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
2018-08-17 09:56:01	ga_ls8c_ard_3-0-0_096082_2018-08-17_final
2018-08-17 09:56:25	ga_ls8c_ard_3-0-0_096083_2018-08-17_final
2018-08-17 11:34:54	ga_ls8c_ard_3-0-0_112082_2018-08-17_final
2018-08-17 11:35:18	ga_ls8c_ard_3-0-0_112083_2018-08-17_final
2018-08-18 10:39:17	ga_ls8c_ard_3-0-0_103082_2018-08-18_final
2018-08-18 10:39:41	ga_ls8c_ard_3-0-0_103083_2018-08-18_final
2018-08-19 09:43:41	ga_ls8c_ard_3-0-0_094082_2018-08-19_final
2018-08-19 09:44:04	ga_ls8c_ard_3-0-0_094083_2018-08-19_final
2018-08-19 11:22:34	ga_ls8c_ard_3-0-0_110082_2018-08-19_final
2018-08-19 11:22:58	ga_ls8c_ard_3-0-0_110083_2018-08-19_final
2018-08-20 10:26:57	ga_ls8c_ard_3-0-0_101082_2018-08-20_final
2018-08-20 10:27:21	ga_ls8c_ard_3-0-0_101083_2018-08-20_final
2018-09-04 09:43:47	ga_ls8c_ard_3-0-0_094082_2018-09-04_final
2018-09-04 09:44:11	ga_ls8c_ard_3-0-0_094083_2018-09-04_final
2018-09-04 11:22:40	ga_ls8c_ard_3-0-0_110082_2018-09-04_final
2018-09-04 11:23:04	ga_ls8c_ard_3-0-0_110083_2018-09-04_final
2018-09-05 10:27:03	ga_ls8c_ard_3-1-0_101082_2018-09-05_final
2018-09-05 10:27:27	ga_ls8c_ard_3-0-0_101083_2018-09-05_final
2018-09-16 10:08:58	ga_ls8c_ard_3-0-0_098083_2018-09-16_final
2018-09-17 09:12:56	ga_ls8c_ard_3-0-0_089082_2018-09-16_final
2018-09-17 09:13:20	ga_ls8c_ard_3-0-0_089083_2018-09-16_final
2018-09-17 10:51:49	ga_ls8c_ard_3-0-0_105082_2018-09-17_final
2018-09-17 10:52:13	ga_ls8c_ard_3-0-0_105083_2018-09-17_final
2019-01-06 10:09:12	ga_ls8c_ard_3-0-0_098083_2019-01-06_final
2019-01-07 09:13:10	ga_ls8c_ard_3-0-0_089082_2019-01-06_final
2019-01-07 09:13:34	ga_ls8c_ard_3-0-0_089083_2019-01-06_final
2019-01-07 10:52:03	ga_ls8c_ard_3-0-0_105082_2019-01-07_final
2019-01-07 10:52:27	ga_ls8c_ard_3-0-0_105083_2019-01-07_final
2019-07-08 10:15:02	ga_ls8c_ard_3-1-0_099082_2019-07-08_final
2019-07-08 10:15:26	ga_ls8c_ard_3-1-0_099083_2019-07-08_final
2019-07-09 09:19:49	ga_ls8c_ard_3-1-0_090083_2019-07-08_final
2019-07-09 10:58:18	ga_ls8c_ard_3-1-0_106082_2019-07-09_final
2019-07-09 10:58:42	ga_ls8c_ard_3-1-0_106083_2019-07-09_final
2019-07-10 10:02:41	ga_ls8c_ard_3-1-0_097082_2019-07-10_final
2019-07-10 10:03:05	ga_ls8c_ard_3-1-0_097083_2019-07-10_final
2019-07-10 11:41:34	ga_ls8c_ard_3-1-0_113082_2019-07-10_final
2019-07-10 11:41:58	ga_ls8c_ard_3-1-0_113083_2019-07-10_final
2019-07-11 09:07:04	ga_ls8c_ard_3-1-0_088082_2019-07-10_final
2019-07-11 09:07:28	ga_ls8c_ard_3-1-0_088083_2019-07-10_final
2019-07-11 10:45:57	ga_ls8c_ard_3-1-0_104082_2019-07-11_final
2019-07-11 10:46:21	ga_ls8c_ard_3-1-0_104083_2019-07-11_final
2019-08-04 09:56:39	ga_ls8c_ard_3-1-0_096082_2019-08-04_final
2019-08-04 09:57:03	ga_ls8c_ard_3-1-0_096083_2019-08-04_final
2019-08-04 11:35:32	ga_ls8c_ard_3-1-0_112082_2019-08-04_final
2019-08-04 11:35:56	ga_ls8c_ard_3-1-0_112083_2019-08-04_final
2019-08-05 10:39:55	ga_ls8c_ard_3-1-0_103082_2019-08-05_final
2019-08-05 10:40:19	ga_ls8c_ard_3-1-0_103083_2019-08-05_final
2019-08-25 10:15:17	ga_ls8c_ard_3-1-0_099082_2019-08-25_final
2019-08-25 10:15:41	ga_ls8c_ard_3-1-0_099083_2019-08-25_final
2019-08-26 09:19:40	ga_ls8c_ard_3-1-0_090082_2019-08-25_final
2019-08-26 09:20:04	ga_ls8c_ard_3-1-0_090083_2019-08-25_final
2019-08-26 10:58:33	ga_ls8c_ard_3-1-0_106082_2019-08-26_final
2019-08-26 10:58:57	ga_ls8c_ard_3-1-0_106083_2019-08-26_final
2019-08-27 10:02:56	ga_ls8c_ard_3-1-0_097082_2019-08-27_final
2019-08-27 10:03:20	ga_ls8c_ard_3-1-0_097083_2019-08-27_final
2019-08-27 11:41:49	ga_ls8c_ard_3-1-0_113082_2019-08-27_final
2019-08-27 11:42:13	ga_ls8c_ard_3-1-0_113083_2019-08-27_final
2019-08-28 09:07:19	ga_ls8c_ard_3-1-0_088082_2019-08-27_final
2019-08-28 09:07:43	ga_ls8c_ard_3-1-0_088083_2019-08-27_final
2019-08-28 10:46:12	ga_ls8c_ard_3-1-0_104082_2019-08-28_final
2019-08-28 10:46:36	ga_ls8c_ard_3-1-0_104083_2019-08-28_final
2019-09-19 10:09:14	ga_ls8c_ard_3-1-0_098082_2019-09-19_final
2019-09-19 10:09:38	ga_ls8c_ard_3-1-0_098083_2019-09-19_final
2019-09-20 09:13:37	ga_ls8c_ard_3-1-0_089082_2019-09-19_final
2019-09-20 09:14:01	ga_ls8c_ard_3-1-0_089083_2019-09-19_final
2019-09-20 10:52:30	ga_ls8c_ard_3-1-0_105082_2019-09-20_final
2019-09-20 10:52:54	ga_ls8c_ard_3-1-0_105083_2019-09-20_final
2019-09-21 09:56:53	ga_ls8c_ard_3-1-0_096082_2019-09-21_final
2019-09-21 09:57:17	ga_ls8c_ard_3-1-0_096083_2019-09-21_final
2019-09-21 11:35:46	ga_ls8c_ard_3-1-0_112082_2019-09-21_final
2019-09-21 11:36:10	ga_ls8c_ard_3-1-0_112083_2019-09-21_final
2019-09-22 10:40:33	ga_ls8c_ard_3-1-0_103083_2019-09-22_final
2019-09-30 09:50:45	ga_ls8c_ard_3-1-0_095082_2019-09-30_final
2019-09-30 09:51:09	ga_ls8c_ard_3-1-0_095083_2019-09-30_final
2019-09-30 11:29:38	ga_ls8c_ard_3-1-0_111082_2019-09-30_final
2019-09-30 11:30:02	ga_ls8c_ard_3-1-0_111083_2019-09-30_final
2019-10-01 10:34:01	ga_ls8c_ard_3-1-0_102082_2019-10-01_final
2019-10-01 10:34:24	ga_ls8c_ard_3-1-0_102083_2019-10-01_final
2019-10-02 09:38:23	ga_ls8c_ard_3-1-0_093082_2019-10-02_final
2019-10-02 09:38:47	ga_ls8c_ard_3-1-0_093083_2019-10-02_final
2019-10-02 11:17:16	ga_ls8c_ard_3-1-0_109082_2019-10-02_final
2019-10-02 11:17:40	ga_ls8c_ard_3-1-0_109083_2019-10-02_final
2019-10-03 08:42:46	ga_ls8c_ard_3-2-1_084082_2019-10-02_final
2019-10-03 10:21:39	ga_ls8c_ard_3-1-0_100082_2019-10-03_final
2019-10-03 10:22:03	ga_ls8c_ard_3-1-0_100083_2019-10-03_final
2022-08-19 10:03:41	ga_ls8c_ard_3-2-1_097083_2022-08-19_final
2022-08-19 11:42:10	ga_ls8c_ard_3-2-1_113082_2022-08-19_final
2022-08-19 11:42:34	ga_ls8c_ard_3-2-1_113083_2022-08-19_final
2022-08-20 09:07:40	ga_ls8c_ard_3-2-1_088082_2022-08-19_final
2022-08-20 09:08:04	ga_ls8c_ard_3-2-1_088083_2022-08-19_final
2022-08-21 09:50:56	ga_ls8c_ard_3-2-1_095082_2022-08-21_final
2022-08-21 09:51:20	ga_ls8c_ard_3-2-1_095083_2022-08-21_final
2022-08-21 11:29:49	ga_ls8c_ard_3-2-1_111082_2022-08-21_final
2022-08-21 11:30:13	ga_ls8c_ard_3-2-1_111083_2022-08-21_final
2022-08-22 10:34:12	ga_ls8c_ard_3-2-1_102082_2022-08-22_final
2022-10-06 11:42:14	ga_ls8c_ard_3-2-1_113082_2022-10-06_final
2022-10-06 11:42:38	ga_ls8c_ard_3-2-1_113083_2022-10-06_final
2022-10-07 09:07:43	ga_ls8c_ard_3-2-1_088082_2022-10-06_final
2022-10-07 09:08:07	ga_ls8c_ard_3-2-1_088083_2022-10-06_final
2022-10-07 10:46:36	ga_ls8c_ard_3-2-1_104082_2022-10-07_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