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
2020-10-21 08:42:45	ga_ls8c_ard_3-2-1_084082_2020-10-20_final
2021-07-21 12:37:25	ga_ls8c_ard_3-2-1_123067_2021-07-21_final
2022-05-19 09:38:23	ga_ls8c_ard_3-2-1_093083_2022-05-19_final
2022-06-27 09:44:27	ga_ls8c_ard_3-2-1_094082_2022-06-27_final
2022-07-08 11:02:24	ga_ls8c_ard_3-2-1_107076_2022-07-08_final
2022-07-27 09:52:09	ga_ls8c_ard_3-2-1_096070_2022-07-27_final
2022-07-30 10:27:05	ga_ls8c_ard_3-2-1_101080_2022-07-30_final
2022-08-01 10:13:09	ga_ls8c_ard_3-2-1_099076_2022-08-01_final
2022-08-02 10:55:13	ga_ls8c_ard_3-2-1_106073_2022-08-02_final
2022-08-03 10:00:00	ga_ls8c_ard_3-2-1_097074_2022-08-03_final
2022-08-11 09:13:49	ga_ls8c_ard_3-2-1_089082_2022-08-10_final
2022-08-12 09:57:29	ga_ls8c_ard_3-2-1_096083_2022-08-12_final
2022-08-14 11:24:25	ga_ls8c_ard_3-2-1_110084_2022-08-14_final
2022-08-16 11:08:04	ga_ls8c_ard_3-2-1_108074_2022-08-16_final
2022-08-18 10:55:19	ga_ls8c_ard_3-2-1_106073_2022-08-18_final
2022-08-18 10:55:43	ga_ls8c_ard_3-2-1_106074_2022-08-18_final
2022-08-22 10:29:00	ga_ls8c_ard_3-2-1_102069_2022-08-22_final
2022-08-30 11:21:38	ga_ls8c_ard_3-2-1_110077_2022-08-30_final
2022-09-08 11:15:54	ga_ls8c_ard_3-2-1_109078_2022-09-08_final
2022-09-15 11:19:20	ga_ls8c_ard_3-2-1_110071_2022-09-15_final
2022-09-17 11:11:46	ga_ls8c_ard_3-2-1_108083_2022-09-17_final
2022-09-20 09:58:37	ga_ls8c_ard_3-2-1_097070_2022-09-20_final
2022-09-23 10:28:43	ga_ls8c_ard_3-2-1_102068_2022-09-23_final
2022-09-27 11:45:40	ga_ls8c_ard_3-2-1_114075_2022-09-27_final
2022-10-05 09:19:18	ga_ls8c_ard_3-2-1_090080_2022-10-04_final
2022-10-07 10:41:25	ga_ls8c_ard_3-2-1_104069_2022-10-07_final
2022-11-09 11:29:54	ga_ls8c_ard_3-2-1_111082_2022-11-09_final
2022-11-12 10:19:29	ga_ls8c_ard_3-2-1_100076_2022-11-12_final
2022-11-23 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-11-23_final
2022-12-06 11:06:54	ga_ls8c_ard_3-2-1_108071_2022-12-06_final
2022-12-10 10:41:22	ga_ls8c_ard_3-2-1_104069_2022-12-10_final
2022-12-15 11:03:51	ga_ls8c_ard_3-2-1_107079_2022-12-15_final
2022-12-16 10:09:48	ga_ls8c_ard_3-2-1_098083_2022-12-16_final
2022-12-22 09:28:15	ga_ls8c_ard_3-2-1_092072_2022-12-21_final
2022-12-26 10:42:25	ga_ls8c_ard_3-2-1_104072_2022-12-26_final
2022-12-30 10:21:19	ga_ls8c_ard_3-2-1_100081_2022-12-30_final
2023-01-03 11:36:16	ga_ls8c_ard_3-2-1_112083_2023-01-03_final
2023-01-12 09:51:09	ga_ls8c_ard_3-2-1_095083_2023-01-12_final
2023-01-16 11:03:16	ga_ls8c_ard_3-2-1_107078_2023-01-16_final
2023-01-18 10:50:28	ga_ls8c_ard_3-2-1_105077_2023-01-18_final
2023-01-20 10:38:57	ga_ls8c_ard_3-2-1_103079_2023-01-20_final
2023-01-21 09:46:08	ga_ls8c_ard_3-2-1_094086_2023-01-21_final
2023-01-30 11:18:06	ga_ls8c_ard_3-2-1_109084_2023-01-30_final
2023-02-25 10:11:58	ga_ls8c_ard_3-2-1_099074_2023-02-25_final
2023-03-04 11:57:25	ga_ls8c_ard_3-2-1_116075_2023-03-04_final
2023-03-07 09:14:31	ga_ls8c_ard_3-2-1_089085_2023-03-06_final
2023-03-13 11:51:35	ga_ls8c_ard_3-2-1_115076_2023-03-13_final
2023-03-21 09:28:45	ga_ls8c_ard_3-2-1_091090_2023-03-20_final
2023-04-02 11:26:15	ga_ls8c_ard_3-2-1_111075_2023-04-02_final
2023-04-03 10:27:49	ga_ls8c_ard_3-2-1_102068_2023-04-03_final
2023-05-08 11:03:08	ga_ls8c_ard_3-2-1_107080_2023-05-08_final
2023-05-18 09:57:37	ga_ls8c_ard_3-2-1_097071_2023-05-18_final
2023-05-20 09:46:29	ga_ls8c_ard_3-2-1_095074_2023-05-20_final
2023-05-21 10:29:45	ga_ls8c_ard_3-2-1_102074_2023-05-21_final
2023-06-02 09:20:48	ga_ls8c_ard_3-2-1_090087_2023-06-01_final
2023-06-03 10:02:29	ga_ls8c_ard_3-2-1_097083_2023-06-03_final
2023-06-11 10:51:38	ga_ls8c_ard_3-2-1_105082_2023-06-11_final
2023-06-16 11:10:12	ga_ls8c_ard_3-2-1_108082_2023-06-16_final
2023-07-10 10:20:59	ga_ls8c_ard_3-2-1_100082_2023-07-10_final
2023-07-20 12:30:58	ga_ls8c_ard_3-2-1_122067_2023-07-20_final
2023-08-11 11:57:38	ga_ls8c_ard_3-2-1_116076_2023-08-11_final
2023-08-19 11:11:06	ga_ls8c_ard_3-2-1_108083_2023-08-19_final
2023-08-28 11:02:10	ga_ls8c_ard_3-2-1_107076_2023-08-28_final
2023-09-04 11:05:32	ga_ls8c_ard_3-2-1_108069_2023-09-04_final
2023-09-12 11:57:25	ga_ls8c_ard_3-2-1_116075_2023-09-12_final
2023-09-12 11:57:49	ga_ls8c_ard_3-2-1_116076_2023-09-12_final
2023-09-20 09:31:08	ga_ls8c_ard_3-2-1_092080_2023-09-20_final
2023-09-21 10:12:47	ga_ls8c_ard_3-2-1_099076_2023-09-21_final
2023-09-23 10:01:37	ga_ls8c_ard_3-2-1_097079_2023-09-23_final
2023-09-30 11:44:45	ga_ls8c_ard_3-2-1_114074_2023-09-30_final
2023-10-01 10:52:19	ga_ls8c_ard_3-2-1_105082_2023-10-01_final
2023-10-04 11:23:37	ga_ls8c_ard_3-2-1_110083_2023-10-04_final
2023-10-12 10:30:38	ga_ls8c_ard_3-2-1_102074_2023-10-12_final
2023-10-17 10:52:21	ga_ls8c_ard_3-2-1_105082_2023-10-17_final
2023-10-18 09:53:32	ga_ls8c_ard_3-2-1_096074_2023-10-18_final
2023-10-19 10:39:11	ga_ls8c_ard_3-2-1_103080_2023-10-19_final
2023-11-01 11:44:51	ga_ls8c_ard_3-2-1_114074_2023-11-01_final
2023-11-04 10:40:02	ga_ls8c_ard_3-2-1_103082_2023-11-04_final
2023-11-18 10:52:49	ga_ls8c_ard_3-2-1_105083_2023-11-18_final
2023-11-24 11:51:51	ga_ls8c_ard_3-2-1_115076_2023-11-24_final
2023-11-29 10:32:41	ga_ls8c_ard_3-2-1_102079_2023-11-29_final
2023-11-30 09:37:03	ga_ls8c_ard_3-2-1_093079_2023-11-30_final
2023-11-30 11:13:08	ga_ls8c_ard_3-2-1_109072_2023-11-30_final
2023-12-03 10:06:18	ga_ls8c_ard_3-2-1_098075_2023-12-03_final
2023-12-07 09:44:18	ga_ls8c_ard_3-2-1_094082_2023-12-07_final
2023-12-15 10:31:27	ga_ls8c_ard_3-2-1_102076_2023-12-15_final
2023-12-23 09:44:26	ga_ls8c_ard_3-2-1_094082_2023-12-23_final
2024-01-10 11:06:28	ga_ls8c_ard_3-2-1_108071_2024-01-10_final
2024-01-10 11:09:39	ga_ls8c_ard_3-2-1_108079_2024-01-10_final
2024-01-22 11:34:20	ga_ls8c_ard_3-2-1_112079_2024-01-22_final
2024-02-04 09:26:10	ga_ls8c_ard_3-2-1_091083_2024-02-03_final
2024-02-09 11:18:25	ga_ls8c_ard_3-2-1_110070_2024-02-09_final
2024-02-19 10:20:10	ga_ls8c_ard_3-2-1_100079_2024-02-19_final
2024-03-01 11:42:01	ga_ls8c_ard_3-2-1_113083_2024-03-01_final
2024-03-10 11:34:07	ga_ls8c_ard_3-2-1_112079_2024-03-10_final
2024-03-11 10:38:06	ga_ls8c_ard_3-2-1_103078_2024-03-11_final
2024-03-19 11:26:16	ga_ls8c_ard_3-2-1_111075_2024-03-19_final
2024-04-01 10:55:12	ga_ls8c_ard_3-2-1_106075_2024-04-01_final
2024-04-02 11:42:03	ga_ls8c_ard_3-2-1_113084_2024-04-02_final
2024-04-04 09:51:12	ga_ls8c_ard_3-2-1_095085_2024-04-04_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years