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
2019-08-04 09:57:03	ga_ls8c_ard_3-1-0_096083_2019-08-04_final
2019-08-04 09:57:27	ga_ls8c_ard_3-1-0_096084_2019-08-04_final
2019-08-04 11:35:56	ga_ls8c_ard_3-1-0_112083_2019-08-04_final
2019-08-04 11:36:20	ga_ls8c_ard_3-1-0_112084_2019-08-04_final
2019-08-05 10:40:19	ga_ls8c_ard_3-1-0_103083_2019-08-05_final
2019-08-22 09:44:47	ga_ls8c_ard_3-1-0_094083_2019-08-22_final
2019-08-22 09:45:11	ga_ls8c_ard_3-1-0_094084_2019-08-22_final
2019-08-22 11:23:40	ga_ls8c_ard_3-1-0_110083_2019-08-22_final
2019-08-22 11:24:04	ga_ls8c_ard_3-1-0_110084_2019-08-22_final
2019-08-23 10:28:03	ga_ls8c_ard_3-1-0_101083_2019-08-23_final
2019-08-23 10:28:27	ga_ls8c_ard_3-1-0_101084_2019-08-23_final
2019-08-24 09:32:25	ga_ls8c_ard_3-1-0_092083_2019-08-24_final
2019-08-24 09:32:49	ga_ls8c_ard_3-1-0_092084_2019-08-24_final
2019-08-24 11:11:19	ga_ls8c_ard_3-1-0_108083_2019-08-24_final
2019-08-24 11:11:42	ga_ls8c_ard_3-1-0_108084_2019-08-24_final
2019-10-30 10:03:33	ga_ls8c_ard_3-1-0_097083_2019-10-30_final
2019-10-30 10:03:57	ga_ls8c_ard_3-1-0_097084_2019-10-30_final
2019-10-30 11:42:26	ga_ls8c_ard_3-1-0_113083_2019-10-30_final
2019-10-30 11:42:50	ga_ls8c_ard_3-1-0_113084_2019-10-30_final
2019-10-31 09:07:55	ga_ls8c_ard_3-1-0_088083_2019-10-30_final
2019-10-31 09:08:19	ga_ls8c_ard_3-1-0_088084_2019-10-30_final
2019-10-31 10:46:48	ga_ls8c_ard_3-1-0_104083_2019-10-31_final
2019-11-01 09:51:11	ga_ls8c_ard_3-1-0_095083_2019-11-01_final
2019-11-01 09:51:35	ga_ls8c_ard_3-1-0_095084_2019-11-01_final
2019-11-01 11:30:04	ga_ls8c_ard_3-1-0_111083_2019-11-01_final
2019-11-01 11:30:28	ga_ls8c_ard_3-1-0_111084_2019-11-01_final
2019-11-02 10:34:27	ga_ls8c_ard_3-1-0_102083_2019-11-02_final
2019-11-22 10:09:39	ga_ls8c_ard_3-1-0_098083_2019-11-22_final
2019-11-22 10:10:03	ga_ls8c_ard_3-1-0_098084_2019-11-22_final
2019-11-23 09:14:02	ga_ls8c_ard_3-1-0_089083_2019-11-22_final
2019-11-23 09:14:26	ga_ls8c_ard_3-1-0_089084_2019-11-22_final
2019-11-23 10:52:55	ga_ls8c_ard_3-1-0_105083_2019-11-23_final
2019-11-24 09:57:17	ga_ls8c_ard_3-1-0_096083_2019-11-24_final
2019-11-24 09:57:41	ga_ls8c_ard_3-1-0_096084_2019-11-24_final
2019-11-24 11:36:34	ga_ls8c_ard_3-1-0_112084_2019-11-24_final
2019-11-25 10:40:33	ga_ls8c_ard_3-1-0_103083_2019-11-25_final
2022-01-22 10:58:57	ga_ls8c_ard_3-2-1_106083_2022-01-22_final
2022-01-23 10:03:44	ga_ls8c_ard_3-2-1_097084_2022-01-23_final
2022-01-23 11:42:13	ga_ls8c_ard_3-2-1_113083_2022-01-23_final
2022-01-23 11:42:37	ga_ls8c_ard_3-2-1_113084_2022-01-23_final
2022-01-24 09:07:42	ga_ls8c_ard_3-2-1_088083_2022-01-23_final
2022-01-25 09:50:57	ga_ls8c_ard_3-2-1_095083_2022-01-25_final
2022-01-25 09:51:21	ga_ls8c_ard_3-2-1_095084_2022-01-25_final
2022-03-30 09:50:56	ga_ls8c_ard_3-2-1_095084_2022-03-30_final
2022-03-30 11:29:49	ga_ls8c_ard_3-2-1_111084_2022-03-30_final
2022-04-01 09:38:34	ga_ls8c_ard_3-2-1_093084_2022-04-01_final
2022-04-01 11:17:27	ga_ls8c_ard_3-2-1_109084_2022-04-01_final
2022-04-05 09:13:52	ga_ls8c_ard_3-2-1_089084_2022-04-04_final
2022-04-06 09:57:09	ga_ls8c_ard_3-2-1_096084_2022-04-06_final
2022-04-06 11:36:02	ga_ls8c_ard_3-2-1_112084_2022-04-06_final
2022-04-25 10:27:40	ga_ls8c_ard_3-2-1_101083_2022-04-25_final
2022-04-26 09:32:02	ga_ls8c_ard_3-2-1_092083_2022-04-26_final
2022-04-26 09:32:26	ga_ls8c_ard_3-2-1_092084_2022-04-26_final
2022-04-26 11:10:55	ga_ls8c_ard_3-2-1_108083_2022-04-26_final
2022-04-26 11:11:19	ga_ls8c_ard_3-2-1_108084_2022-04-26_final
2022-04-27 10:15:17	ga_ls8c_ard_3-2-1_099083_2022-04-27_final
2022-04-27 10:15:41	ga_ls8c_ard_3-2-1_099084_2022-04-27_final
2022-04-28 09:19:39	ga_ls8c_ard_3-2-1_090083_2022-04-27_final
2022-04-28 09:20:03	ga_ls8c_ard_3-2-1_090084_2022-04-27_final
2022-04-28 10:58:32	ga_ls8c_ard_3-2-1_106083_2022-04-28_final
2022-04-29 10:02:54	ga_ls8c_ard_3-2-1_097083_2022-04-29_final
2022-04-29 10:03:18	ga_ls8c_ard_3-2-1_097084_2022-04-29_final
2022-04-29 11:41:48	ga_ls8c_ard_3-2-1_113083_2022-04-29_final
2022-04-29 11:42:11	ga_ls8c_ard_3-2-1_113084_2022-04-29_final
2022-04-30 09:07:18	ga_ls8c_ard_3-2-1_088083_2022-04-29_final
2022-05-01 09:50:35	ga_ls8c_ard_3-2-1_095083_2022-05-01_final
2022-05-01 09:50:59	ga_ls8c_ard_3-2-1_095084_2022-05-01_final
2022-05-01 11:29:28	ga_ls8c_ard_3-2-1_111083_2022-05-01_final
2022-05-01 11:29:52	ga_ls8c_ard_3-2-1_111084_2022-05-01_final
2022-05-03 09:38:15	ga_ls8c_ard_3-2-1_093083_2022-05-03_final
2022-05-03 09:38:39	ga_ls8c_ard_3-2-1_093084_2022-05-03_final
2022-05-03 11:17:08	ga_ls8c_ard_3-2-1_109083_2022-05-03_final
2022-05-03 11:17:32	ga_ls8c_ard_3-2-1_109084_2022-05-03_final
2022-05-04 10:21:31	ga_ls8c_ard_3-2-1_100083_2022-05-04_final
2022-05-04 10:21:55	ga_ls8c_ard_3-2-1_100084_2022-05-04_final
2022-06-02 11:30:05	ga_ls8c_ard_3-2-1_111084_2022-06-02_final
2022-06-04 09:38:52	ga_ls8c_ard_3-2-1_093084_2022-06-04_final
2022-06-04 11:17:21	ga_ls8c_ard_3-2-1_109083_2022-06-04_final
2022-06-04 11:17:45	ga_ls8c_ard_3-2-1_109084_2022-06-04_final
2022-06-05 10:21:45	ga_ls8c_ard_3-2-1_100083_2022-06-05_final
2022-06-05 10:22:09	ga_ls8c_ard_3-2-1_100084_2022-06-05_final
2022-06-06 09:26:32	ga_ls8c_ard_3-2-1_091084_2022-06-05_final
2022-06-06 11:05:01	ga_ls8c_ard_3-2-1_107083_2022-06-06_final
2022-06-06 11:05:25	ga_ls8c_ard_3-2-1_107084_2022-06-06_final
2022-06-07 10:09:25	ga_ls8c_ard_3-2-1_098083_2022-06-07_final
2022-06-07 10:09:49	ga_ls8c_ard_3-2-1_098084_2022-06-07_final
2022-06-08 09:13:48	ga_ls8c_ard_3-2-1_089083_2022-06-07_final
2022-06-08 09:14:12	ga_ls8c_ard_3-2-1_089084_2022-06-07_final
2022-06-08 10:52:41	ga_ls8c_ard_3-2-1_105083_2022-06-08_final
2022-06-11 09:44:44	ga_ls8c_ard_3-2-1_094083_2022-06-11_final
2022-06-11 09:45:08	ga_ls8c_ard_3-2-1_094084_2022-06-11_final
2022-06-11 11:23:38	ga_ls8c_ard_3-2-1_110083_2022-06-11_final
2022-06-11 11:24:01	ga_ls8c_ard_3-2-1_110084_2022-06-11_final
2022-06-12 10:28:01	ga_ls8c_ard_3-2-1_101083_2022-06-12_final
2022-06-13 09:32:24	ga_ls8c_ard_3-2-1_092083_2022-06-13_final
2022-06-13 09:32:48	ga_ls8c_ard_3-2-1_092084_2022-06-13_final
2022-06-13 11:11:17	ga_ls8c_ard_3-2-1_108083_2022-06-13_final
2022-06-13 11:11:41	ga_ls8c_ard_3-2-1_108084_2022-06-13_final
2022-06-18 11:30:16	ga_ls8c_ard_3-2-1_111084_2022-06-18_final
2022-06-20 09:38:38	ga_ls8c_ard_3-2-1_093083_2022-06-20_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