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
2021-10-05 09:47:35	ga_ls8c_ard_3-2-0_095074_2021-10-05_final
2021-10-10 10:03:21	ga_ls8c_ard_3-2-0_098067_2021-10-10_final
2021-11-08 11:14:07	ga_ls8c_ard_3-2-0_109074_2021-11-08_final
2021-11-22 09:44:45	ga_ls8c_ard_3-2-0_095067_2021-11-22_final
2021-11-24 11:15:16	ga_ls8c_ard_3-2-0_109077_2021-11-24_final
2021-11-27 10:08:06	ga_ls8c_ard_3-2-0_098079_2021-11-27_final
2021-11-27 11:46:59	ga_ls8c_ard_3-2-0_114079_2021-11-27_final
2021-12-12 11:04:31	ga_ls8c_ard_3-2-1_107081_2021-12-12_final
2021-12-18 10:25:25	ga_ls8c_ard_3-2-1_101076_2021-12-18_final
2021-12-24 11:29:59	ga_ls8c_ard_3-2-1_111083_2021-12-24_final
2021-12-26 11:15:12	ga_ls8c_ard_3-2-1_109077_2021-12-26_final
2022-01-23 11:41:01	ga_ls8c_ard_3-2-1_113080_2022-01-23_final
2022-01-24 10:43:47	ga_ls8c_ard_3-2-1_104076_2022-01-24_final
2022-01-25 09:51:21	ga_ls8c_ard_3-2-1_095084_2022-01-25_final
2022-02-01 09:57:07	ga_ls8c_ard_3-2-1_096083_2022-02-01_final
2022-02-01 11:35:36	ga_ls8c_ard_3-2-1_112082_2022-02-01_final
2022-02-05 11:11:16	ga_ls8c_ard_3-2-1_108083_2022-02-05_final
2022-02-06 11:50:56	ga_ls8c_ard_3-2-1_115074_2022-02-06_final
2022-02-19 11:20:44	ga_ls8c_ard_3-2-1_110076_2022-02-19_final
2022-02-24 10:01:35	ga_ls8c_ard_3-2-1_097079_2022-02-24_final
2022-02-27 10:29:17	ga_ls8c_ard_3-2-1_102071_2022-02-27_final
2022-02-28 11:17:20	ga_ls8c_ard_3-2-1_109083_2022-02-28_final
2022-03-04 09:14:55	ga_ls8c_ard_3-2-1_089086_2022-03-03_final
2022-03-09 09:32:14	ga_ls8c_ard_3-2-1_092083_2022-03-09_final
2022-03-09 11:09:31	ga_ls8c_ard_3-2-1_108079_2022-03-09_final
2022-03-12 11:41:12	ga_ls8c_ard_3-2-1_113081_2022-03-12_final
2022-03-14 11:24:50	ga_ls8c_ard_3-2-1_111071_2022-03-14_final
2022-03-17 10:21:36	ga_ls8c_ard_3-2-1_100083_2022-03-17_final
2022-03-21 09:57:38	ga_ls8c_ard_3-2-1_096085_2022-03-21_final
2022-03-23 11:20:32	ga_ls8c_ard_3-2-1_110076_2022-03-23_final
2022-03-30 09:50:08	ga_ls8c_ard_3-2-1_095082_2022-03-30_final
2022-04-01 09:37:22	ga_ls8c_ard_3-2-1_093081_2022-04-01_final
2022-04-02 10:18:38	ga_ls8c_ard_3-2-1_100076_2022-04-02_final
2022-04-03 11:01:54	ga_ls8c_ard_3-2-1_107076_2022-04-03_final
2022-04-05 09:16:16	ga_ls8c_ard_3-2-1_089090_2022-04-04_final
2022-04-13 11:41:04	ga_ls8c_ard_3-2-1_113081_2022-04-13_final
2022-04-26 11:07:19	ga_ls8c_ard_3-2-1_108074_2022-04-26_final
2022-05-01 11:23:29	ga_ls8c_ard_3-2-1_111068_2022-05-01_final
2022-05-04 10:20:43	ga_ls8c_ard_3-2-1_100081_2022-05-04_final
2022-05-19 09:38:23	ga_ls8c_ard_3-2-1_093083_2022-05-19_final
2022-06-06 11:01:50	ga_ls8c_ard_3-2-1_107075_2022-06-06_final
2022-06-10 10:35:10	ga_ls8c_ard_3-2-1_103070_2022-06-10_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
2023-03-07 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
2023-08-11 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
2023-09-04 11:05:32	ga_ls8c_ard_3-2-1_108069_2023-09-04_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years