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
2018-05-24 11:11:50	ga_ls8c_ard_3-0-0_109072_2018-05-24_final
2018-05-25 10:16:11	ga_ls8c_ard_3-0-0_100072_2018-05-25_final
2018-06-07 09:45:12	ga_ls8c_ard_3-0-0_095072_2018-06-07_final
2018-06-07 09:45:36	ga_ls8c_ard_3-0-0_095073_2018-06-07_final
2018-06-07 11:24:05	ga_ls8c_ard_3-0-0_111072_2018-06-07_final
2018-06-07 11:24:29	ga_ls8c_ard_3-0-0_111073_2018-06-07_final
2018-06-08 10:28:28	ga_ls8c_ard_3-0-0_102072_2018-06-08_final
2018-06-08 10:28:52	ga_ls8c_ard_3-0-0_102073_2018-06-08_final
2018-06-09 09:32:51	ga_ls8c_ard_3-0-0_093072_2018-06-09_final
2018-06-09 09:33:15	ga_ls8c_ard_3-0-0_093073_2018-06-09_final
2018-06-09 11:11:45	ga_ls8c_ard_3-0-0_109072_2018-06-09_final
2018-06-09 11:12:09	ga_ls8c_ard_3-0-0_109073_2018-06-09_final
2018-06-10 10:16:08	ga_ls8c_ard_3-0-0_100072_2018-06-10_final
2018-06-10 10:16:32	ga_ls8c_ard_3-0-0_100073_2018-06-10_final
2018-08-10 09:45:47	ga_ls8c_ard_3-0-0_095072_2018-08-10_final
2018-08-10 09:46:11	ga_ls8c_ard_3-0-0_095073_2018-08-10_final
2018-08-10 11:24:40	ga_ls8c_ard_3-0-0_111072_2018-08-10_final
2018-08-10 11:25:04	ga_ls8c_ard_3-0-0_111073_2018-08-10_final
2018-08-11 10:29:04	ga_ls8c_ard_3-0-0_102072_2018-08-11_final
2018-08-11 10:29:27	ga_ls8c_ard_3-0-0_102073_2018-08-11_final
2018-08-12 09:33:27	ga_ls8c_ard_3-0-0_093072_2018-08-12_final
2018-08-12 09:33:51	ga_ls8c_ard_3-0-0_093073_2018-08-12_final
2018-08-12 11:12:20	ga_ls8c_ard_3-0-0_109072_2018-08-12_final
2018-08-12 11:12:44	ga_ls8c_ard_3-0-0_109073_2018-08-12_final
2018-08-13 10:16:43	ga_ls8c_ard_3-0-0_100072_2018-08-13_final
2018-08-28 11:12:27	ga_ls8c_ard_3-0-0_109072_2018-08-28_final
2018-08-28 11:12:51	ga_ls8c_ard_3-0-0_109073_2018-08-28_final
2018-08-29 10:16:50	ga_ls8c_ard_3-0-0_100072_2018-08-29_final
2018-08-29 10:17:14	ga_ls8c_ard_3-0-0_100073_2018-08-29_final
2018-09-16 10:04:34	ga_ls8c_ard_3-0-0_098072_2018-09-16_final
2018-09-16 10:04:58	ga_ls8c_ard_3-0-0_098073_2018-09-16_final
2018-09-17 10:47:50	ga_ls8c_ard_3-0-0_105072_2018-09-17_final
2018-09-17 10:48:14	ga_ls8c_ard_3-0-0_105073_2018-09-17_final
2018-09-18 09:52:13	ga_ls8c_ard_3-0-0_096072_2018-09-18_final
2018-09-18 11:31:06	ga_ls8c_ard_3-0-0_112072_2018-09-18_final
2018-09-18 11:31:30	ga_ls8c_ard_3-0-0_112073_2018-09-18_final
2018-09-19 10:35:29	ga_ls8c_ard_3-0-0_103072_2018-09-19_final
2018-09-20 09:39:52	ga_ls8c_ard_3-0-0_094072_2018-09-20_final
2018-09-20 09:40:16	ga_ls8c_ard_3-0-0_094073_2018-09-20_final
2018-09-20 11:18:45	ga_ls8c_ard_3-0-0_110072_2018-09-20_final
2018-09-20 11:19:09	ga_ls8c_ard_3-0-0_110073_2018-09-20_final
2018-09-21 10:23:08	ga_ls8c_ard_3-1-0_101072_2018-09-21_final
2018-09-21 10:23:32	ga_ls8c_ard_3-0-0_101073_2018-09-21_final
2018-10-04 09:52:21	ga_ls8c_ard_3-0-0_096072_2018-10-04_final
2018-10-04 11:31:14	ga_ls8c_ard_3-0-0_112072_2018-10-04_final
2018-10-04 11:31:38	ga_ls8c_ard_3-0-0_112073_2018-10-04_final
2018-10-05 10:35:37	ga_ls8c_ard_3-0-0_103072_2018-10-05_final
2018-10-05 10:36:01	ga_ls8c_ard_3-0-0_103073_2018-10-05_final
2018-10-06 09:40:00	ga_ls8c_ard_3-0-0_094072_2018-10-06_final
2018-10-06 09:40:24	ga_ls8c_ard_3-0-0_094073_2018-10-06_final
2018-10-06 11:18:53	ga_ls8c_ard_3-0-0_110072_2018-10-06_final
2018-10-06 11:19:17	ga_ls8c_ard_3-0-0_110073_2018-10-06_final
2018-10-07 10:23:16	ga_ls8c_ard_3-1-0_101072_2018-10-07_final
2018-10-07 10:23:40	ga_ls8c_ard_3-0-0_101073_2018-10-07_final
2018-11-21 09:52:31	ga_ls8c_ard_3-0-0_096072_2018-11-21_final
2018-11-21 11:31:24	ga_ls8c_ard_3-0-0_112072_2018-11-21_final
2018-11-22 10:35:47	ga_ls8c_ard_3-0-0_103072_2018-11-22_final
2018-11-23 09:40:09	ga_ls8c_ard_3-0-0_094072_2018-11-23_final
2018-11-23 09:40:33	ga_ls8c_ard_3-0-0_094073_2018-11-23_final
2018-11-23 11:19:02	ga_ls8c_ard_3-0-0_110072_2018-11-23_final
2018-11-24 10:23:25	ga_ls8c_ard_3-1-0_101072_2018-11-24_final
2018-11-24 10:23:49	ga_ls8c_ard_3-0-0_101073_2018-11-24_final
2018-12-07 09:52:29	ga_ls8c_ard_3-0-0_096072_2018-12-07_final
2018-12-07 11:31:22	ga_ls8c_ard_3-0-0_112072_2018-12-07_final
2018-12-08 10:35:44	ga_ls8c_ard_3-0-0_103072_2018-12-08_final
2018-12-08 10:36:08	ga_ls8c_ard_3-0-0_103073_2018-12-08_final
2018-12-09 09:40:07	ga_ls8c_ard_3-0-0_094072_2018-12-09_final
2018-12-09 11:19:00	ga_ls8c_ard_3-0-0_110072_2018-12-09_final
2018-12-10 10:23:22	ga_ls8c_ard_3-0-0_101072_2018-12-10_final
2018-12-25 09:40:06	ga_ls8c_ard_3-0-0_094072_2018-12-25_final
2018-12-25 11:18:59	ga_ls8c_ard_3-0-0_110072_2018-12-25_final
2018-12-26 10:23:22	ga_ls8c_ard_3-1-0_101072_2018-12-26_final
2019-01-06 10:04:48	ga_ls8c_ard_3-0-0_098072_2019-01-06_final
2019-01-06 10:05:12	ga_ls8c_ard_3-0-0_098073_2019-01-06_final
2019-01-07 10:48:04	ga_ls8c_ard_3-0-0_105072_2019-01-07_final
2023-08-23 10:42:01	ga_ls8c_ard_3-2-1_104072_2023-08-23_final
2023-08-23 10:42:25	ga_ls8c_ard_3-2-1_104073_2023-08-23_final
2023-08-24 09:46:24	ga_ls8c_ard_3-2-1_095072_2023-08-24_final
2023-08-24 11:25:17	ga_ls8c_ard_3-2-1_111072_2023-08-24_final
2023-08-26 11:12:56	ga_ls8c_ard_3-2-1_109072_2023-08-26_final
2023-08-26 11:13:19	ga_ls8c_ard_3-2-1_109073_2023-08-26_final
2023-08-27 10:17:18	ga_ls8c_ard_3-2-1_100072_2023-08-27_final
2023-08-27 10:17:42	ga_ls8c_ard_3-2-1_100073_2023-08-27_final
2023-08-28 09:21:41	ga_ls8c_ard_3-2-1_091072_2023-08-27_final
2023-08-28 09:22:05	ga_ls8c_ard_3-2-1_091073_2023-08-27_final
2023-08-28 11:00:34	ga_ls8c_ard_3-2-1_107072_2023-08-28_final
2023-08-28 11:00:58	ga_ls8c_ard_3-2-1_107073_2023-08-28_final
2023-08-29 10:04:57	ga_ls8c_ard_3-2-1_098072_2023-08-29_final
2023-08-29 10:05:21	ga_ls8c_ard_3-2-1_098073_2023-08-29_final
2023-08-30 10:48:12	ga_ls8c_ard_3-2-1_105072_2023-08-30_final
2023-08-31 09:52:35	ga_ls8c_ard_3-2-1_096072_2023-08-31_final
2023-08-31 11:31:28	ga_ls8c_ard_3-2-1_112072_2023-08-31_final
2023-08-31 11:31:52	ga_ls8c_ard_3-2-1_112073_2023-08-31_final
2023-09-01 10:35:50	ga_ls8c_ard_3-2-1_103072_2023-09-01_final
2023-09-04 09:27:50	ga_ls8c_ard_3-2-1_092072_2023-09-03_final
2023-09-04 11:06:43	ga_ls8c_ard_3-2-1_108072_2023-09-04_final
2023-09-05 10:11:06	ga_ls8c_ard_3-2-1_099072_2023-09-05_final
2023-09-05 10:11:30	ga_ls8c_ard_3-2-1_099073_2023-09-05_final
2023-09-07 09:58:44	ga_ls8c_ard_3-2-1_097072_2023-09-07_final
2023-09-07 11:37:37	ga_ls8c_ard_3-2-1_113072_2023-09-07_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