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
2017-09-04 10:15:13	ga_ls8c_ard_3-0-0_099082_2017-09-04_final
2017-09-04 10:15:37	ga_ls8c_ard_3-0-0_099083_2017-09-04_final
2017-09-05 09:20:00	ga_ls8c_ard_3-0-0_090083_2017-09-04_final
2017-09-05 10:58:29	ga_ls8c_ard_3-0-0_106082_2017-09-05_final
2017-09-05 10:58:53	ga_ls8c_ard_3-0-0_106083_2017-09-05_final
2017-09-06 10:02:52	ga_ls8c_ard_3-0-0_097082_2017-09-06_final
2017-09-06 10:03:16	ga_ls8c_ard_3-0-0_097083_2017-09-06_final
2017-09-06 11:42:09	ga_ls8c_ard_3-0-0_113083_2017-09-06_final
2017-09-07 09:07:15	ga_ls8c_ard_3-0-0_088082_2017-09-06_final
2017-09-07 09:07:39	ga_ls8c_ard_3-0-0_088083_2017-09-06_final
2017-09-07 10:46:08	ga_ls8c_ard_3-0-0_104082_2017-09-07_final
2017-09-07 10:46:32	ga_ls8c_ard_3-0-0_104083_2017-09-07_final
2017-09-08 09:50:54	ga_ls8c_ard_3-0-0_095083_2017-09-08_final
2017-09-08 11:29:47	ga_ls8c_ard_3-0-0_111083_2017-09-08_final
2017-10-25 09:07:26	ga_ls8c_ard_3-0-0_088082_2017-10-24_final
2017-10-25 09:07:50	ga_ls8c_ard_3-0-0_088083_2017-10-24_final
2017-10-25 10:46:19	ga_ls8c_ard_3-0-0_104082_2017-10-25_final
2017-10-25 10:46:43	ga_ls8c_ard_3-0-0_104083_2017-10-25_final
2017-10-26 09:50:42	ga_ls8c_ard_3-0-0_095082_2017-10-26_final
2017-10-26 09:51:06	ga_ls8c_ard_3-0-0_095083_2017-10-26_final
2017-10-26 11:29:59	ga_ls8c_ard_3-0-0_111083_2017-10-26_final
2017-10-27 10:34:21	ga_ls8c_ard_3-0-0_102083_2017-10-27_final
2017-11-10 09:07:48	ga_ls8c_ard_3-0-0_088083_2017-11-09_final
2017-11-10 10:46:41	ga_ls8c_ard_3-0-0_104083_2017-11-10_final
2017-11-11 09:51:04	ga_ls8c_ard_3-0-0_095083_2017-11-11_final
2017-11-11 11:29:57	ga_ls8c_ard_3-0-0_111083_2017-11-11_final
2017-11-12 10:33:55	ga_ls8c_ard_3-0-0_102082_2017-11-12_final
2017-11-12 10:34:19	ga_ls8c_ard_3-0-0_102083_2017-11-12_final
2017-11-26 09:07:18	ga_ls8c_ard_3-0-0_088082_2017-11-25_final
2017-11-26 09:07:42	ga_ls8c_ard_3-0-0_088083_2017-11-25_final
2017-11-26 10:46:35	ga_ls8c_ard_3-0-0_104083_2017-11-26_final
2017-11-27 09:50:58	ga_ls8c_ard_3-0-0_095083_2017-11-27_final
2017-11-27 11:29:51	ga_ls8c_ard_3-0-0_111083_2017-11-27_final
2017-11-28 10:34:13	ga_ls8c_ard_3-0-0_102083_2017-11-28_final
2017-12-12 09:07:17	ga_ls8c_ard_3-0-0_088082_2017-12-11_final
2017-12-12 09:07:41	ga_ls8c_ard_3-0-0_088083_2017-12-11_final
2017-12-12 10:46:34	ga_ls8c_ard_3-0-0_104083_2017-12-12_final
2017-12-13 09:50:57	ga_ls8c_ard_3-0-0_095083_2017-12-13_final
2017-12-13 11:29:26	ga_ls8c_ard_3-0-0_111082_2017-12-13_final
2017-12-13 11:29:50	ga_ls8c_ard_3-0-0_111083_2017-12-13_final
2017-12-14 10:34:13	ga_ls8c_ard_3-0-0_102083_2017-12-14_final
2018-01-29 10:46:20	ga_ls8c_ard_3-0-0_104083_2018-01-29_final
2018-01-30 09:50:18	ga_ls8c_ard_3-0-0_095082_2018-01-30_final
2018-01-30 09:50:42	ga_ls8c_ard_3-0-0_095083_2018-01-30_final
2018-01-30 11:29:35	ga_ls8c_ard_3-0-0_111083_2018-01-30_final
2018-01-31 10:33:57	ga_ls8c_ard_3-0-0_102083_2018-01-31_final
2022-01-22 10:58:33	ga_ls8c_ard_3-2-1_106082_2022-01-22_final
2022-01-22 10:58:57	ga_ls8c_ard_3-2-1_106083_2022-01-22_final
2022-01-23 10:03:20	ga_ls8c_ard_3-2-1_097083_2022-01-23_final
2022-01-23 11:42:13	ga_ls8c_ard_3-2-1_113083_2022-01-23_final
2022-01-24 09:07:18	ga_ls8c_ard_3-2-1_088082_2022-01-23_final
2022-01-24 09:07:42	ga_ls8c_ard_3-2-1_088083_2022-01-23_final
2022-01-25 09:50:33	ga_ls8c_ard_3-2-1_095082_2022-01-25_final
2022-01-25 09:50:57	ga_ls8c_ard_3-2-1_095083_2022-01-25_final
2022-03-21 11:35:43	ga_ls8c_ard_3-2-1_112083_2022-03-21_final
2022-03-23 09:44:27	ga_ls8c_ard_3-2-1_094083_2022-03-23_final
2022-03-23 11:23:20	ga_ls8c_ard_3-2-1_110083_2022-03-23_final
2022-03-24 10:27:42	ga_ls8c_ard_3-2-1_101083_2022-03-24_final
2022-03-25 09:32:04	ga_ls8c_ard_3-2-1_092083_2022-03-25_final
2022-03-25 11:10:57	ga_ls8c_ard_3-2-1_108083_2022-03-25_final
2022-03-26 10:15:19	ga_ls8c_ard_3-2-1_099083_2022-03-26_final
2022-03-27 09:19:40	ga_ls8c_ard_3-2-1_090083_2022-03-26_final
2022-03-27 10:58:33	ga_ls8c_ard_3-2-1_106083_2022-03-27_final
2022-03-28 10:02:55	ga_ls8c_ard_3-2-1_097083_2022-03-28_final
2022-03-28 11:41:48	ga_ls8c_ard_3-2-1_113083_2022-03-28_final
2022-04-01 09:38:10	ga_ls8c_ard_3-2-1_093083_2022-04-01_final
2022-04-01 11:17:03	ga_ls8c_ard_3-2-1_109083_2022-04-01_final
2022-04-02 10:21:26	ga_ls8c_ard_3-2-1_100083_2022-04-02_final
2022-04-03 09:25:48	ga_ls8c_ard_3-2-1_091083_2022-04-02_final
2022-04-03 11:04:41	ga_ls8c_ard_3-2-1_107083_2022-04-03_final
2022-04-04 10:09:05	ga_ls8c_ard_3-2-1_098083_2022-04-04_final
2022-04-05 09:13:28	ga_ls8c_ard_3-2-1_089083_2022-04-04_final
2022-04-05 10:52:21	ga_ls8c_ard_3-2-1_105083_2022-04-05_final
2022-04-06 09:56:45	ga_ls8c_ard_3-2-1_096083_2022-04-06_final
2022-04-06 11:35:38	ga_ls8c_ard_3-2-1_112083_2022-04-06_final
2022-06-18 11:29:28	ga_ls8c_ard_3-2-1_111082_2022-06-18_final
2022-06-18 11:29:52	ga_ls8c_ard_3-2-1_111083_2022-06-18_final
2022-06-19 10:33:51	ga_ls8c_ard_3-2-1_102082_2022-06-19_final
2022-06-20 09:38:38	ga_ls8c_ard_3-2-1_093083_2022-06-20_final
2023-02-12 09:07:26	ga_ls8c_ard_3-2-1_088082_2023-02-11_final
2023-02-12 09:07:50	ga_ls8c_ard_3-2-1_088083_2023-02-11_final
2023-02-13 09:51:05	ga_ls8c_ard_3-2-1_095083_2023-02-13_final
2023-02-13 11:29:58	ga_ls8c_ard_3-2-1_111083_2023-02-13_final
2023-02-14 10:33:56	ga_ls8c_ard_3-2-1_102082_2023-02-14_final
2023-02-15 09:38:42	ga_ls8c_ard_3-2-1_093083_2023-02-15_final
2023-02-15 11:17:35	ga_ls8c_ard_3-2-1_109083_2023-02-15_final
2023-02-16 10:21:57	ga_ls8c_ard_3-2-1_100083_2023-02-16_final
2023-02-17 09:26:18	ga_ls8c_ard_3-2-1_091083_2023-02-16_final
2023-02-17 11:04:47	ga_ls8c_ard_3-2-1_107082_2023-02-17_final
2023-02-17 11:05:11	ga_ls8c_ard_3-2-1_107083_2023-02-17_final
2023-02-18 10:09:33	ga_ls8c_ard_3-2-1_098083_2023-02-18_final
2023-02-19 09:13:54	ga_ls8c_ard_3-2-1_089083_2023-02-18_final
2023-02-19 10:52:47	ga_ls8c_ard_3-2-1_105083_2023-02-19_final
2023-02-24 11:11:13	ga_ls8c_ard_3-2-1_108083_2023-02-24_final
2023-02-25 10:15:10	ga_ls8c_ard_3-2-1_099082_2023-02-25_final
2023-02-25 10:15:34	ga_ls8c_ard_3-2-1_099083_2023-02-25_final
2023-02-26 09:19:57	ga_ls8c_ard_3-2-1_090083_2023-02-25_final
2023-02-26 10:58:50	ga_ls8c_ard_3-2-1_106083_2023-02-26_final
2023-02-27 10:03:13	ga_ls8c_ard_3-2-1_097083_2023-02-27_final
2023-02-27 11:42:06	ga_ls8c_ard_3-2-1_113083_2023-02-27_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years