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
2022-07-17 10:56:13	ga_ls8c_ard_3-2-1_106076_2022-07-17_final
2022-07-18 10:02:36	ga_ls8c_ard_3-2-1_097081_2022-07-18_final
2022-07-26 10:51:22	ga_ls8c_ard_3-2-1_105079_2022-07-26_final
2022-07-29 11:21:54	ga_ls8c_ard_3-2-1_110078_2022-07-29_final
2022-08-05 09:52:03	ga_ls8c_ard_3-2-1_095085_2022-08-05_final
2022-08-09 11:05:27	ga_ls8c_ard_3-2-1_107083_2022-08-09_final
2022-08-11 09:14:37	ga_ls8c_ard_3-2-1_089084_2022-08-10_final
2022-08-11 10:51:54	ga_ls8c_ard_3-2-1_105080_2022-08-11_final
2022-08-13 10:34:46	ga_ls8c_ard_3-2-1_103068_2022-08-13_final
2022-08-14 11:20:49	ga_ls8c_ard_3-2-1_110075_2022-08-14_final
2022-08-21 09:52:32	ga_ls8c_ard_3-2-1_095086_2022-08-21_final
2022-08-24 10:20:38	ga_ls8c_ard_3-2-1_100079_2022-08-24_final
2022-08-25 11:02:42	ga_ls8c_ard_3-2-1_107076_2022-08-25_final
2022-08-26 10:10:16	ga_ls8c_ard_3-2-1_098084_2022-08-26_final
2022-08-27 10:50:44	ga_ls8c_ard_3-2-1_105077_2022-08-27_final
2022-09-01 09:32:47	ga_ls8c_ard_3-2-1_092083_2022-09-01_final
2022-09-01 11:08:52	ga_ls8c_ard_3-2-1_108076_2022-09-01_final
2022-09-03 10:56:30	ga_ls8c_ard_3-2-1_106076_2022-09-03_final
2022-09-07 10:33:26	ga_ls8c_ard_3-2-1_102080_2022-09-07_final
2022-09-07 10:33:50	ga_ls8c_ard_3-2-1_102081_2022-09-07_final
2022-09-09 10:20:41	ga_ls8c_ard_3-2-1_100079_2022-09-09_final
2022-09-12 10:52:25	ga_ls8c_ard_3-2-1_105081_2022-09-12_final
2022-09-15 09:41:15	ga_ls8c_ard_3-2-1_094073_2022-09-15_final
2022-09-15 11:20:56	ga_ls8c_ard_3-2-1_110075_2022-09-15_final
2022-09-17 09:34:29	ga_ls8c_ard_3-2-1_092087_2022-09-17_final
2022-09-28 10:46:51	ga_ls8c_ard_3-2-1_105067_2022-09-28_final
2022-09-29 11:34:54	ga_ls8c_ard_3-2-1_112079_2022-09-29_final
2022-10-01 09:44:51	ga_ls8c_ard_3-2-1_094082_2022-10-01_final
2022-10-06 10:04:33	ga_ls8c_ard_3-2-1_097085_2022-10-06_final
2022-10-07 10:46:12	ga_ls8c_ard_3-2-1_104081_2022-10-07_final
2022-10-10 11:14:40	ga_ls8c_ard_3-2-1_109075_2022-10-10_final
2022-10-14 10:49:54	ga_ls8c_ard_3-2-1_105075_2022-10-14_final
2022-10-14 10:50:42	ga_ls8c_ard_3-2-1_105077_2022-10-14_final
2022-10-17 09:44:45	ga_ls8c_ard_3-2-1_094082_2022-10-17_final
2022-10-17 11:20:50	ga_ls8c_ard_3-2-1_110075_2022-10-17_final
2022-10-20 10:11:18	ga_ls8c_ard_3-2-1_099071_2022-10-20_final
2022-10-28 11:03:12	ga_ls8c_ard_3-2-1_107077_2022-10-28_final
2022-11-02 11:21:21	ga_ls8c_ard_3-2-1_110076_2022-11-02_final
2022-11-04 09:32:06	ga_ls8c_ard_3-2-1_092081_2022-11-04_final
2022-11-08 10:46:14	ga_ls8c_ard_3-2-1_104081_2022-11-08_final
2022-11-09 11:26:42	ga_ls8c_ard_3-2-1_111074_2022-11-09_final
2022-11-11 11:17:31	ga_ls8c_ard_3-2-1_109082_2022-11-11_final
2022-11-15 10:49:33	ga_ls8c_ard_3-2-1_105074_2022-11-15_final
2022-11-16 09:55:55	ga_ls8c_ard_3-2-1_096079_2022-11-16_final
2022-11-20 09:31:35	ga_ls8c_ard_3-2-1_092080_2022-11-20_final
2022-11-21 11:51:20	ga_ls8c_ard_3-2-1_115074_2022-11-21_final
2022-11-22 10:58:55	ga_ls8c_ard_3-2-1_106082_2022-11-22_final
2022-11-27 09:40:11	ga_ls8c_ard_3-2-1_093086_2022-11-27_final
2022-11-27 11:14:17	ga_ls8c_ard_3-2-1_109074_2022-11-27_final
2022-11-30 10:10:42	ga_ls8c_ard_3-2-1_098085_2022-11-30_final
2022-12-01 10:50:46	ga_ls8c_ard_3-2-1_105077_2022-12-01_final
2022-12-04 09:41:35	ga_ls8c_ard_3-2-1_094074_2022-12-04_final
2022-12-06 09:31:37	ga_ls8c_ard_3-2-1_092080_2022-12-06_final
2022-12-08 09:20:02	ga_ls8c_ard_3-2-1_090082_2022-12-07_final
2022-12-15 11:03:27	ga_ls8c_ard_3-2-1_107078_2022-12-15_final
2022-12-16 10:10:12	ga_ls8c_ard_3-2-1_098084_2022-12-16_final
2022-12-17 09:14:10	ga_ls8c_ard_3-2-1_089083_2022-12-16_final
2022-12-17 10:49:52	ga_ls8c_ard_3-2-1_105075_2022-12-17_final
2022-12-19 10:40:16	ga_ls8c_ard_3-2-1_103082_2022-12-19_final
2022-12-26 10:46:01	ga_ls8c_ard_3-2-1_104081_2022-12-26_final
2022-12-29 11:14:08	ga_ls8c_ard_3-2-1_109074_2022-12-29_final
2023-01-02 10:51:49	ga_ls8c_ard_3-2-1_105080_2023-01-02_final
2023-01-05 09:42:14	ga_ls8c_ard_3-2-1_094076_2023-01-05_final
2023-01-09 10:57:58	ga_ls8c_ard_3-2-1_106080_2023-01-09_final
2023-01-12 11:30:26	ga_ls8c_ard_3-2-1_111084_2023-01-12_final
2023-01-16 11:02:28	ga_ls8c_ard_3-2-1_107076_2023-01-16_final
2023-01-25 09:17:52	ga_ls8c_ard_3-2-1_090077_2023-01-24_final
2023-01-25 10:57:56	ga_ls8c_ard_3-2-1_106080_2023-01-25_final
2023-02-05 10:34:37	ga_ls8c_ard_3-2-1_103068_2023-02-05_final
2023-02-05 10:39:25	ga_ls8c_ard_3-2-1_103080_2023-02-05_final
2023-02-08 11:10:42	ga_ls8c_ard_3-2-1_108081_2023-02-08_final
2023-02-09 10:14:40	ga_ls8c_ard_3-2-1_099080_2023-02-09_final
2023-02-13 09:51:53	ga_ls8c_ard_3-2-1_095085_2023-02-13_final
2023-02-17 11:05:11	ga_ls8c_ard_3-2-1_107083_2023-02-17_final
2023-02-17 11:05:35	ga_ls8c_ard_3-2-1_107084_2023-02-17_final
2023-02-24 09:35:07	ga_ls8c_ard_3-2-1_092090_2023-02-24_final
2023-03-03 11:14:10	ga_ls8c_ard_3-2-1_109075_2023-03-03_final
2023-03-12 11:10:19	ga_ls8c_ard_3-2-1_108081_2023-03-12_final
2023-03-18 10:33:11	ga_ls8c_ard_3-2-1_102081_2023-03-18_final
2023-03-25 10:38:52	ga_ls8c_ard_3-2-1_103080_2023-03-25_final
2023-03-26 09:44:03	ga_ls8c_ard_3-2-1_094082_2023-03-26_final
2023-03-28 09:30:52	ga_ls8c_ard_3-2-1_092080_2023-03-28_final
2023-04-04 09:37:21	ga_ls8c_ard_3-2-1_093081_2023-04-04_final
2023-04-04 09:38:57	ga_ls8c_ard_3-2-1_093085_2023-04-04_final
2023-04-06 11:02:38	ga_ls8c_ard_3-2-1_107078_2023-04-06_final
2023-04-08 10:49:26	ga_ls8c_ard_3-2-1_105076_2023-04-08_final
2023-04-11 09:43:46	ga_ls8c_ard_3-2-1_094082_2023-04-11_final
2023-04-11 11:19:52	ga_ls8c_ard_3-2-1_110075_2023-04-11_final
2023-04-20 09:37:08	ga_ls8c_ard_3-2-1_093081_2023-04-20_final
2023-04-20 09:38:20	ga_ls8c_ard_3-2-1_093084_2023-04-20_final
2023-04-24 10:49:43	ga_ls8c_ard_3-2-1_105077_2023-04-24_final
2023-04-24 10:50:55	ga_ls8c_ard_3-2-1_105080_2023-04-24_final
2023-04-26 10:33:46	ga_ls8c_ard_3-2-1_103068_2023-04-26_final
2023-04-29 09:28:33	ga_ls8c_ard_3-2-1_092075_2023-04-28_final
2023-04-30 10:15:48	ga_ls8c_ard_3-2-1_099085_2023-04-30_final
2023-05-05 10:32:41	ga_ls8c_ard_3-2-1_102081_2023-05-05_final
2023-05-10 10:50:44	ga_ls8c_ard_3-2-1_105080_2023-05-10_final
2023-05-13 11:19:12	ga_ls8c_ard_3-2-1_110074_2023-05-13_final
2023-05-13 11:19:36	ga_ls8c_ard_3-2-1_110075_2023-05-13_final
2023-05-15 11:07:37	ga_ls8c_ard_3-2-1_108076_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