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
2022-07-26 10:48:10	ga_ls8c_ard_3-2-1_105071_2022-07-26_final
2022-07-27 09:52:57	ga_ls8c_ard_3-2-1_096072_2022-07-27_final
2022-07-27 09:54:09	ga_ls8c_ard_3-2-1_096075_2022-07-27_final
2022-07-28 10:37:02	ga_ls8c_ard_3-2-1_103074_2022-07-28_final
2022-07-28 10:39:01	ga_ls8c_ard_3-2-1_103079_2022-07-28_final
2022-07-29 11:22:18	ga_ls8c_ard_3-2-1_110079_2022-07-29_final
2022-08-21 09:49:44	ga_ls8c_ard_3-2-1_095079_2022-08-21_final
2022-08-21 11:27:49	ga_ls8c_ard_3-2-1_111077_2022-08-21_final
2022-08-24 10:21:02	ga_ls8c_ard_3-2-1_100080_2022-08-24_final
2022-08-25 09:24:37	ga_ls8c_ard_3-2-1_091078_2022-08-24_final
2022-08-26 11:46:46	ga_ls8c_ard_3-2-1_114078_2022-08-26_final
2022-08-28 09:56:43	ga_ls8c_ard_3-2-1_096081_2022-08-28_final
2022-09-12 10:52:01	ga_ls8c_ard_3-2-1_105080_2022-09-12_final
2022-09-17 11:10:35	ga_ls8c_ard_3-2-1_108080_2022-09-17_final
2022-09-20 11:40:17	ga_ls8c_ard_3-2-1_113077_2022-09-20_final
2022-09-26 09:29:31	ga_ls8c_ard_3-2-1_091090_2022-09-25_final
2022-09-27 10:07:11	ga_ls8c_ard_3-2-1_098076_2022-09-27_final
2022-09-29 11:34:06	ga_ls8c_ard_3-2-1_112077_2022-09-29_final
2022-09-29 11:34:54	ga_ls8c_ard_3-2-1_112079_2022-09-29_final
2022-10-03 09:32:05	ga_ls8c_ard_3-2-1_092081_2022-10-03_final
2022-10-05 10:58:35	ga_ls8c_ard_3-2-1_106081_2022-10-05_final
2022-10-07 10:42:37	ga_ls8c_ard_3-2-1_104072_2022-10-07_final
2022-10-07 10:45:00	ga_ls8c_ard_3-2-1_104078_2022-10-07_final
2022-10-08 11:29:03	ga_ls8c_ard_3-2-1_111080_2022-10-08_final
2022-10-22 11:39:50	ga_ls8c_ard_3-2-1_113076_2022-10-22_final
2022-10-23 10:42:37	ga_ls8c_ard_3-2-1_104072_2022-10-23_final
2022-10-31 11:35:18	ga_ls8c_ard_3-2-1_112080_2022-10-31_final
2022-11-09 09:48:37	ga_ls8c_ard_3-2-1_095076_2022-11-09_final
2022-11-09 09:49:49	ga_ls8c_ard_3-2-1_095079_2022-11-09_final
2022-11-13 11:03:32	ga_ls8c_ard_3-2-1_107078_2022-11-13_final
2022-11-16 09:54:19	ga_ls8c_ard_3-2-1_096075_2022-11-16_final
2022-11-16 11:34:24	ga_ls8c_ard_3-2-1_112078_2022-11-16_final
2022-11-18 09:42:20	ga_ls8c_ard_3-2-1_094076_2022-11-18_final
2022-11-25 09:50:09	ga_ls8c_ard_3-2-1_095080_2022-11-25_final
2022-11-29 11:05:07	ga_ls8c_ard_3-2-1_107082_2022-11-29_final
2022-12-02 11:34:25	ga_ls8c_ard_3-2-1_112078_2022-12-02_final
2022-12-02 11:35:13	ga_ls8c_ard_3-2-1_112080_2022-12-02_final
2022-12-02 11:35:37	ga_ls8c_ard_3-2-1_112081_2022-12-02_final
2022-12-04 11:22:04	ga_ls8c_ard_3-2-1_110078_2022-12-04_final
2022-12-05 10:23:15	ga_ls8c_ard_3-2-1_101070_2022-12-05_final
2022-12-09 10:03:18	ga_ls8c_ard_3-2-1_097082_2022-12-09_final
2022-12-10 10:45:21	ga_ls8c_ard_3-2-1_104079_2022-12-10_final
2022-12-11 11:30:12	ga_ls8c_ard_3-2-1_111083_2022-12-11_final
2022-12-13 09:34:33	ga_ls8c_ard_3-2-1_093072_2022-12-13_final
2022-12-18 09:56:13	ga_ls8c_ard_3-2-1_096080_2022-12-18_final
2022-12-18 11:34:18	ga_ls8c_ard_3-2-1_112078_2022-12-18_final
2022-12-19 10:39:04	ga_ls8c_ard_3-2-1_103079_2022-12-19_final
2022-12-20 09:41:50	ga_ls8c_ard_3-2-1_094075_2022-12-20_final
2022-12-26 10:45:13	ga_ls8c_ard_3-2-1_104079_2022-12-26_final
2022-12-27 09:48:48	ga_ls8c_ard_3-2-1_095077_2022-12-27_final
2022-12-27 09:49:12	ga_ls8c_ard_3-2-1_095078_2022-12-27_final
2022-12-27 09:49:36	ga_ls8c_ard_3-2-1_095079_2022-12-27_final
2023-01-05 11:23:55	ga_ls8c_ard_3-2-1_110083_2023-01-05_final
2023-01-10 11:40:25	ga_ls8c_ard_3-2-1_113078_2023-01-10_final
2023-01-15 11:58:30	ga_ls8c_ard_3-2-1_116077_2023-01-15_final
2023-01-19 09:54:04	ga_ls8c_ard_3-2-1_096075_2023-01-19_final
2023-01-21 09:42:32	ga_ls8c_ard_3-2-1_094077_2023-01-21_final
2023-01-21 09:42:56	ga_ls8c_ard_3-2-1_094078_2023-01-21_final
2023-01-23 09:30:12	ga_ls8c_ard_3-2-1_092077_2023-01-23_final
2023-01-30 09:37:13	ga_ls8c_ard_3-2-1_093079_2023-01-30_final
2023-02-07 10:25:27	ga_ls8c_ard_3-2-1_101076_2023-02-07_final
2023-02-11 10:00:17	ga_ls8c_ard_3-2-1_097075_2023-02-11_final
2023-02-11 10:02:40	ga_ls8c_ard_3-2-1_097081_2023-02-11_final
2023-02-11 10:03:28	ga_ls8c_ard_3-2-1_097083_2023-02-11_final
2023-02-13 11:27:10	ga_ls8c_ard_3-2-1_111076_2023-02-13_final
2023-02-13 11:27:34	ga_ls8c_ard_3-2-1_111077_2023-02-13_final
2023-02-17 11:04:47	ga_ls8c_ard_3-2-1_107082_2023-02-17_final
2023-02-22 11:22:02	ga_ls8c_ard_3-2-1_110079_2023-02-22_final
2023-02-24 11:08:25	ga_ls8c_ard_3-2-1_108076_2023-02-24_final
2023-02-28 10:43:41	ga_ls8c_ard_3-2-1_104076_2023-02-28_final
2023-02-28 10:45:40	ga_ls8c_ard_3-2-1_104081_2023-02-28_final
2023-03-04 10:21:20	ga_ls8c_ard_3-2-1_100082_2023-03-04_final
2023-03-11 10:26:15	ga_ls8c_ard_3-2-1_101079_2023-03-11_final
2023-03-12 09:31:50	ga_ls8c_ard_3-2-1_092082_2023-03-12_final
2023-03-13 10:14:41	ga_ls8c_ard_3-2-1_099081_2023-03-13_final
2023-03-14 10:56:45	ga_ls8c_ard_3-2-1_106078_2023-03-14_final
2023-03-16 10:45:10	ga_ls8c_ard_3-2-1_104080_2023-03-16_final
2023-03-17 09:47:56	ga_ls8c_ard_3-2-1_095076_2023-03-17_final
2023-03-17 11:26:49	ga_ls8c_ard_3-2-1_111076_2023-03-17_final
2023-03-21 09:23:58	ga_ls8c_ard_3-2-1_091078_2023-03-20_final
2023-03-24 09:55:13	ga_ls8c_ard_3-2-1_096079_2023-03-24_final
2023-03-31 10:02:57	ga_ls8c_ard_3-2-1_097083_2023-03-31_final
2023-04-02 09:48:57	ga_ls8c_ard_3-2-1_095079_2023-04-02_final
2023-04-09 11:32:40	ga_ls8c_ard_3-2-1_112076_2023-04-09_final
2023-04-10 10:37:01	ga_ls8c_ard_3-2-1_103076_2023-04-10_final
2023-04-13 09:29:49	ga_ls8c_ard_3-2-1_092078_2023-04-12_final
2023-04-17 10:44:21	ga_ls8c_ard_3-2-1_104079_2023-04-17_final
2023-04-18 09:49:07	ga_ls8c_ard_3-2-1_095080_2023-04-18_final
2023-04-18 11:26:48	ga_ls8c_ard_3-2-1_111077_2023-04-18_final
2023-04-18 11:28:48	ga_ls8c_ard_3-2-1_111082_2023-04-18_final
2023-04-21 10:20:00	ga_ls8c_ard_3-2-1_100080_2023-04-21_final
2023-04-24 10:50:07	ga_ls8c_ard_3-2-1_105078_2023-04-24_final
2023-04-25 11:33:23	ga_ls8c_ard_3-2-1_112078_2023-04-25_final
2023-04-28 10:26:35	ga_ls8c_ard_3-2-1_101081_2023-04-28_final
2023-05-02 11:38:19	ga_ls8c_ard_3-2-1_113075_2023-05-02_final
2023-05-06 09:35:27	ga_ls8c_ard_3-2-1_093077_2023-05-06_final
2023-05-06 09:38:15	ga_ls8c_ard_3-2-1_093084_2023-05-06_final
2023-05-11 09:54:41	ga_ls8c_ard_3-2-1_096079_2023-05-11_final
2023-05-13 09:42:42	ga_ls8c_ard_3-2-1_094080_2023-05-13_final
2023-05-13 11:21:11	ga_ls8c_ard_3-2-1_110079_2023-05-13_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