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
2022-06-06 11:02:14	ga_ls8c_ard_3-2-1_107076_2022-06-06_final
2022-06-08 10:50:18	ga_ls8c_ard_3-2-1_105077_2022-06-08_final
2022-06-08 10:51:53	ga_ls8c_ard_3-2-1_105081_2022-06-08_final
2022-06-19 10:31:04	ga_ls8c_ard_3-2-1_102075_2022-06-19_final
2022-06-24 10:50:26	ga_ls8c_ard_3-2-1_105077_2022-06-24_final
2022-06-29 09:31:18	ga_ls8c_ard_3-2-1_092080_2022-06-29_final
2022-07-06 11:14:22	ga_ls8c_ard_3-2-1_109075_2022-07-06_final
2022-07-08 11:02:48	ga_ls8c_ard_3-2-1_107077_2022-07-08_final
2022-07-15 11:08:33	ga_ls8c_ard_3-2-1_108076_2022-07-15_final
2022-07-15 11:08:57	ga_ls8c_ard_3-2-1_108077_2022-07-15_final
2022-07-20 11:25:58	ga_ls8c_ard_3-2-1_111073_2022-07-20_final
2022-07-22 11:15:14	ga_ls8c_ard_3-2-1_109077_2022-07-22_final
2022-07-26 10:51:45	ga_ls8c_ard_3-2-1_105080_2022-07-26_final
2022-07-29 11:20:18	ga_ls8c_ard_3-2-1_110074_2022-07-29_final
2022-08-03 10:01:36	ga_ls8c_ard_3-2-1_097078_2022-08-03_final
2022-08-03 10:04:24	ga_ls8c_ard_3-2-1_097085_2022-08-03_final
2022-08-04 10:45:16	ga_ls8c_ard_3-2-1_104079_2022-08-04_final
2022-08-06 10:28:56	ga_ls8c_ard_3-2-1_102069_2022-08-06_final
2022-08-14 09:44:44	ga_ls8c_ard_3-2-1_094082_2022-08-14_final
2022-08-17 10:15:39	ga_ls8c_ard_3-2-1_099082_2022-08-17_final
2022-08-18 09:21:37	ga_ls8c_ard_3-2-1_090086_2022-08-17_final
2022-08-19 10:04:29	ga_ls8c_ard_3-2-1_097085_2022-08-19_final
2022-08-25 09:27:48	ga_ls8c_ard_3-2-1_091086_2022-08-24_final
2022-08-25 11:03:30	ga_ls8c_ard_3-2-1_107078_2022-08-25_final
2022-08-27 09:11:51	ga_ls8c_ard_3-2-1_089077_2022-08-26_final
2022-08-27 10:51:56	ga_ls8c_ard_3-2-1_105080_2022-08-27_final
2022-08-29 10:35:11	ga_ls8c_ard_3-2-1_103069_2022-08-29_final
2022-08-30 11:20:26	ga_ls8c_ard_3-2-1_110074_2022-08-30_final
2022-09-04 11:40:59	ga_ls8c_ard_3-2-1_113079_2022-09-04_final
2022-09-05 10:45:22	ga_ls8c_ard_3-2-1_104079_2022-09-05_final
2022-09-08 11:16:18	ga_ls8c_ard_3-2-1_109079_2022-09-08_final
2022-09-12 10:50:25	ga_ls8c_ard_3-2-1_105076_2022-09-12_final
2022-09-12 10:52:01	ga_ls8c_ard_3-2-1_105080_2022-09-12_final
2022-09-26 11:03:13	ga_ls8c_ard_3-2-1_107077_2022-09-26_final
2022-09-28 10:50:03	ga_ls8c_ard_3-2-1_105075_2022-09-28_final
2022-09-28 10:50:27	ga_ls8c_ard_3-2-1_105076_2022-09-28_final
2022-09-28 10:50:51	ga_ls8c_ard_3-2-1_105077_2022-09-28_final
2022-09-30 10:39:41	ga_ls8c_ard_3-2-1_103080_2022-09-30_final
2022-10-01 11:20:56	ga_ls8c_ard_3-2-1_110075_2022-10-01_final
2022-10-04 10:14:32	ga_ls8c_ard_3-2-1_099079_2022-10-04_final
2022-10-11 10:22:38	ga_ls8c_ard_3-2-1_100084_2022-10-11_final
2022-10-18 10:26:26	ga_ls8c_ard_3-2-1_101078_2022-10-18_final
2022-10-19 09:30:01	ga_ls8c_ard_3-2-1_092076_2022-10-19_final
2022-10-24 09:51:00	ga_ls8c_ard_3-2-1_095082_2022-10-24_final
2022-10-28 11:03:36	ga_ls8c_ard_3-2-1_107078_2022-10-28_final
2022-11-06 09:17:20	ga_ls8c_ard_3-2-1_090075_2022-11-05_final
2022-11-06 09:21:44	ga_ls8c_ard_3-2-1_090086_2022-11-05_final
2022-11-06 10:58:37	ga_ls8c_ard_3-2-1_106081_2022-11-06_final
2022-11-20 11:10:52	ga_ls8c_ard_3-2-1_108081_2022-11-20_final
2022-11-25 09:52:33	ga_ls8c_ard_3-2-1_095086_2022-11-25_final
2022-11-27 11:14:41	ga_ls8c_ard_3-2-1_109075_2022-11-27_final
2022-11-29 09:27:26	ga_ls8c_ard_3-2-1_091085_2022-11-28_final
2022-11-29 11:00:20	ga_ls8c_ard_3-2-1_107070_2022-11-29_final
2022-12-01 10:49:10	ga_ls8c_ard_3-2-1_105073_2022-12-01_final
2022-12-06 11:08:06	ga_ls8c_ard_3-2-1_108074_2022-12-06_final
2022-12-09 10:03:42	ga_ls8c_ard_3-2-1_097083_2022-12-09_final
2022-12-09 10:04:30	ga_ls8c_ard_3-2-1_097085_2022-12-09_final
2022-12-14 10:22:11	ga_ls8c_ard_3-2-1_100083_2022-12-14_final
2022-12-20 11:20:43	ga_ls8c_ard_3-2-1_110075_2022-12-20_final
2022-12-28 10:33:16	ga_ls8c_ard_3-2-1_102080_2022-12-28_final
2022-12-31 11:02:59	ga_ls8c_ard_3-2-1_107077_2022-12-31_final
2022-12-31 11:05:46	ga_ls8c_ard_3-2-1_107084_2022-12-31_final
2023-01-04 10:40:15	ga_ls8c_ard_3-2-1_103082_2023-01-04_final
2023-01-05 09:43:02	ga_ls8c_ard_3-2-1_094078_2023-01-05_final
2023-01-05 11:20:43	ga_ls8c_ard_3-2-1_110075_2023-01-05_final
2023-01-08 10:11:07	ga_ls8c_ard_3-2-1_099071_2023-01-08_final
2023-01-10 10:03:56	ga_ls8c_ard_3-2-1_097084_2023-01-10_final
2023-01-12 09:49:09	ga_ls8c_ard_3-2-1_095078_2023-01-12_final
2023-01-12 11:25:15	ga_ls8c_ard_3-2-1_111071_2023-01-12_final
2023-01-18 10:50:04	ga_ls8c_ard_3-2-1_105076_2023-01-18_final
2023-01-19 09:58:04	ga_ls8c_ard_3-2-1_096085_2023-01-19_final
2023-01-22 10:23:49	ga_ls8c_ard_3-2-1_101072_2023-01-22_final
2023-01-26 09:57:32	ga_ls8c_ard_3-2-1_097068_2023-01-26_final
2023-01-26 11:41:13	ga_ls8c_ard_3-2-1_113080_2023-01-26_final
2023-02-09 10:09:52	ga_ls8c_ard_3-2-1_099068_2023-02-09_final
2023-02-10 10:56:19	ga_ls8c_ard_3-2-1_106076_2023-02-10_final
2023-02-10 10:57:55	ga_ls8c_ard_3-2-1_106080_2023-02-10_final
2023-02-10 10:59:06	ga_ls8c_ard_3-2-1_106083_2023-02-10_final
2023-02-17 11:02:48	ga_ls8c_ard_3-2-1_107077_2023-02-17_final
2023-02-25 10:15:58	ga_ls8c_ard_3-2-1_099084_2023-02-25_final
2023-03-01 09:52:27	ga_ls8c_ard_3-2-1_095087_2023-03-01_final
2023-03-05 11:04:35	ga_ls8c_ard_3-2-1_107082_2023-03-05_final
2023-03-06 11:47:26	ga_ls8c_ard_3-2-1_114081_2023-03-06_final
2023-03-08 09:52:58	ga_ls8c_ard_3-2-1_096073_2023-03-08_final
2023-03-10 09:40:36	ga_ls8c_ard_3-2-1_094073_2023-03-10_final
2023-03-10 11:20:17	ga_ls8c_ard_3-2-1_110075_2023-03-10_final
2023-03-14 10:55:57	ga_ls8c_ard_3-2-1_106076_2023-03-14_final
2023-03-28 09:33:40	ga_ls8c_ard_3-2-1_092087_2023-03-28_final
2023-03-29 11:53:01	ga_ls8c_ard_3-2-1_115080_2023-03-29_final
2023-04-02 09:51:45	ga_ls8c_ard_3-2-1_095086_2023-04-02_final
2023-04-02 11:27:02	ga_ls8c_ard_3-2-1_111077_2023-04-02_final
2023-04-04 11:13:51	ga_ls8c_ard_3-2-1_109075_2023-04-04_final
2023-04-05 11:57:29	ga_ls8c_ard_3-2-1_116076_2023-04-05_final
2023-04-08 09:10:57	ga_ls8c_ard_3-2-1_089077_2023-04-07_final
2023-04-08 10:50:38	ga_ls8c_ard_3-2-1_105079_2023-04-08_final
2023-04-19 10:33:10	ga_ls8c_ard_3-2-1_102082_2023-04-19_final
2023-04-21 11:57:18	ga_ls8c_ard_3-2-1_116076_2023-04-21_final
2023-05-06 09:39:26	ga_ls8c_ard_3-2-1_093087_2023-05-06_final
2023-05-09 10:09:29	ga_ls8c_ard_3-2-1_098085_2023-05-09_final
2023-05-10 10:49:32	ga_ls8c_ard_3-2-1_105077_2023-05-10_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