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 09:29:42	ga_ls8c_ard_3-0-0_092077_2017-07-16_final
2017-07-17 09:30:06	ga_ls8c_ard_3-0-0_092078_2017-07-17_final
2017-07-17 11:08:35	ga_ls8c_ard_3-0-0_108077_2017-07-17_final
2017-07-17 11:08:59	ga_ls8c_ard_3-0-0_108078_2017-07-17_final
2017-07-18 10:12:58	ga_ls8c_ard_3-0-0_099077_2017-07-18_final
2017-07-18 10:13:22	ga_ls8c_ard_3-0-0_099078_2017-07-18_final
2017-07-18 11:51:51	ga_ls8c_ard_3-0-0_115077_2017-07-18_final
2017-07-18 11:52:15	ga_ls8c_ard_3-0-0_115078_2017-07-18_final
2017-07-19 09:17:21	ga_ls8c_ard_3-0-0_090077_2017-07-18_final
2017-07-19 09:17:45	ga_ls8c_ard_3-0-0_090078_2017-07-18_final
2017-07-19 10:56:38	ga_ls8c_ard_3-0-0_106078_2017-07-19_final
2017-07-27 10:06:52	ga_ls8c_ard_3-1-0_098077_2017-07-27_final
2017-07-27 10:07:16	ga_ls8c_ard_3-0-0_098078_2017-07-27_final
2017-07-27 11:46:09	ga_ls8c_ard_3-0-0_114078_2017-07-27_final
2017-07-28 09:11:15	ga_ls8c_ard_3-0-0_089077_2017-07-27_final
2017-07-28 09:11:39	ga_ls8c_ard_3-0-0_089078_2017-07-27_final
2017-07-28 10:50:32	ga_ls8c_ard_3-0-0_105078_2017-07-28_final
2017-07-29 09:54:31	ga_ls8c_ard_3-0-0_096077_2017-07-29_final
2017-07-29 09:54:55	ga_ls8c_ard_3-0-0_096078_2017-07-29_final
2017-07-29 11:33:24	ga_ls8c_ard_3-0-0_112077_2017-07-29_final
2017-07-29 11:33:48	ga_ls8c_ard_3-0-0_112078_2017-07-29_final
2021-09-29 10:25:49	ga_ls8c_ard_3-2-0_101077_2021-09-29_final
2021-09-30 09:30:36	ga_ls8c_ard_3-2-0_092078_2021-09-30_final
2021-10-09 09:24:05	ga_ls8c_ard_3-2-0_091077_2021-10-08_final
2021-10-09 09:24:29	ga_ls8c_ard_3-2-0_091078_2021-10-08_final
2021-10-09 11:02:58	ga_ls8c_ard_3-2-0_107077_2021-10-09_final
2021-10-09 11:03:22	ga_ls8c_ard_3-2-0_107078_2021-10-09_final
2021-10-10 10:07:21	ga_ls8c_ard_3-2-0_098077_2021-10-10_final
2021-10-10 10:07:45	ga_ls8c_ard_3-2-0_098078_2021-10-10_final
2021-10-10 11:46:38	ga_ls8c_ard_3-2-0_114078_2021-10-10_final
2021-10-11 09:11:44	ga_ls8c_ard_3-2-0_089077_2021-10-10_final
2021-10-11 09:12:07	ga_ls8c_ard_3-2-0_089078_2021-10-10_final
2021-10-11 10:50:37	ga_ls8c_ard_3-2-0_105077_2021-10-11_final
2021-10-11 10:51:00	ga_ls8c_ard_3-2-0_105078_2021-10-11_final
2021-10-14 09:42:38	ga_ls8c_ard_3-2-0_094077_2021-10-14_final
2021-10-14 09:43:02	ga_ls8c_ard_3-2-0_094078_2021-10-14_final
2021-10-14 11:21:31	ga_ls8c_ard_3-2-0_110077_2021-10-14_final
2021-10-14 11:21:55	ga_ls8c_ard_3-2-0_110078_2021-10-14_final
2021-10-15 10:25:54	ga_ls8c_ard_3-2-0_101077_2021-10-15_final
2021-10-15 10:26:18	ga_ls8c_ard_3-2-0_101078_2021-10-15_final
2023-07-13 09:11:01	ga_ls8c_ard_3-2-1_089077_2023-07-12_final
2023-07-13 09:11:25	ga_ls8c_ard_3-2-1_089078_2023-07-12_final
2023-07-13 10:50:18	ga_ls8c_ard_3-2-1_105078_2023-07-13_final
2023-07-14 09:54:17	ga_ls8c_ard_3-2-1_096077_2023-07-14_final
2023-07-14 09:54:41	ga_ls8c_ard_3-2-1_096078_2023-07-14_final
2023-07-14 11:33:10	ga_ls8c_ard_3-2-1_112077_2023-07-14_final
2023-07-14 11:33:34	ga_ls8c_ard_3-2-1_112078_2023-07-14_final
2023-07-15 10:37:33	ga_ls8c_ard_3-2-1_103077_2023-07-15_final
2023-07-15 10:37:57	ga_ls8c_ard_3-2-1_103078_2023-07-15_final
2023-07-21 10:00:27	ga_ls8c_ard_3-2-1_097077_2023-07-21_final
2023-07-21 10:00:51	ga_ls8c_ard_3-2-1_097078_2023-07-21_final
2023-07-21 11:39:21	ga_ls8c_ard_3-2-1_113077_2023-07-21_final
2023-07-21 11:39:45	ga_ls8c_ard_3-2-1_113078_2023-07-21_final
2023-07-22 10:44:08	ga_ls8c_ard_3-2-1_104078_2023-07-22_final
2023-07-23 09:48:08	ga_ls8c_ard_3-2-1_095077_2023-07-23_final
2023-07-23 09:48:32	ga_ls8c_ard_3-2-1_095078_2023-07-23_final
2023-07-23 11:27:01	ga_ls8c_ard_3-2-1_111077_2023-07-23_final
2023-07-23 11:27:25	ga_ls8c_ard_3-2-1_111078_2023-07-23_final
2023-07-24 10:31:49	ga_ls8c_ard_3-2-1_102078_2023-07-24_final
2023-07-25 09:35:48	ga_ls8c_ard_3-2-1_093077_2023-07-25_final
2023-07-25 09:36:12	ga_ls8c_ard_3-2-1_093078_2023-07-25_final
2023-07-25 11:15:05	ga_ls8c_ard_3-2-1_109078_2023-07-25_final
2023-07-26 10:19:05	ga_ls8c_ard_3-2-1_100077_2023-07-26_final
2023-07-26 10:19:29	ga_ls8c_ard_3-2-1_100078_2023-07-26_final
2023-07-26 11:57:58	ga_ls8c_ard_3-2-1_116077_2023-07-26_final
2023-07-26 11:58:22	ga_ls8c_ard_3-2-1_116078_2023-07-26_final
2023-09-10 10:31:40	ga_ls8c_ard_3-2-1_102077_2023-09-10_final
2023-09-10 10:32:04	ga_ls8c_ard_3-2-1_102078_2023-09-10_final
2023-09-11 09:36:03	ga_ls8c_ard_3-2-1_093077_2023-09-11_final
2023-09-11 09:36:27	ga_ls8c_ard_3-2-1_093078_2023-09-11_final
2023-09-11 11:14:56	ga_ls8c_ard_3-2-1_109077_2023-09-11_final
2023-09-11 11:15:20	ga_ls8c_ard_3-2-1_109078_2023-09-11_final
2023-09-12 10:19:20	ga_ls8c_ard_3-2-1_100077_2023-09-12_final
2023-09-12 10:19:44	ga_ls8c_ard_3-2-1_100078_2023-09-12_final
2023-09-12 11:58:13	ga_ls8c_ard_3-2-1_116077_2023-09-12_final
2023-09-12 11:58:37	ga_ls8c_ard_3-2-1_116078_2023-09-12_final
2023-09-13 09:23:43	ga_ls8c_ard_3-2-1_091077_2023-09-12_final
2023-09-13 09:24:07	ga_ls8c_ard_3-2-1_091078_2023-09-12_final
2023-09-13 11:02:36	ga_ls8c_ard_3-2-1_107077_2023-09-13_final
2023-09-13 11:03:00	ga_ls8c_ard_3-2-1_107078_2023-09-13_final
2023-10-12 10:31:50	ga_ls8c_ard_3-2-1_102077_2023-10-12_final
2023-10-12 10:32:13	ga_ls8c_ard_3-2-1_102078_2023-10-12_final
2023-10-13 09:36:36	ga_ls8c_ard_3-2-1_093078_2023-10-13_final
2023-10-13 11:15:05	ga_ls8c_ard_3-2-1_109077_2023-10-13_final
2023-10-13 11:15:29	ga_ls8c_ard_3-2-1_109078_2023-10-13_final
2023-10-14 10:19:28	ga_ls8c_ard_3-2-1_100077_2023-10-14_final
2023-10-14 10:19:28	ga_ls8c_ard_3-2-1_100077_2023-10-14_nrt
2023-10-14 10:19:52	ga_ls8c_ard_3-2-1_100078_2023-10-14_final
2023-10-14 10:19:52	ga_ls8c_ard_3-2-1_100078_2023-10-14_nrt
2023-10-14 11:58:21	ga_ls8c_ard_3-2-1_116077_2023-10-14_final
2023-10-14 11:58:21	ga_ls8c_ard_3-2-1_116077_2023-10-14_nrt
2023-10-14 11:58:45	ga_ls8c_ard_3-2-1_116078_2023-10-14_final
2023-10-14 11:58:45	ga_ls8c_ard_3-2-1_116078_2023-10-14_nrt
2023-10-15 09:23:51	ga_ls8c_ard_3-2-1_091077_2023-10-14_final
2023-10-15 09:23:51	ga_ls8c_ard_3-2-1_091077_2023-10-14_nrt
2023-10-15 09:24:15	ga_ls8c_ard_3-2-1_091078_2023-10-14_final
2023-10-15 09:24:15	ga_ls8c_ard_3-2-1_091078_2023-10-14_nrt
2023-10-15 11:02:44	ga_ls8c_ard_3-2-1_107077_2023-10-15_final
2023-10-15 11:02:44	ga_ls8c_ard_3-2-1_107077_2023-10-15_nrt
2023-10-15 11:03:07	ga_ls8c_ard_3-2-1_107078_2023-10-15_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