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
2014-01-22 10:22:50	ga_ls8c_ard_3-0-0_100083_2014-01-22_final
2014-01-23 09:27:12	ga_ls8c_ard_3-0-0_091083_2014-01-22_final
2014-01-25 09:14:50	ga_ls8c_ard_3-0-0_089083_2014-01-24_final
2014-01-26 09:58:05	ga_ls8c_ard_3-0-0_096083_2014-01-26_final
2014-01-26 11:36:58	ga_ls8c_ard_3-0-0_112083_2014-01-26_final
2014-02-15 11:11:59	ga_ls8c_ard_3-0-0_108083_2014-02-15_final
2014-02-16 10:16:21	ga_ls8c_ard_3-0-0_099083_2014-02-16_final
2014-02-17 09:20:43	ga_ls8c_ard_3-0-0_090083_2014-02-16_final
2014-02-17 10:59:36	ga_ls8c_ard_3-0-0_106083_2014-02-17_final
2014-02-18 10:03:58	ga_ls8c_ard_3-0-0_097083_2014-02-18_final
2014-02-18 11:42:51	ga_ls8c_ard_3-0-0_113083_2014-02-18_final
2014-02-20 09:51:36	ga_ls8c_ard_3-0-0_095083_2014-02-20_final
2014-02-20 11:30:29	ga_ls8c_ard_3-0-0_111083_2014-02-20_final
2014-05-30 10:21:16	ga_ls8c_ard_3-0-0_100083_2014-05-30_final
2014-05-31 09:25:40	ga_ls8c_ard_3-0-0_091083_2014-05-30_final
2014-05-31 11:04:09	ga_ls8c_ard_3-0-0_107082_2014-05-31_final
2014-05-31 11:04:33	ga_ls8c_ard_3-0-0_107083_2014-05-31_final
2014-06-05 09:44:15	ga_ls8c_ard_3-0-0_094083_2014-06-05_final
2014-06-05 11:23:08	ga_ls8c_ard_3-0-0_110083_2014-06-05_final
2014-06-06 10:27:32	ga_ls8c_ard_3-0-0_101083_2014-06-06_final
2014-06-07 09:31:55	ga_ls8c_ard_3-0-0_092083_2014-06-07_final
2014-06-07 11:10:24	ga_ls8c_ard_3-0-0_108082_2014-06-07_final
2014-06-07 11:10:48	ga_ls8c_ard_3-0-0_108083_2014-06-07_final
2014-06-08 10:15:11	ga_ls8c_ard_3-0-0_099083_2014-06-08_final
2014-06-09 09:19:10	ga_ls8c_ard_3-0-0_090082_2014-06-08_final
2014-06-09 09:19:34	ga_ls8c_ard_3-0-0_090083_2014-06-08_final
2014-06-09 10:58:03	ga_ls8c_ard_3-0-0_106082_2014-06-09_final
2014-06-09 10:58:27	ga_ls8c_ard_3-0-0_106083_2014-06-09_final
2022-09-11 10:09:56	ga_ls8c_ard_3-2-1_098083_2022-09-11_final
2022-09-12 09:14:19	ga_ls8c_ard_3-2-1_089083_2022-09-11_final
2022-09-12 10:52:49	ga_ls8c_ard_3-2-1_105082_2022-09-12_final
2022-09-12 10:53:12	ga_ls8c_ard_3-2-1_105083_2022-09-12_final
2022-09-13 09:57:36	ga_ls8c_ard_3-2-1_096083_2022-09-13_final
2022-09-13 11:36:29	ga_ls8c_ard_3-2-1_112083_2022-09-13_final
2022-09-17 11:11:46	ga_ls8c_ard_3-2-1_108083_2022-09-17_final
2022-09-18 10:16:09	ga_ls8c_ard_3-2-1_099083_2022-09-18_final
2022-09-19 09:20:32	ga_ls8c_ard_3-2-1_090083_2022-09-18_final
2022-09-21 09:08:11	ga_ls8c_ard_3-2-1_088083_2022-09-20_final
2022-09-21 10:46:40	ga_ls8c_ard_3-2-1_104082_2022-09-21_final
2022-09-22 09:51:27	ga_ls8c_ard_3-2-1_095083_2022-09-22_final
2022-09-22 11:30:20	ga_ls8c_ard_3-2-1_111083_2022-09-22_final
2022-09-24 09:39:05	ga_ls8c_ard_3-2-1_093083_2022-09-24_final
2022-09-24 11:17:34	ga_ls8c_ard_3-2-1_109082_2022-09-24_final
2022-09-24 11:17:58	ga_ls8c_ard_3-2-1_109083_2022-09-24_final
2022-09-25 08:43:04	ga_ls8c_ard_3-2-1_084082_2022-09-24_final
2022-09-25 10:22:21	ga_ls8c_ard_3-2-1_100083_2022-09-25_final
2022-09-26 09:26:43	ga_ls8c_ard_3-2-1_091083_2022-09-25_final
2022-09-26 11:05:36	ga_ls8c_ard_3-2-1_107083_2022-09-26_final
2022-09-27 10:09:59	ga_ls8c_ard_3-2-1_098083_2022-09-27_final
2022-09-28 09:14:21	ga_ls8c_ard_3-2-1_089083_2022-09-27_final
2022-09-28 10:53:14	ga_ls8c_ard_3-2-1_105083_2022-09-28_final
2022-09-29 09:57:37	ga_ls8c_ard_3-2-1_096083_2022-09-29_final
2022-09-29 11:36:30	ga_ls8c_ard_3-2-1_112083_2022-09-29_final
2022-10-02 10:28:30	ga_ls8c_ard_3-2-1_101083_2022-10-02_final
2022-10-03 09:32:53	ga_ls8c_ard_3-2-1_092083_2022-10-03_final
2022-10-03 11:11:46	ga_ls8c_ard_3-2-1_108083_2022-10-03_final
2022-10-21 09:20:28	ga_ls8c_ard_3-2-1_090083_2022-10-20_final
2022-10-21 10:59:21	ga_ls8c_ard_3-2-1_106083_2022-10-21_final
2022-10-22 10:03:45	ga_ls8c_ard_3-2-1_097083_2022-10-22_final
2022-10-22 11:42:38	ga_ls8c_ard_3-2-1_113083_2022-10-22_final
2022-10-23 09:08:08	ga_ls8c_ard_3-2-1_088083_2022-10-22_final
2022-10-24 09:51:24	ga_ls8c_ard_3-2-1_095083_2022-10-24_final
2022-10-24 11:30:17	ga_ls8c_ard_3-2-1_111083_2022-10-24_final
2022-10-26 09:39:03	ga_ls8c_ard_3-2-1_093083_2022-10-26_final
2022-10-26 11:17:56	ga_ls8c_ard_3-2-1_109083_2022-10-26_final
2022-10-27 10:22:19	ga_ls8c_ard_3-2-1_100083_2022-10-27_final
2022-10-28 09:26:42	ga_ls8c_ard_3-2-1_091083_2022-10-27_final
2022-10-28 11:05:35	ga_ls8c_ard_3-2-1_107083_2022-10-28_final
2022-10-29 10:09:58	ga_ls8c_ard_3-2-1_098083_2022-10-29_final
2022-10-30 09:14:21	ga_ls8c_ard_3-2-1_089083_2022-10-29_final
2022-11-20 11:11:40	ga_ls8c_ard_3-2-1_108083_2022-11-20_final
2022-11-21 10:16:03	ga_ls8c_ard_3-2-1_099083_2022-11-21_final
2022-11-22 09:20:26	ga_ls8c_ard_3-2-1_090083_2022-11-21_final
2022-11-22 10:59:19	ga_ls8c_ard_3-2-1_106083_2022-11-22_final
2022-11-23 10:03:42	ga_ls8c_ard_3-2-1_097083_2022-11-23_final
2022-11-23 11:42:35	ga_ls8c_ard_3-2-1_113083_2022-11-23_final
2022-11-24 09:08:05	ga_ls8c_ard_3-2-1_088083_2022-11-23_final
2022-11-25 09:51:21	ga_ls8c_ard_3-2-1_095083_2022-11-25_final
2022-11-27 11:17:52	ga_ls8c_ard_3-2-1_109083_2022-11-27_final
2022-11-28 10:22:15	ga_ls8c_ard_3-2-1_100083_2022-11-28_final
2022-11-29 09:26:38	ga_ls8c_ard_3-2-1_091083_2022-11-28_final
2022-11-29 11:05:31	ga_ls8c_ard_3-2-1_107083_2022-11-29_final
2022-11-30 10:09:54	ga_ls8c_ard_3-2-1_098083_2022-11-30_final
2022-12-02 11:36:25	ga_ls8c_ard_3-2-1_112083_2022-12-02_final
2022-12-04 09:45:10	ga_ls8c_ard_3-2-1_094083_2022-12-04_final
2022-12-06 11:11:41	ga_ls8c_ard_3-2-1_108083_2022-12-06_final
2022-12-07 10:16:04	ga_ls8c_ard_3-2-1_099083_2022-12-07_final
2023-04-06 09:25:45	ga_ls8c_ard_3-2-1_091083_2023-04-05_final
2023-04-06 11:04:38	ga_ls8c_ard_3-2-1_107083_2023-04-06_final
2023-04-07 10:08:59	ga_ls8c_ard_3-2-1_098083_2023-04-07_final
2023-04-08 09:13:21	ga_ls8c_ard_3-2-1_089083_2023-04-07_final
2023-04-09 09:56:35	ga_ls8c_ard_3-2-1_096083_2023-04-09_final
2023-04-09 11:35:28	ga_ls8c_ard_3-2-1_112083_2023-04-09_final
2023-04-11 09:44:10	ga_ls8c_ard_3-2-1_094083_2023-04-11_final
2023-04-15 09:19:27	ga_ls8c_ard_3-2-1_090083_2023-04-14_final
2023-04-15 10:58:20	ga_ls8c_ard_3-2-1_106083_2023-04-15_final
2023-04-16 10:02:42	ga_ls8c_ard_3-2-1_097083_2023-04-16_final
2023-04-16 11:41:35	ga_ls8c_ard_3-2-1_113083_2023-04-16_final
2023-04-17 09:07:04	ga_ls8c_ard_3-2-1_088083_2023-04-16_final
2023-04-18 09:50:19	ga_ls8c_ard_3-2-1_095083_2023-04-18_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