ls8c_ard_3-2-1_104078_2022-07-03_final
2022-07-10 09:14:21	ga_ls8c_ard_3-2-1_089084_2022-07-09_final
2022-07-12 10:36:28	ga_ls8c_ard_3-2-1_103073_2022-07-12_final
2022-07-14 10:25:18	ga_ls8c_ard_3-2-1_101076_2022-07-14_final
2022-07-17 09:20:08	ga_ls8c_ard_3-2-1_090083_2022-07-16_final
2022-07-17 10:54:37	ga_ls8c_ard_3-2-1_106072_2022-07-17_final
2022-07-17 10:56:13	ga_ls8c_ard_3-2-1_106076_2022-07-17_final
2022-07-22 11:13:38	ga_ls8c_ard_3-2-1_109073_2022-07-22_final
2022-07-31 11:07:57	ga_ls8c_ard_3-2-1_108074_2022-07-31_final
2022-07-31 11:11:33	ga_ls8c_ard_3-2-1_108083_2022-07-31_final
2022-08-03 10:02:48	ga_ls8c_ard_3-2-1_097081_2022-08-03_final
2022-08-03 10:04:00	ga_ls8c_ard_3-2-1_097084_2022-08-03_final
2022-08-13 10:35:34	ga_ls8c_ard_3-2-1_103070_2022-08-13_final
2022-08-21 09:52:56	ga_ls8c_ard_3-2-1_095087_2022-08-21_final
2022-08-28 09:57:31	ga_ls8c_ard_3-2-1_096083_2022-08-28_final
2022-08-31 10:25:13	ga_ls8c_ard_3-2-1_101075_2022-08-31_final
2022-08-31 10:27:12	ga_ls8c_ard_3-2-1_101080_2022-08-31_final
2022-09-04 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-09-04_final
2022-09-09 10:22:41	ga_ls8c_ard_3-2-1_100084_2022-09-09_final
2022-09-13 11:35:41	ga_ls8c_ard_3-2-1_112081_2022-09-13_final
2022-09-23 10:30:19	ga_ls8c_ard_3-2-1_102072_2022-09-23_final
2022-10-03 09:35:16	ga_ls8c_ard_3-2-1_092089_2022-10-03_final
2022-10-17 09:46:45	ga_ls8c_ard_3-2-1_094087_2022-10-17_final
2022-10-18 10:26:49	ga_ls8c_ard_3-2-1_101079_2022-10-18_final
2022-10-23 10:41:50	ga_ls8c_ard_3-2-1_104070_2022-10-23_final
2022-10-26 11:17:56	ga_ls8c_ard_3-2-1_109083_2022-10-26_final
2022-11-11 09:36:14	ga_ls8c_ard_3-2-1_093076_2022-11-11_final
2022-11-11 11:15:31	ga_ls8c_ard_3-2-1_109077_2022-11-11_final
2022-11-12 10:21:05	ga_ls8c_ard_3-2-1_100080_2022-11-12_final
2022-11-20 09:32:47	ga_ls8c_ard_3-2-1_092083_2022-11-20_final
2022-11-24 10:44:34	ga_ls8c_ard_3-2-1_104077_2022-11-24_final
2022-11-29 11:01:32	ga_ls8c_ard_3-2-1_107073_2022-11-29_final
2022-11-29 11:04:43	ga_ls8c_ard_3-2-1_107081_2022-11-29_final
2022-11-30 10:08:42	ga_ls8c_ard_3-2-1_098080_2022-11-30_final
2022-12-01 10:52:22	ga_ls8c_ard_3-2-1_105081_2022-12-01_final
2022-12-03 10:38:48	ga_ls8c_ard_3-2-1_103078_2022-12-03_final
2022-12-08 10:56:56	ga_ls8c_ard_3-2-1_106077_2022-12-08_final
2022-12-13 09:36:33	ga_ls8c_ard_3-2-1_093077_2022-12-13_final
2022-12-13 09:38:09	ga_ls8c_ard_3-2-1_093081_2022-12-13_final
2022-12-14 10:21:24	ga_ls8c_ard_3-2-1_100081_2022-12-14_final
2022-12-20 09:46:38	ga_ls8c_ard_3-2-1_094087_2022-12-20_final
2022-12-21 10:27:29	ga_ls8c_ard_3-2-1_101081_2022-12-21_final
2022-12-24 09:20:40	ga_ls8c_ard_3-2-1_090084_2022-12-23_final
2022-12-24 10:57:10	ga_ls8c_ard_3-2-1_106078_2022-12-24_final
2022-12-27 11:27:17	ga_ls8c_ard_3-2-1_111076_2022-12-27_final
2022-12-29 09:36:27	ga_ls8c_ard_3-2-1_093077_2022-12-29_final
2022-12-31 09:25:17	ga_ls8c_ard_3-2-1_091080_2022-12-30_final
2022-12-31 11:04:34	ga_ls8c_ard_3-2-1_107081_2022-12-31_final
2023-01-01 10:06:57	ga_ls8c_ard_3-2-1_098076_2023-01-01_final
2023-01-07 09:30:40	ga_ls8c_ard_3-2-1_092078_2023-01-07_final
2023-01-09 09:20:41	ga_ls8c_ard_3-2-1_090084_2023-01-08_final
2023-01-15 10:20:25	ga_ls8c_ard_3-2-1_100079_2023-01-15_final
2023-01-20 10:34:57	ga_ls8c_ard_3-2-1_103069_2023-01-20_final
2023-02-10 09:18:38	ga_ls8c_ard_3-2-1_090079_2023-02-09_final
2023-02-14 10:31:32	ga_ls8c_ard_3-2-1_102076_2023-02-14_final
2023-02-16 10:21:09	ga_ls8c_ard_3-2-1_100081_2023-02-16_final
2023-03-08 11:35:26	ga_ls8c_ard_3-2-1_112082_2023-03-08_final
2023-03-11 10:23:28	ga_ls8c_ard_3-2-1_101072_2023-03-11_final
2023-03-12 11:09:31	ga_ls8c_ard_3-2-1_108079_2023-03-12_final
2023-03-16 10:44:22	ga_ls8c_ard_3-2-1_104078_2023-03-16_final
2023-03-30 10:56:11	ga_ls8c_ard_3-2-1_106077_2023-03-30_final
2023-04-02 11:29:50	ga_ls8c_ard_3-2-1_111084_2023-04-02_final
2023-04-04 09:37:21	ga_ls8c_ard_3-2-1_093081_2023-04-04_final
2023-04-06 11:00:39	ga_ls8c_ard_3-2-1_107073_2023-04-06_final
2023-04-07 10:08:36	ga_ls8c_ard_3-2-1_098082_2023-04-07_final
2023-04-20 11:11:14	ga_ls8c_ard_3-2-1_109069_2023-04-20_final
2023-04-20 11:16:01	ga_ls8c_ard_3-2-1_109081_2023-04-20_final
2023-04-24 09:14:02	ga_ls8c_ard_3-2-1_089085_2023-04-23_final
2023-04-27 11:23:48	ga_ls8c_ard_3-2-1_110085_2023-04-27_final
2023-05-01 10:53:28	ga_ls8c_ard_3-2-1_106071_2023-05-01_final
2023-05-06 11:15:08	ga_ls8c_ard_3-2-1_109079_2023-05-06_final
2023-05-08 11:00:20	ga_ls8c_ard_3-2-1_107073_2023-05-08_final
2023-05-08 11:03:32	ga_ls8c_ard_3-2-1_107081_2023-05-08_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