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
2022-03-22 10:37:18	ga_ls8c_ard_3-2-1_103076_2022-03-22_final
2022-03-23 09:41:16	ga_ls8c_ard_3-2-1_094075_2022-03-23_final
2022-03-23 09:42:51	ga_ls8c_ard_3-2-1_094079_2022-03-23_final
2022-03-24 10:26:30	ga_ls8c_ard_3-2-1_101080_2022-03-24_final
2022-03-25 11:09:21	ga_ls8c_ard_3-2-1_108079_2022-03-25_final
2022-04-03 09:23:49	ga_ls8c_ard_3-2-1_091078_2022-04-02_final
2022-04-04 10:05:53	ga_ls8c_ard_3-2-1_098075_2022-04-04_final
2022-04-06 11:31:38	ga_ls8c_ard_3-2-1_112073_2022-04-06_final
2022-04-07 10:35:14	ga_ls8c_ard_3-2-1_103071_2022-04-07_final
2022-04-10 09:30:04	ga_ls8c_ard_3-2-1_092078_2022-04-10_final
2022-04-11 10:12:08	ga_ls8c_ard_3-2-1_099075_2022-04-11_final
2022-04-13 11:38:41	ga_ls8c_ard_3-2-1_113075_2022-04-13_final
2022-04-13 11:39:52	ga_ls8c_ard_3-2-1_113078_2022-04-13_final
2022-04-14 10:43:27	ga_ls8c_ard_3-2-1_104076_2022-04-14_final
2022-04-15 11:27:31	ga_ls8c_ard_3-2-1_111078_2022-04-15_final
2022-04-16 10:32:18	ga_ls8c_ard_3-2-1_102079_2022-04-16_final
2022-04-20 10:06:22	ga_ls8c_ard_3-2-1_098076_2022-04-20_final
2022-04-24 09:42:25	ga_ls8c_ard_3-2-1_094078_2022-04-24_final
2022-04-24 09:42:49	ga_ls8c_ard_3-2-1_094079_2022-04-24_final
2022-04-24 09:44:25	ga_ls8c_ard_3-2-1_094083_2022-04-24_final
2022-04-29 10:00:31	ga_ls8c_ard_3-2-1_097077_2022-04-29_final
2022-04-30 10:43:23	ga_ls8c_ard_3-2-1_104076_2022-04-30_final
2022-05-08 09:53:39	ga_ls8c_ard_3-2-1_096075_2022-05-08_final
2022-05-08 09:56:27	ga_ls8c_ard_3-2-1_096082_2022-05-08_final
2022-05-09 10:35:20	ga_ls8c_ard_3-2-1_103071_2022-05-09_final
2022-05-09 10:38:07	ga_ls8c_ard_3-2-1_103078_2022-05-09_final
2022-05-11 10:24:35	ga_ls8c_ard_3-2-1_101075_2022-05-11_final
2022-05-12 11:08:15	ga_ls8c_ard_3-2-1_108076_2022-05-12_final
2022-05-15 10:00:41	ga_ls8c_ard_3-2-1_097077_2022-05-15_final
2022-05-16 10:43:09	ga_ls8c_ard_3-2-1_104075_2022-05-16_final
2022-05-19 09:36:47	ga_ls8c_ard_3-2-1_093079_2022-05-19_final
2022-05-24 09:55:43	ga_ls8c_ard_3-2-1_096080_2022-05-24_final
2022-05-25 10:37:22	ga_ls8c_ard_3-2-1_103076_2022-05-25_final
2022-05-25 10:38:10	ga_ls8c_ard_3-2-1_103078_2022-05-25_final
2022-05-26 11:21:26	ga_ls8c_ard_3-2-1_110078_2022-05-26_final
2022-05-29 10:11:52	ga_ls8c_ard_3-2-1_099074_2022-05-29_final
2022-05-31 10:00:44	ga_ls8c_ard_3-2-1_097077_2022-05-31_final
2022-06-01 10:40:49	ga_ls8c_ard_3-2-1_104069_2022-06-01_final
2022-06-09 11:34:22	ga_ls8c_ard_3-2-1_112079_2022-06-09_final
2022-06-11 09:41:33	ga_ls8c_ard_3-2-1_094075_2022-06-11_final
2022-06-11 11:21:38	ga_ls8c_ard_3-2-1_110078_2022-06-11_final
2022-06-15 10:57:21	ga_ls8c_ard_3-2-1_106079_2022-06-15_final
2022-06-16 10:02:32	ga_ls8c_ard_3-2-1_097081_2022-06-16_final
2022-06-16 11:39:02	ga_ls8c_ard_3-2-1_113075_2022-06-16_final
2022-06-23 10:08:46	ga_ls8c_ard_3-2-1_098081_2022-06-23_final
2022-06-25 09:55:36	ga_ls8c_ard_3-2-1_096079_2022-06-25_final
2022-06-25 11:32:54	ga_ls8c_ard_3-2-1_112075_2022-06-25_final
2022-06-29 11:10:11	ga_ls8c_ard_3-2-1_108080_2022-06-29_final
2022-07-03 10:41:04	ga_ls8c_ard_3-2-1_104069_2022-07-03_final
2022-07-03 10:44:40	ga_ls8c_ard_3-2-1_104078_2022-07-03_final
2022-07-05 10:31:30	ga_ls8c_ard_3-2-1_102076_2022-07-05_final
2022-07-13 11:24:31	ga_ls8c_ard_3-2-1_110085_2022-07-13_final
2022-07-15 11:09:45	ga_ls8c_ard_3-2-1_108079_2022-07-15_final
2022-07-17 10:56:37	ga_ls8c_ard_3-2-1_106077_2022-07-17_final
2022-07-17 10:57:25	ga_ls8c_ard_3-2-1_106079_2022-07-17_final
2022-07-19 10:44:41	ga_ls8c_ard_3-2-1_104078_2022-07-19_final
2022-07-20 09:47:53	ga_ls8c_ard_3-2-1_095075_2022-07-20_final
2022-07-22 09:38:45	ga_ls8c_ard_3-2-1_093083_2022-07-22_final
2022-07-23 10:22:25	ga_ls8c_ard_3-2-1_100084_2022-07-23_final
2022-07-26 10:48:58	ga_ls8c_ard_3-2-1_105073_2022-07-26_final
2022-07-27 09:52:57	ga_ls8c_ard_3-2-1_096072_2022-07-27_final
2022-07-27 09:56:09	ga_ls8c_ard_3-2-1_096080_2022-07-27_final
2022-07-27 09:56:57	ga_ls8c_ard_3-2-1_096082_2022-07-27_final
2022-07-27 11:33:02	ga_ls8c_ard_3-2-1_112075_2022-07-27_final
2022-07-29 09:44:12	ga_ls8c_ard_3-2-1_094081_2022-07-29_final
2022-08-03 10:01:12	ga_ls8c_ard_3-2-1_097077_2022-08-03_final
2022-08-03 11:39:41	ga_ls8c_ard_3-2-1_113076_2022-08-03_final
2022-08-05 09:48:27	ga_ls8c_ard_3-2-1_095076_2022-08-05_final
2022-08-07 09:36:31	ga_ls8c_ard_3-2-1_093077_2022-08-07_final
2022-08-17 10:15:15	ga_ls8c_ard_3-2-1_099081_2022-08-17_final
2022-08-18 09:19:14	ga_ls8c_ard_3-2-1_090080_2022-08-17_final
2022-09-02 10:15:14	ga_ls8c_ard_3-2-1_099081_2022-09-02_final
2022-09-06 09:48:10	ga_ls8c_ard_3-2-1_095075_2022-09-06_final
2022-09-09 10:21:05	ga_ls8c_ard_3-2-1_100080_2022-09-09_final
2022-11-27 11:15:29	ga_ls8c_ard_3-2-1_109077_2022-11-27_final
2022-11-27 11:16:41	ga_ls8c_ard_3-2-1_109080_2022-11-27_final
2022-11-28 10:19:04	ga_ls8c_ard_3-2-1_100075_2022-11-28_final
2022-11-29 11:04:19	ga_ls8c_ard_3-2-1_107080_2022-11-29_final
2022-12-03 10:39:12	ga_ls8c_ard_3-2-1_103079_2022-12-03_final
2022-12-11 11:27:25	ga_ls8c_ard_3-2-1_111076_2022-12-11_final
2023-01-30 11:16:06	ga_ls8c_ard_3-2-1_109079_2023-01-30_final
2023-02-06 09:43:47	ga_ls8c_ard_3-2-1_094080_2023-02-06_final
2023-02-07 10:25:27	ga_ls8c_ard_3-2-1_101076_2023-02-07_final
2023-02-08 09:29:49	ga_ls8c_ard_3-2-1_092076_2023-02-07_final
2023-02-08 11:11:05	ga_ls8c_ard_3-2-1_108082_2023-02-08_final
2023-02-11 10:00:17	ga_ls8c_ard_3-2-1_097075_2023-02-11_final
2023-02-14 10:32:44	ga_ls8c_ard_3-2-1_102079_2023-02-14_final
2023-02-15 09:37:30	ga_ls8c_ard_3-2-1_093080_2023-02-15_final
2023-02-15 11:16:47	ga_ls8c_ard_3-2-1_109081_2023-02-15_final
2023-02-17 09:24:19	ga_ls8c_ard_3-2-1_091078_2023-02-16_final
2023-02-18 10:08:45	ga_ls8c_ard_3-2-1_098081_2023-02-18_final
2023-02-20 11:34:50	ga_ls8c_ard_3-2-1_112080_2023-02-20_final
2023-02-27 10:00:01	ga_ls8c_ard_3-2-1_097075_2023-02-27_final
2023-02-27 11:40:06	ga_ls8c_ard_3-2-1_113078_2023-02-27_final
2023-03-01 11:27:44	ga_ls8c_ard_3-2-1_111078_2023-03-01_final
2023-03-03 09:36:53	ga_ls8c_ard_3-2-1_093079_2023-03-03_final
2023-03-04 10:21:20	ga_ls8c_ard_3-2-1_100082_2023-03-04_final
2023-03-08 09:55:22	ga_ls8c_ard_3-2-1_096079_2023-03-08_final
2023-03-11 10:26:15	ga_ls8c_ard_3-2-1_101079_2023-03-11_final
2023-03-12 09:32:14	ga_ls8c_ard_3-2-1_092083_2023-03-12_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