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
2022-03-05 11:31:52	ga_ls8c_ard_3-2-1_112073_2022-03-05_final
2022-03-16 11:12:51	ga_ls8c_ard_3-2-1_109072_2022-03-16_final
2022-03-30 09:47:20	ga_ls8c_ard_3-2-1_095075_2022-03-30_final
2022-04-03 11:03:06	ga_ls8c_ard_3-2-1_107079_2022-04-03_final
2022-04-11 11:51:49	ga_ls8c_ard_3-2-1_115077_2022-04-11_final
2022-04-12 09:18:07	ga_ls8c_ard_3-2-1_090079_2022-04-11_final
2022-04-20 10:08:45	ga_ls8c_ard_3-2-1_098082_2022-04-20_final
2022-04-21 10:50:01	ga_ls8c_ard_3-2-1_105077_2022-04-21_final
2022-04-23 10:36:03	ga_ls8c_ard_3-2-1_103073_2022-04-23_final
2022-04-26 11:09:19	ga_ls8c_ard_3-2-1_108079_2022-04-26_final
2022-04-28 09:19:15	ga_ls8c_ard_3-2-1_090082_2022-04-27_final
2022-05-04 10:17:32	ga_ls8c_ard_3-2-1_100073_2022-05-04_final
2022-05-04 11:57:37	ga_ls8c_ard_3-2-1_116076_2022-05-04_final
2022-05-06 11:46:52	ga_ls8c_ard_3-2-1_114080_2022-05-06_final
2022-05-07 09:14:46	ga_ls8c_ard_3-2-1_089086_2022-05-06_final
2022-05-20 11:57:44	ga_ls8c_ard_3-2-1_116076_2022-05-20_final
2022-05-21 11:04:06	ga_ls8c_ard_3-2-1_107081_2022-05-21_final
2022-06-04 11:15:45	ga_ls8c_ard_3-2-1_109079_2022-06-04_final
2022-06-07 11:45:30	ga_ls8c_ard_3-2-1_114076_2022-06-07_final
2022-06-08 09:14:12	ga_ls8c_ard_3-2-1_089084_2022-06-07_final
2022-06-20 11:12:20	ga_ls8c_ard_3-2-1_109070_2022-06-20_final
2022-06-24 09:15:08	ga_ls8c_ard_3-2-1_089086_2022-06-23_final
2022-06-27 09:43:15	ga_ls8c_ard_3-2-1_094079_2022-06-27_final
2022-06-28 10:25:43	ga_ls8c_ard_3-2-1_101077_2022-06-28_final
2022-07-10 10:47:39	ga_ls8c_ard_3-2-1_105070_2022-07-10_final
2022-07-11 09:55:37	ga_ls8c_ard_3-2-1_096079_2022-07-11_final
2022-07-13 11:22:31	ga_ls8c_ard_3-2-1_110080_2022-07-13_final
2022-07-15 09:30:52	ga_ls8c_ard_3-2-1_092079_2022-07-15_final
2022-07-16 11:53:01	ga_ls8c_ard_3-2-1_115079_2022-07-16_final
2022-07-17 10:57:25	ga_ls8c_ard_3-2-1_106079_2022-07-17_final
2022-07-22 11:13:38	ga_ls8c_ard_3-2-1_109073_2022-07-22_final
2022-07-27 09:52:33	ga_ls8c_ard_3-2-1_096071_2022-07-27_final
2022-07-29 09:45:00	ga_ls8c_ard_3-2-1_094083_2022-07-29_final
2022-08-05 09:47:40	ga_ls8c_ard_3-2-1_095074_2022-08-05_final
2022-08-10 10:04:15	ga_ls8c_ard_3-2-1_098069_2022-08-10_final
2022-08-11 09:13:25	ga_ls8c_ard_3-2-1_089081_2022-08-10_final
2022-08-17 10:12:27	ga_ls8c_ard_3-2-1_099074_2022-08-17_final
2022-08-23 09:39:22	ga_ls8c_ard_3-2-1_093084_2022-08-23_final
2022-08-24 10:21:26	ga_ls8c_ard_3-2-1_100081_2022-08-24_final
2022-08-26 10:04:41	ga_ls8c_ard_3-2-1_098070_2022-08-26_final
2022-08-27 10:46:45	ga_ls8c_ard_3-2-1_105067_2022-08-27_final
2022-09-04 11:38:11	ga_ls8c_ard_3-2-1_113072_2022-09-04_final
2022-09-05 10:42:10	ga_ls8c_ard_3-2-1_104071_2022-09-05_final
2022-09-10 09:25:04	ga_ls8c_ard_3-2-1_091079_2022-09-09_final
2022-09-11 11:47:14	ga_ls8c_ard_3-2-1_114079_2022-09-11_final
2022-09-17 11:08:59	ga_ls8c_ard_3-2-1_108076_2022-09-17_final
2022-09-24 09:39:53	ga_ls8c_ard_3-2-1_093085_2022-09-24_final
2022-10-03 11:06:10	ga_ls8c_ard_3-2-1_108069_2022-10-03_final
2022-10-10 11:16:40	ga_ls8c_ard_3-2-1_109080_2022-10-10_final
2022-10-12 09:25:47	ga_ls8c_ard_3-2-1_091081_2022-10-11_final
2022-10-15 09:56:17	ga_ls8c_ard_3-2-1_096080_2022-10-15_final
2022-10-22 10:00:57	ga_ls8c_ard_3-2-1_097076_2022-10-22_final
2022-10-27 10:20:43	ga_ls8c_ard_3-2-1_100079_2022-10-27_final
2022-10-27 11:59:13	ga_ls8c_ard_3-2-1_116078_2022-10-27_final
2022-10-29 10:06:47	ga_ls8c_ard_3-2-1_098075_2022-10-29_final
2022-11-04 09:32:30	ga_ls8c_ard_3-2-1_092082_2022-11-04_final
2022-11-04 11:10:59	ga_ls8c_ard_3-2-1_108081_2022-11-04_final
2022-11-04 11:11:23	ga_ls8c_ard_3-2-1_108082_2022-11-04_final
2022-11-07 10:01:23	ga_ls8c_ard_3-2-1_097077_2022-11-07_final
2022-11-08 10:43:51	ga_ls8c_ard_3-2-1_104075_2022-11-08_final
2022-11-14 10:06:42	ga_ls8c_ard_3-2-1_098075_2022-11-14_final
2022-11-16 09:53:55	ga_ls8c_ard_3-2-1_096074_2022-11-16_final
2022-11-22 09:19:14	ga_ls8c_ard_3-2-1_090080_2022-11-21_final
2022-11-22 10:59:19	ga_ls8c_ard_3-2-1_106083_2022-11-22_final
2022-11-24 10:43:22	ga_ls8c_ard_3-2-1_104074_2022-11-24_final
2022-12-06 09:35:12	ga_ls8c_ard_3-2-1_092089_2022-12-06_final
2022-12-07 10:12:52	ga_ls8c_ard_3-2-1_099075_2022-12-07_final
2022-12-10 10:45:45	ga_ls8c_ard_3-2-1_104080_2022-12-10_final
2022-12-14 10:21:00	ga_ls8c_ard_3-2-1_100080_2022-12-14_final
2022-12-23 11:51:11	ga_ls8c_ard_3-2-1_115074_2022-12-23_final
2022-12-25 11:42:02	ga_ls8c_ard_3-2-1_113082_2022-12-25_final
2022-12-26 09:07:56	ga_ls8c_ard_3-2-1_088083_2022-12-25_final
2022-12-27 09:52:48	ga_ls8c_ard_3-2-1_095087_2022-12-27_final
2023-01-01 11:46:14	ga_ls8c_ard_3-2-1_114077_2023-01-01_final
2023-01-02 10:51:25	ga_ls8c_ard_3-2-1_105079_2023-01-02_final
2023-01-05 09:45:02	ga_ls8c_ard_3-2-1_094083_2023-01-05_final
2023-01-09 09:20:41	ga_ls8c_ard_3-2-1_090084_2023-01-08_final
2023-01-09 10:57:58	ga_ls8c_ard_3-2-1_106080_2023-01-09_final
2023-01-25 09:18:16	ga_ls8c_ard_3-2-1_090078_2023-01-24_final
2023-02-15 09:40:42	ga_ls8c_ard_3-2-1_093088_2023-02-15_final
2023-02-20 09:55:09	ga_ls8c_ard_3-2-1_096078_2023-02-20_final
2023-02-21 10:38:47	ga_ls8c_ard_3-2-1_103079_2023-02-21_final
2023-03-03 09:36:53	ga_ls8c_ard_3-2-1_093079_2023-03-03_final
2023-03-05 11:02:35	ga_ls8c_ard_3-2-1_107077_2023-03-05_final
2023-03-07 10:50:12	ga_ls8c_ard_3-2-1_105077_2023-03-07_final
2023-03-15 10:01:31	ga_ls8c_ard_3-2-1_097079_2023-03-15_final
2023-03-15 11:41:36	ga_ls8c_ard_3-2-1_113082_2023-03-15_final
2023-03-18 10:31:35	ga_ls8c_ard_3-2-1_102077_2023-03-18_final
2023-03-29 10:14:32	ga_ls8c_ard_3-2-1_099081_2023-03-29_final
2023-04-04 09:37:21	ga_ls8c_ard_3-2-1_093081_2023-04-04_final
2023-04-04 11:15:50	ga_ls8c_ard_3-2-1_109080_2023-04-04_final
2023-04-07 11:46:17	ga_ls8c_ard_3-2-1_114079_2023-04-07_final
2023-04-09 09:52:35	ga_ls8c_ard_3-2-1_096073_2023-04-09_final
2023-04-09 09:52:59	ga_ls8c_ard_3-2-1_096074_2023-04-09_final
2023-04-16 10:01:30	ga_ls8c_ard_3-2-1_097080_2023-04-16_final
2023-04-20 11:14:50	ga_ls8c_ard_3-2-1_109078_2023-04-20_final
2023-05-04 09:49:26	ga_ls8c_ard_3-2-1_095081_2023-05-04_final
2023-05-10 10:50:20	ga_ls8c_ard_3-2-1_105079_2023-05-10_final
2023-05-15 09:30:20	ga_ls8c_ard_3-2-1_092080_2023-05-15_final
2023-05-15 11:05:13	ga_ls8c_ard_3-2-1_108070_2023-05-15_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years