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
2018-09-16 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
2019-01-06 10:09:12	ga_ls8c_ard_3-0-0_098083_2019-01-06_final
2019-01-06 10:09:36	ga_ls8c_ard_3-0-0_098084_2019-01-06_final
2019-01-07 09:13:34	ga_ls8c_ard_3-0-0_089083_2019-01-06_final
2019-01-07 09:13:58	ga_ls8c_ard_3-0-0_089084_2019-01-06_final
2019-01-07 10:52:27	ga_ls8c_ard_3-0-0_105083_2019-01-07_final
2019-06-26 09:50:40	ga_ls8c_ard_3-1-0_095083_2019-06-26_final
2019-06-26 09:51:04	ga_ls8c_ard_3-1-0_095084_2019-06-26_final
2019-06-26 11:29:34	ga_ls8c_ard_3-1-0_111083_2019-06-26_final
2019-06-26 11:29:57	ga_ls8c_ard_3-1-0_111084_2019-06-26_final
2019-06-27 10:33:56	ga_ls8c_ard_3-1-0_102083_2019-06-27_final
2019-06-28 09:38:19	ga_ls8c_ard_3-1-0_093083_2019-06-28_final
2019-06-28 09:38:43	ga_ls8c_ard_3-1-0_093084_2019-06-28_final
2019-06-28 11:17:12	ga_ls8c_ard_3-1-0_109083_2019-06-28_final
2019-06-28 11:17:36	ga_ls8c_ard_3-1-0_109084_2019-06-28_final
2019-06-29 10:21:35	ga_ls8c_ard_3-1-0_100083_2019-06-29_final
2019-06-29 10:21:59	ga_ls8c_ard_3-1-0_100084_2019-06-29_final
2019-08-13 09:50:55	ga_ls8c_ard_3-1-0_095083_2019-08-13_final
2019-08-13 09:51:19	ga_ls8c_ard_3-1-0_095084_2019-08-13_final
2019-08-13 11:29:48	ga_ls8c_ard_3-1-0_111083_2019-08-13_final
2019-08-13 11:30:12	ga_ls8c_ard_3-1-0_111084_2019-08-13_final
2019-08-14 10:34:11	ga_ls8c_ard_3-1-0_102083_2019-08-14_final
2019-08-15 09:38:34	ga_ls8c_ard_3-1-0_093083_2019-08-15_final
2019-08-15 09:38:58	ga_ls8c_ard_3-1-0_093084_2019-08-15_final
2019-08-15 11:17:27	ga_ls8c_ard_3-1-0_109083_2019-08-15_final
2019-08-15 11:17:51	ga_ls8c_ard_3-1-0_109084_2019-08-15_final
2019-08-16 10:21:50	ga_ls8c_ard_3-1-0_100083_2019-08-16_final
2019-08-16 10:22:14	ga_ls8c_ard_3-1-0_100084_2019-08-16_final
2019-08-25 10:15:41	ga_ls8c_ard_3-1-0_099083_2019-08-25_final
2019-08-25 10:16:05	ga_ls8c_ard_3-1-0_099084_2019-08-25_final
2019-08-26 09:20:04	ga_ls8c_ard_3-1-0_090083_2019-08-25_final
2019-08-26 09:20:28	ga_ls8c_ard_3-1-0_090084_2019-08-25_final
2019-08-26 10:58:57	ga_ls8c_ard_3-1-0_106083_2019-08-26_final
2019-08-26 10:59:21	ga_ls8c_ard_3-1-0_106084_2019-08-26_final
2019-08-27 10:03:20	ga_ls8c_ard_3-1-0_097083_2019-08-27_final
2019-08-27 10:03:44	ga_ls8c_ard_3-1-0_097084_2019-08-27_final
2019-08-27 11:42:13	ga_ls8c_ard_3-1-0_113083_2019-08-27_final
2019-08-27 11:42:37	ga_ls8c_ard_3-1-0_113084_2019-08-27_final
2019-08-28 09:07:43	ga_ls8c_ard_3-1-0_088083_2019-08-27_final
2019-08-28 09:08:07	ga_ls8c_ard_3-1-0_088084_2019-08-27_final
2019-08-28 10:46:36	ga_ls8c_ard_3-1-0_104083_2019-08-28_final
2019-09-26 10:15:51	ga_ls8c_ard_3-1-0_099083_2019-09-26_final
2019-09-26 10:16:15	ga_ls8c_ard_3-1-0_099084_2019-09-26_final
2019-09-27 09:20:14	ga_ls8c_ard_3-1-0_090083_2019-09-26_final
2019-09-27 09:20:38	ga_ls8c_ard_3-1-0_090084_2019-09-26_final
2019-09-27 10:59:07	ga_ls8c_ard_3-1-0_106083_2019-09-27_final
2019-09-27 10:59:31	ga_ls8c_ard_3-1-0_106084_2019-09-27_final
2019-09-28 10:03:30	ga_ls8c_ard_3-1-0_097083_2019-09-28_final
2019-09-28 10:03:54	ga_ls8c_ard_3-1-0_097084_2019-09-28_final
2019-09-28 11:42:23	ga_ls8c_ard_3-1-0_113083_2019-09-28_final
2019-09-28 11:42:47	ga_ls8c_ard_3-1-0_113084_2019-09-28_final
2019-09-29 09:07:53	ga_ls8c_ard_3-1-0_088083_2019-09-28_final
2019-09-29 09:08:17	ga_ls8c_ard_3-1-0_088084_2019-09-28_final
2019-09-29 10:46:46	ga_ls8c_ard_3-1-0_104083_2019-09-29_final
2019-09-30 09:51:09	ga_ls8c_ard_3-1-0_095083_2019-09-30_final
2019-09-30 09:51:33	ga_ls8c_ard_3-1-0_095084_2019-09-30_final
2019-09-30 11:30:02	ga_ls8c_ard_3-1-0_111083_2019-09-30_final
2019-09-30 11:30:26	ga_ls8c_ard_3-1-0_111084_2019-09-30_final
2019-10-01 10:34:24	ga_ls8c_ard_3-1-0_102083_2019-10-01_final
2019-10-02 09:38:47	ga_ls8c_ard_3-1-0_093083_2019-10-02_final
2019-10-02 09:39:11	ga_ls8c_ard_3-1-0_093084_2019-10-02_final
2019-10-02 11:17:40	ga_ls8c_ard_3-1-0_109083_2019-10-02_final
2019-10-02 11:18:04	ga_ls8c_ard_3-1-0_109084_2019-10-02_final
2019-10-03 10:22:03	ga_ls8c_ard_3-1-0_100083_2019-10-03_final
2019-10-03 10:22:27	ga_ls8c_ard_3-1-0_100084_2019-10-03_final
2022-12-06 09:32:48	ga_ls8c_ard_3-2-1_092083_2022-12-06_final
2022-12-06 09:33:12	ga_ls8c_ard_3-2-1_092084_2022-12-06_final
2022-12-06 11:11:41	ga_ls8c_ard_3-2-1_108083_2022-12-06_final
2022-12-06 11:12:05	ga_ls8c_ard_3-2-1_108084_2022-12-06_final
2022-12-20 09:45:02	ga_ls8c_ard_3-2-1_094083_2022-12-20_final
2022-12-20 09:45:26	ga_ls8c_ard_3-2-1_094084_2022-12-20_final
2022-12-29 11:17:44	ga_ls8c_ard_3-2-1_109083_2022-12-29_final
2022-12-29 11:18:08	ga_ls8c_ard_3-2-1_109084_2022-12-29_final
2022-12-30 10:22:06	ga_ls8c_ard_3-2-1_100083_2022-12-30_final
2022-12-30 10:22:30	ga_ls8c_ard_3-2-1_100084_2022-12-30_final
2022-12-31 09:26:29	ga_ls8c_ard_3-2-1_091083_2022-12-30_final
2022-12-31 09:26:53	ga_ls8c_ard_3-2-1_091084_2022-12-30_final
2022-12-31 11:05:22	ga_ls8c_ard_3-2-1_107083_2022-12-31_final
2022-12-31 11:05:46	ga_ls8c_ard_3-2-1_107084_2022-12-31_final
2023-01-01 10:09:45	ga_ls8c_ard_3-2-1_098083_2023-01-01_final
2023-01-01 10:10:09	ga_ls8c_ard_3-2-1_098084_2023-01-01_final
2023-01-02 09:14:08	ga_ls8c_ard_3-2-1_089083_2023-01-01_final
2023-01-02 09:14:32	ga_ls8c_ard_3-2-1_089084_2023-01-01_final
2023-01-02 10:53:01	ga_ls8c_ard_3-2-1_105083_2023-01-02_final
2023-01-03 09:57:23	ga_ls8c_ard_3-2-1_096083_2023-01-03_final
2023-01-03 09:57:47	ga_ls8c_ard_3-2-1_096084_2023-01-03_final
2023-01-03 11:36:16	ga_ls8c_ard_3-2-1_112083_2023-01-03_final
2023-01-03 11:36:40	ga_ls8c_ard_3-2-1_112084_2023-01-03_final
2023-01-12 09:51:33	ga_ls8c_ard_3-2-1_095084_2023-01-12_final
2023-01-12 11:30:02	ga_ls8c_ard_3-2-1_111083_2023-01-12_final
2023-01-12 11:30:26	ga_ls8c_ard_3-2-1_111084_2023-01-12_final
2023-01-19 09:57:16	ga_ls8c_ard_3-2-1_096083_2023-01-19_final
2023-01-19 09:57:40	ga_ls8c_ard_3-2-1_096084_2023-01-19_final
2023-01-19 11:36:09	ga_ls8c_ard_3-2-1_112083_2023-01-19_final
2023-01-19 11:36:33	ga_ls8c_ard_3-2-1_112084_2023-01-19_final
2023-01-21 09:44:56	ga_ls8c_ard_3-2-1_094083_2023-01-21_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