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
2022-11-05 10:16:09	ga_ls8c_ard_3-2-1_099083_2022-11-05_final
2022-11-06 10:55:25	ga_ls8c_ard_3-2-1_106073_2022-11-06_final
2022-11-06 10:55:49	ga_ls8c_ard_3-2-1_106074_2022-11-06_final
2022-11-07 10:00:35	ga_ls8c_ard_3-2-1_097075_2022-11-07_final
2022-11-14 10:06:42	ga_ls8c_ard_3-2-1_098075_2022-11-14_final
2022-11-16 11:34:24	ga_ls8c_ard_3-2-1_112078_2022-11-16_final
2022-11-18 11:21:37	ga_ls8c_ard_3-2-1_110077_2022-11-18_final
2022-11-18 11:22:01	ga_ls8c_ard_3-2-1_110078_2022-11-18_final
2022-11-22 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-11-21_final
2022-11-22 10:54:31	ga_ls8c_ard_3-2-1_106071_2022-11-22_final
2022-11-23 11:41:23	ga_ls8c_ard_3-2-1_113080_2022-11-23_final
2022-11-24 10:44:58	ga_ls8c_ard_3-2-1_104078_2022-11-24_final
2022-11-24 10:45:22	ga_ls8c_ard_3-2-1_104079_2022-11-24_final
2022-11-27 11:15:53	ga_ls8c_ard_3-2-1_109078_2022-11-27_final
2022-11-27 11:17:05	ga_ls8c_ard_3-2-1_109081_2022-11-27_final
2022-11-28 11:59:09	ga_ls8c_ard_3-2-1_116078_2022-11-28_final
2022-11-29 09:28:14	ga_ls8c_ard_3-2-1_091087_2022-11-28_final
2022-12-01 10:48:46	ga_ls8c_ard_3-2-1_105072_2022-12-01_final
2022-12-02 11:34:49	ga_ls8c_ard_3-2-1_112079_2022-12-02_final
2022-12-03 10:35:37	ga_ls8c_ard_3-2-1_103070_2022-12-03_final
2022-12-03 10:36:48	ga_ls8c_ard_3-2-1_103073_2022-12-03_final
2022-12-04 09:45:34	ga_ls8c_ard_3-2-1_094084_2022-12-04_final
2022-12-07 10:12:28	ga_ls8c_ard_3-2-1_099074_2022-12-07_final
2022-12-09 09:58:30	ga_ls8c_ard_3-2-1_097070_2022-12-09_final
2022-12-09 10:02:30	ga_ls8c_ard_3-2-1_097080_2022-12-09_final
2022-12-11 11:28:12	ga_ls8c_ard_3-2-1_111078_2022-12-11_final
2022-12-13 09:37:45	ga_ls8c_ard_3-2-1_093080_2022-12-13_final
2022-12-17 10:48:16	ga_ls8c_ard_3-2-1_105071_2022-12-17_final
2022-12-18 09:54:14	ga_ls8c_ard_3-2-1_096075_2022-12-18_final
2022-12-18 09:57:01	ga_ls8c_ard_3-2-1_096082_2022-12-18_final
2022-12-18 11:35:06	ga_ls8c_ard_3-2-1_112080_2022-12-18_final
2022-12-20 09:42:14	ga_ls8c_ard_3-2-1_094076_2022-12-20_final
2022-12-20 09:43:26	ga_ls8c_ard_3-2-1_094079_2022-12-20_final
2022-12-22 09:30:14	ga_ls8c_ard_3-2-1_092077_2022-12-22_final
2022-12-22 11:09:31	ga_ls8c_ard_3-2-1_108078_2022-12-22_final
2022-12-24 10:56:46	ga_ls8c_ard_3-2-1_106077_2022-12-24_final
2022-12-25 11:38:50	ga_ls8c_ard_3-2-1_113074_2022-12-25_final
2022-12-25 11:39:14	ga_ls8c_ard_3-2-1_113075_2022-12-25_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
2022-12-29 09:37:15	ga_ls8c_ard_3-2-1_093079_2022-12-29_final
2022-12-30 10:22:06	ga_ls8c_ard_3-2-1_100083_2022-12-30_final
2022-12-31 11:02:11	ga_ls8c_ard_3-2-1_107075_2022-12-31_final
2023-01-02 09:14:56	ga_ls8c_ard_3-2-1_089085_2023-01-01_final
2023-01-03 09:54:36	ga_ls8c_ard_3-2-1_096076_2023-01-03_final
2023-01-03 11:34:41	ga_ls8c_ard_3-2-1_112079_2023-01-03_final
2023-01-03 11:36:40	ga_ls8c_ard_3-2-1_112084_2023-01-03_final
2023-01-05 09:45:25	ga_ls8c_ard_3-2-1_094084_2023-01-05_final
2023-01-06 10:27:05	ga_ls8c_ard_3-2-1_101080_2023-01-06_final
2023-01-07 09:33:03	ga_ls8c_ard_3-2-1_092084_2023-01-07_final
2023-01-09 09:20:17	ga_ls8c_ard_3-2-1_090083_2023-01-08_final
2023-01-09 09:21:29	ga_ls8c_ard_3-2-1_090086_2023-01-08_final
2023-01-12 09:47:34	ga_ls8c_ard_3-2-1_095074_2023-01-12_final
2023-01-14 09:39:10	ga_ls8c_ard_3-2-1_093084_2023-01-14_final
2023-01-15 10:20:25	ga_ls8c_ard_3-2-1_100079_2023-01-15_final
2023-01-18 09:14:23	ga_ls8c_ard_3-2-1_089084_2023-01-17_final
2023-01-19 09:56:52	ga_ls8c_ard_3-2-1_096082_2023-01-19_final
2023-01-20 10:37:21	ga_ls8c_ard_3-2-1_103075_2023-01-20_final
2023-01-21 11:23:49	ga_ls8c_ard_3-2-1_110083_2023-01-21_final
2023-01-25 09:21:27	ga_ls8c_ard_3-2-1_090086_2023-01-24_final
2023-01-26 10:03:31	ga_ls8c_ard_3-2-1_097083_2023-01-26_final
2023-01-26 11:39:37	ga_ls8c_ard_3-2-1_113076_2023-01-26_final
2023-01-30 09:37:13	ga_ls8c_ard_3-2-1_093079_2023-01-30_final
2023-01-30 11:18:06	ga_ls8c_ard_3-2-1_109084_2023-01-30_final
2023-01-31 10:21:17	ga_ls8c_ard_3-2-1_100081_2023-01-31_final
2023-02-06 09:43:47	ga_ls8c_ard_3-2-1_094080_2023-02-06_final
2023-02-06 11:21:28	ga_ls8c_ard_3-2-1_110077_2023-02-06_final
2023-02-07 10:25:27	ga_ls8c_ard_3-2-1_101076_2023-02-07_final
2023-02-07 10:27:02	ga_ls8c_ard_3-2-1_101080_2023-02-07_final
2023-02-11 10:01:05	ga_ls8c_ard_3-2-1_097077_2023-02-11_final
2023-02-11 10:01:29	ga_ls8c_ard_3-2-1_097078_2023-02-11_final
2023-02-11 10:01:53	ga_ls8c_ard_3-2-1_097079_2023-02-11_final
2023-02-12 10:45:07	ga_ls8c_ard_3-2-1_104079_2023-02-12_final
2023-02-13 09:51:05	ga_ls8c_ard_3-2-1_095083_2023-02-13_final
2023-02-13 11:30:22	ga_ls8c_ard_3-2-1_111084_2023-02-13_final
2023-02-15 09:38:42	ga_ls8c_ard_3-2-1_093083_2023-02-15_final
2023-02-17 11:04:00	ga_ls8c_ard_3-2-1_107080_2023-02-17_final
2023-02-20 11:36:02	ga_ls8c_ard_3-2-1_112083_2023-02-20_final
2023-02-21 10:38:23	ga_ls8c_ard_3-2-1_103078_2023-02-21_final
2023-02-22 09:43:33	ga_ls8c_ard_3-2-1_094080_2023-02-22_final
2023-02-23 10:27:11	ga_ls8c_ard_3-2-1_101081_2023-02-23_final
2023-02-24 11:10:49	ga_ls8c_ard_3-2-1_108082_2023-02-24_final
2023-02-26 09:18:45	ga_ls8c_ard_3-2-1_090080_2023-02-25_final
2023-02-26 09:19:57	ga_ls8c_ard_3-2-1_090083_2023-02-25_final
2023-02-26 10:56:02	ga_ls8c_ard_3-2-1_106076_2023-02-26_final
2023-02-28 10:41:17	ga_ls8c_ard_3-2-1_104070_2023-02-28_final
2023-02-28 10:44:29	ga_ls8c_ard_3-2-1_104078_2023-02-28_final
2023-03-01 09:47:15	ga_ls8c_ard_3-2-1_095074_2023-03-01_final
2023-03-01 09:49:39	ga_ls8c_ard_3-2-1_095080_2023-03-01_final
2023-03-01 11:26:56	ga_ls8c_ard_3-2-1_111076_2023-03-01_final
2023-03-01 11:27:44	ga_ls8c_ard_3-2-1_111078_2023-03-01_final
2023-03-01 11:28:08	ga_ls8c_ard_3-2-1_111079_2023-03-01_final
2023-03-02 10:28:55	ga_ls8c_ard_3-2-1_102070_2023-03-02_final
2023-03-05 09:24:06	ga_ls8c_ard_3-2-1_091078_2023-03-04_final
2023-03-05 11:03:47	ga_ls8c_ard_3-2-1_107080_2023-03-05_final
2023-03-08 11:31:51	ga_ls8c_ard_3-2-1_112073_2023-03-08_final
2023-03-08 11:33:51	ga_ls8c_ard_3-2-1_112078_2023-03-08_final
2023-03-09 10:35:25	ga_ls8c_ard_3-2-1_103071_2023-03-09_final
2023-03-09 10:37:49	ga_ls8c_ard_3-2-1_103077_2023-03-09_final
2023-03-14 09:18:40	ga_ls8c_ard_3-2-1_090080_2023-03-13_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