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
2017-07-17 09:28:30	ga_ls8c_ard_3-0-0_092074_2017-07-16_final
2017-07-17 09:28:54	ga_ls8c_ard_3-0-0_092075_2017-07-16_final
2017-07-17 11:07:23	ga_ls8c_ard_3-0-0_108074_2017-07-17_final
2017-07-17 11:07:47	ga_ls8c_ard_3-0-0_108075_2017-07-17_final
2017-07-18 10:11:46	ga_ls8c_ard_3-0-0_099074_2017-07-18_final
2017-07-18 10:12:10	ga_ls8c_ard_3-0-0_099075_2017-07-18_final
2017-07-18 11:50:39	ga_ls8c_ard_3-0-0_115074_2017-07-18_final
2017-07-18 11:51:03	ga_ls8c_ard_3-0-0_115075_2017-07-18_final
2017-07-19 09:16:09	ga_ls8c_ard_3-0-0_090074_2017-07-18_final
2017-07-19 09:16:33	ga_ls8c_ard_3-0-0_090075_2017-07-18_final
2017-07-19 10:55:02	ga_ls8c_ard_3-0-0_106074_2017-07-19_final
2017-07-19 10:55:26	ga_ls8c_ard_3-0-0_106075_2017-07-19_final
2017-07-27 10:05:40	ga_ls8c_ard_3-0-0_098074_2017-07-27_final
2017-07-27 10:06:04	ga_ls8c_ard_3-0-0_098075_2017-07-27_final
2017-07-27 11:44:33	ga_ls8c_ard_3-0-0_114074_2017-07-27_final
2017-07-27 11:44:57	ga_ls8c_ard_3-0-0_114075_2017-07-27_final
2017-07-28 09:10:03	ga_ls8c_ard_3-0-0_089074_2017-07-27_final
2017-07-28 09:10:27	ga_ls8c_ard_3-0-0_089075_2017-07-27_final
2017-07-28 10:48:56	ga_ls8c_ard_3-0-0_105074_2017-07-28_final
2017-07-28 10:49:20	ga_ls8c_ard_3-0-0_105075_2017-07-28_final
2017-07-29 09:53:19	ga_ls8c_ard_3-0-0_096074_2017-07-29_final
2017-07-29 09:53:43	ga_ls8c_ard_3-0-0_096075_2017-07-29_final
2017-07-29 11:32:12	ga_ls8c_ard_3-0-0_112074_2017-07-29_final
2017-07-29 11:32:36	ga_ls8c_ard_3-0-0_112075_2017-07-29_final
2021-10-09 09:22:53	ga_ls8c_ard_3-2-0_091074_2021-10-08_final
2021-10-09 09:23:17	ga_ls8c_ard_3-2-0_091075_2021-10-08_final
2021-10-09 11:01:46	ga_ls8c_ard_3-2-0_107074_2021-10-09_final
2021-10-09 11:02:10	ga_ls8c_ard_3-2-0_107075_2021-10-09_final
2021-10-10 10:06:09	ga_ls8c_ard_3-2-0_098074_2021-10-10_final
2021-10-10 10:06:33	ga_ls8c_ard_3-2-0_098075_2021-10-10_final
2021-10-10 11:45:02	ga_ls8c_ard_3-2-0_114074_2021-10-10_final
2021-10-10 11:45:26	ga_ls8c_ard_3-2-0_114075_2021-10-10_final
2021-10-11 09:10:32	ga_ls8c_ard_3-2-0_089074_2021-10-10_final
2021-10-11 09:10:56	ga_ls8c_ard_3-2-0_089075_2021-10-10_final
2021-10-11 10:49:25	ga_ls8c_ard_3-2-0_105074_2021-10-11_final
2021-10-11 10:49:49	ga_ls8c_ard_3-2-0_105075_2021-10-11_final
2021-10-14 09:41:26	ga_ls8c_ard_3-2-0_094074_2021-10-14_final
2021-10-14 09:41:50	ga_ls8c_ard_3-2-0_094075_2021-10-14_final
2021-10-14 11:20:19	ga_ls8c_ard_3-2-0_110074_2021-10-14_final
2021-10-14 11:20:43	ga_ls8c_ard_3-2-0_110075_2021-10-14_final
2021-10-15 10:24:42	ga_ls8c_ard_3-2-0_101074_2021-10-15_final
2021-10-15 10:25:06	ga_ls8c_ard_3-2-0_101075_2021-10-15_final
2023-07-13 09:09:49	ga_ls8c_ard_3-2-1_089074_2023-07-12_final
2023-07-13 09:10:13	ga_ls8c_ard_3-2-1_089075_2023-07-12_final
2023-07-13 10:48:42	ga_ls8c_ard_3-2-1_105074_2023-07-13_final
2023-07-13 10:49:06	ga_ls8c_ard_3-2-1_105075_2023-07-13_final
2023-07-14 09:53:05	ga_ls8c_ard_3-2-1_096074_2023-07-14_final
2023-07-14 09:53:29	ga_ls8c_ard_3-2-1_096075_2023-07-14_final
2023-07-14 11:31:58	ga_ls8c_ard_3-2-1_112074_2023-07-14_final
2023-07-14 11:32:22	ga_ls8c_ard_3-2-1_112075_2023-07-14_final
2023-07-15 10:36:21	ga_ls8c_ard_3-2-1_103074_2023-07-15_final
2023-07-15 10:36:45	ga_ls8c_ard_3-2-1_103075_2023-07-15_final
2023-07-21 09:59:16	ga_ls8c_ard_3-2-1_097074_2023-07-21_final
2023-07-21 09:59:40	ga_ls8c_ard_3-2-1_097075_2023-07-21_final
2023-07-21 11:38:09	ga_ls8c_ard_3-2-1_113074_2023-07-21_final
2023-07-21 11:38:33	ga_ls8c_ard_3-2-1_113075_2023-07-21_final
2023-07-22 10:42:32	ga_ls8c_ard_3-2-1_104074_2023-07-22_final
2023-07-22 10:42:56	ga_ls8c_ard_3-2-1_104075_2023-07-22_final
2023-07-23 09:46:56	ga_ls8c_ard_3-2-1_095074_2023-07-23_final
2023-07-23 09:47:20	ga_ls8c_ard_3-2-1_095075_2023-07-23_final
2023-07-23 11:25:49	ga_ls8c_ard_3-2-1_111074_2023-07-23_final
2023-07-23 11:26:13	ga_ls8c_ard_3-2-1_111075_2023-07-23_final
2023-07-24 10:30:13	ga_ls8c_ard_3-2-1_102074_2023-07-24_final
2023-07-24 10:30:37	ga_ls8c_ard_3-2-1_102075_2023-07-24_final
2023-07-25 09:34:36	ga_ls8c_ard_3-2-1_093074_2023-07-25_final
2023-07-25 09:35:00	ga_ls8c_ard_3-2-1_093075_2023-07-25_final
2023-07-25 11:13:29	ga_ls8c_ard_3-2-1_109074_2023-07-25_final
2023-07-25 11:13:53	ga_ls8c_ard_3-2-1_109075_2023-07-25_final
2023-07-26 10:17:53	ga_ls8c_ard_3-2-1_100074_2023-07-26_final
2023-07-26 10:18:17	ga_ls8c_ard_3-2-1_100075_2023-07-26_final
2023-07-26 11:57:10	ga_ls8c_ard_3-2-1_116075_2023-07-26_final
2023-09-10 10:30:28	ga_ls8c_ard_3-2-1_102074_2023-09-10_final
2023-09-10 10:30:52	ga_ls8c_ard_3-2-1_102075_2023-09-10_final
2023-09-11 09:34:52	ga_ls8c_ard_3-2-1_093074_2023-09-11_final
2023-09-11 09:35:15	ga_ls8c_ard_3-2-1_093075_2023-09-11_final
2023-09-11 11:13:45	ga_ls8c_ard_3-2-1_109074_2023-09-11_final
2023-09-11 11:14:09	ga_ls8c_ard_3-2-1_109075_2023-09-11_final
2023-09-12 10:18:08	ga_ls8c_ard_3-2-1_100074_2023-09-12_final
2023-09-12 10:18:32	ga_ls8c_ard_3-2-1_100075_2023-09-12_final
2023-09-12 11:57:25	ga_ls8c_ard_3-2-1_116075_2023-09-12_final
2023-09-13 09:22:31	ga_ls8c_ard_3-2-1_091074_2023-09-12_final
2023-09-13 09:22:55	ga_ls8c_ard_3-2-1_091075_2023-09-12_final
2023-09-13 11:01:24	ga_ls8c_ard_3-2-1_107074_2023-09-13_final
2023-09-13 11:01:48	ga_ls8c_ard_3-2-1_107075_2023-09-13_final
2023-10-12 10:30:38	ga_ls8c_ard_3-2-1_102074_2023-10-12_final
2023-10-12 10:31:02	ga_ls8c_ard_3-2-1_102075_2023-10-12_final
2023-10-13 09:35:01	ga_ls8c_ard_3-2-1_093074_2023-10-13_final
2023-10-13 09:35:24	ga_ls8c_ard_3-2-1_093075_2023-10-13_final
2023-10-13 11:14:17	ga_ls8c_ard_3-2-1_109075_2023-10-13_final
2023-10-14 10:18:16	ga_ls8c_ard_3-2-1_100074_2023-10-14_final
2023-10-14 10:18:16	ga_ls8c_ard_3-2-1_100074_2023-10-14_nrt
2023-10-14 10:18:40	ga_ls8c_ard_3-2-1_100075_2023-10-14_final
2023-10-14 10:18:40	ga_ls8c_ard_3-2-1_100075_2023-10-14_nrt
2023-10-14 11:57:33	ga_ls8c_ard_3-2-1_116075_2023-10-14_final
2023-10-15 09:22:39	ga_ls8c_ard_3-2-1_091074_2023-10-14_final
2023-10-15 09:22:39	ga_ls8c_ard_3-2-1_091074_2023-10-14_nrt
2023-10-15 09:23:03	ga_ls8c_ard_3-2-1_091075_2023-10-14_final
2023-10-15 09:23:03	ga_ls8c_ard_3-2-1_091075_2023-10-14_nrt
2023-10-15 11:01:32	ga_ls8c_ard_3-2-1_107074_2023-10-15_final
2023-10-15 11:01:32	ga_ls8c_ard_3-2-1_107074_2023-10-15_nrt

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