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
2018-03-08 10:09:22	ga_ls8c_ard_3-0-0_098084_2018-03-08_final
2018-03-09 09:13:44	ga_ls8c_ard_3-0-0_089084_2018-03-08_final
2018-03-24 10:09:14	ga_ls8c_ard_3-0-0_098084_2018-03-24_final
2018-03-25 09:13:37	ga_ls8c_ard_3-0-0_089084_2018-03-24_final
2018-04-09 10:09:07	ga_ls8c_ard_3-0-0_098084_2018-04-09_final
2018-04-10 09:13:29	ga_ls8c_ard_3-0-0_089084_2018-04-09_final
2018-05-10 09:25:33	ga_ls8c_ard_3-0-0_091084_2018-05-09_final
2018-05-10 11:04:26	ga_ls8c_ard_3-0-0_107084_2018-05-10_final
2018-05-11 10:08:48	ga_ls8c_ard_3-0-0_098084_2018-05-11_final
2018-05-12 09:13:10	ga_ls8c_ard_3-0-0_089084_2018-05-11_final
2018-05-13 09:56:25	ga_ls8c_ard_3-0-0_096084_2018-05-13_final
2018-05-13 11:35:18	ga_ls8c_ard_3-0-0_112084_2018-05-13_final
2018-05-15 09:44:02	ga_ls8c_ard_3-0-0_094084_2018-05-15_final
2018-05-15 11:22:55	ga_ls8c_ard_3-0-0_110084_2018-05-15_final
2018-05-16 10:27:17	ga_ls8c_ard_3-0-0_101084_2018-05-16_final
2018-05-17 09:31:39	ga_ls8c_ard_3-0-0_092084_2018-05-17_final
2018-05-17 11:10:32	ga_ls8c_ard_3-0-0_108084_2018-05-17_final
2018-09-16 10:08:58	ga_ls8c_ard_3-0-0_098083_2018-09-16_final
2018-09-16 10:09:21	ga_ls8c_ard_3-0-0_098084_2018-09-16_final
2018-09-17 09:13:20	ga_ls8c_ard_3-0-0_089083_2018-09-16_final
2018-09-17 09:13:44	ga_ls8c_ard_3-0-0_089084_2018-09-16_final
2018-09-17 10:52:13	ga_ls8c_ard_3-0-0_105083_2018-09-17_final
2018-11-30 09:50:43	ga_ls8c_ard_3-0-0_095083_2018-11-30_final
2018-11-30 09:51:07	ga_ls8c_ard_3-0-0_095084_2018-11-30_final
2018-11-30 11:30:00	ga_ls8c_ard_3-0-0_111084_2018-11-30_final
2018-12-02 09:38:21	ga_ls8c_ard_3-0-0_093083_2018-12-02_final
2018-12-02 09:38:45	ga_ls8c_ard_3-0-0_093084_2018-12-02_final
2018-12-02 11:17:14	ga_ls8c_ard_3-0-0_109083_2018-12-02_final
2018-12-02 11:17:38	ga_ls8c_ard_3-0-0_109084_2018-12-02_final
2018-12-03 10:22:00	ga_ls8c_ard_3-0-0_100084_2018-12-03_final
2018-12-16 09:51:04	ga_ls8c_ard_3-0-0_095084_2018-12-16_final
2018-12-16 11:29:57	ga_ls8c_ard_3-0-0_111084_2018-12-16_final
2018-12-17 10:33:55	ga_ls8c_ard_3-0-0_102083_2018-12-17_final
2018-12-18 09:38:18	ga_ls8c_ard_3-0-0_093083_2018-12-18_final
2018-12-18 09:38:42	ga_ls8c_ard_3-0-0_093084_2018-12-18_final
2018-12-18 11:17:11	ga_ls8c_ard_3-0-0_109083_2018-12-18_final
2018-12-18 11:17:35	ga_ls8c_ard_3-0-0_109084_2018-12-18_final
2018-12-19 10:21:34	ga_ls8c_ard_3-0-0_100083_2018-12-19_final
2018-12-19 10:21:58	ga_ls8c_ard_3-0-0_100084_2018-12-19_final
2018-12-23 09:57:15	ga_ls8c_ard_3-0-0_096084_2018-12-23_final
2018-12-23 11:36:08	ga_ls8c_ard_3-0-0_112084_2018-12-23_final
2018-12-25 09:44:53	ga_ls8c_ard_3-0-0_094084_2018-12-25_final
2018-12-25 11:23:46	ga_ls8c_ard_3-0-0_110084_2018-12-25_final
2018-12-26 10:28:09	ga_ls8c_ard_3-0-0_101084_2018-12-26_final
2019-01-06 10:09:36	ga_ls8c_ard_3-0-0_098084_2019-01-06_final
2019-01-07 09:13:58	ga_ls8c_ard_3-0-0_089084_2019-01-06_final
2022-11-23 11:42:35	ga_ls8c_ard_3-2-1_113083_2022-11-23_final
2022-11-25 09:51:45	ga_ls8c_ard_3-2-1_095084_2022-11-25_final
2022-12-02 11:36:49	ga_ls8c_ard_3-2-1_112084_2022-12-02_final
2022-12-04 09:45:34	ga_ls8c_ard_3-2-1_094084_2022-12-04_final
2023-01-05 09:45:25	ga_ls8c_ard_3-2-1_094084_2023-01-05_final
2023-01-05 11:24:18	ga_ls8c_ard_3-2-1_110084_2023-01-05_final
2023-01-08 10:16:19	ga_ls8c_ard_3-2-1_099084_2023-01-08_final
2023-06-05 11:29:26	ga_ls8c_ard_3-2-1_111084_2023-06-05_final
2023-06-07 09:38:13	ga_ls8c_ard_3-2-1_093084_2023-06-07_final
2023-06-07 11:16:42	ga_ls8c_ard_3-2-1_109083_2023-06-07_final
2023-06-09 09:25:53	ga_ls8c_ard_3-2-1_091084_2023-06-08_final
2023-06-15 10:27:20	ga_ls8c_ard_3-2-1_101083_2023-06-15_final
2023-06-16 09:32:07	ga_ls8c_ard_3-2-1_092084_2023-06-16_final
2023-06-16 11:10:36	ga_ls8c_ard_3-2-1_108083_2023-06-16_final
2023-06-16 11:11:00	ga_ls8c_ard_3-2-1_108084_2023-06-16_final
2023-07-12 10:09:02	ga_ls8c_ard_3-2-1_098083_2023-07-12_final
2023-07-12 10:09:26	ga_ls8c_ard_3-2-1_098084_2023-07-12_final
2023-07-14 11:35:58	ga_ls8c_ard_3-2-1_112084_2023-07-14_final
2023-07-16 09:44:19	ga_ls8c_ard_3-2-1_094083_2023-07-16_final
2023-07-16 09:44:43	ga_ls8c_ard_3-2-1_094084_2023-07-16_final
2023-07-16 11:23:12	ga_ls8c_ard_3-2-1_110083_2023-07-16_final
2023-07-16 11:23:36	ga_ls8c_ard_3-2-1_110084_2023-07-16_final
2023-07-17 10:27:35	ga_ls8c_ard_3-2-1_101083_2023-07-17_final
2023-07-20 09:19:35	ga_ls8c_ard_3-2-1_090083_2023-07-19_final
2023-07-20 09:19:59	ga_ls8c_ard_3-2-1_090084_2023-07-19_final
2023-07-20 10:58:28	ga_ls8c_ard_3-2-1_106083_2023-07-20_final
2023-07-21 10:02:51	ga_ls8c_ard_3-2-1_097083_2023-07-21_final
2023-07-21 10:03:15	ga_ls8c_ard_3-2-1_097084_2023-07-21_final
2023-07-21 11:41:44	ga_ls8c_ard_3-2-1_113083_2023-07-21_final
2023-07-21 11:42:08	ga_ls8c_ard_3-2-1_113084_2023-07-21_final
2023-07-23 09:50:56	ga_ls8c_ard_3-2-1_095084_2023-07-23_final
2023-07-23 11:29:25	ga_ls8c_ard_3-2-1_111083_2023-07-23_final
2023-07-23 11:29:49	ga_ls8c_ard_3-2-1_111084_2023-07-23_final
2023-07-25 09:38:12	ga_ls8c_ard_3-2-1_093083_2023-07-25_final
2023-07-25 09:38:36	ga_ls8c_ard_3-2-1_093084_2023-07-25_final
2023-07-25 11:17:29	ga_ls8c_ard_3-2-1_109084_2023-07-25_final
2023-07-26 10:21:52	ga_ls8c_ard_3-2-1_100084_2023-07-26_final
2023-07-27 09:26:16	ga_ls8c_ard_3-2-1_091084_2023-07-26_final
2023-08-17 09:44:33	ga_ls8c_ard_3-2-1_094083_2023-08-17_final
2023-08-17 09:44:57	ga_ls8c_ard_3-2-1_094084_2023-08-17_final
2023-08-17 11:23:26	ga_ls8c_ard_3-2-1_110083_2023-08-17_final
2023-08-17 11:23:50	ga_ls8c_ard_3-2-1_110084_2023-08-17_final
2023-08-19 09:32:13	ga_ls8c_ard_3-2-1_092083_2023-08-19_final
2023-08-19 09:32:37	ga_ls8c_ard_3-2-1_092084_2023-08-19_final
2023-08-19 11:11:30	ga_ls8c_ard_3-2-1_108084_2023-08-19_final
2023-08-20 10:15:29	ga_ls8c_ard_3-2-1_099083_2023-08-20_final
2023-08-20 10:15:53	ga_ls8c_ard_3-2-1_099084_2023-08-20_final
2023-08-21 09:20:16	ga_ls8c_ard_3-2-1_090084_2023-08-20_final
2023-08-27 10:21:42	ga_ls8c_ard_3-2-1_100083_2023-08-27_final
2023-08-27 10:22:06	ga_ls8c_ard_3-2-1_100084_2023-08-27_final
2023-08-28 09:26:28	ga_ls8c_ard_3-2-1_091084_2023-08-27_final
2023-08-28 11:04:57	ga_ls8c_ard_3-2-1_107083_2023-08-28_final
2023-08-28 11:05:21	ga_ls8c_ard_3-2-1_107084_2023-08-28_final
2023-08-30 09:14:07	ga_ls8c_ard_3-2-1_089084_2023-08-29_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