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
2018-05-29 09:55:48	ga_ls8c_ard_3-0-0_096083_2018-05-29_final
2018-05-29 11:34:41	ga_ls8c_ard_3-0-0_112083_2018-05-29_final
2018-05-30 10:39:03	ga_ls8c_ard_3-0-0_103083_2018-05-30_final
2018-05-31 09:43:25	ga_ls8c_ard_3-0-0_094083_2018-05-31_final
2018-05-31 11:22:18	ga_ls8c_ard_3-0-0_110083_2018-05-31_final
2018-06-01 10:26:16	ga_ls8c_ard_3-0-0_101082_2018-06-01_final
2018-06-01 10:26:40	ga_ls8c_ard_3-0-0_101083_2018-06-01_final
2018-07-16 09:55:45	ga_ls8c_ard_3-0-0_096082_2018-07-16_final
2018-07-16 09:56:09	ga_ls8c_ard_3-0-0_096083_2018-07-16_final
2018-07-16 11:34:38	ga_ls8c_ard_3-0-0_112082_2018-07-16_final
2018-07-16 11:35:02	ga_ls8c_ard_3-0-0_112083_2018-07-16_final
2018-07-17 10:39:01	ga_ls8c_ard_3-0-0_103082_2018-07-17_final
2018-07-17 10:39:25	ga_ls8c_ard_3-0-0_103083_2018-07-17_final
2018-07-18 09:43:48	ga_ls8c_ard_3-0-0_094083_2018-07-18_final
2018-07-18 11:22:41	ga_ls8c_ard_3-0-0_110083_2018-07-18_final
2018-07-19 10:27:04	ga_ls8c_ard_3-0-0_101083_2018-07-19_final
2018-07-27 11:16:34	ga_ls8c_ard_3-0-0_109083_2018-07-27_final
2018-07-28 10:20:57	ga_ls8c_ard_3-0-0_100083_2018-07-28_final
2018-08-01 09:55:52	ga_ls8c_ard_3-0-0_096082_2018-08-01_final
2018-08-01 09:56:16	ga_ls8c_ard_3-0-0_096083_2018-08-01_final
2018-08-01 11:35:09	ga_ls8c_ard_3-0-0_112083_2018-08-01_final
2018-08-02 10:39:09	ga_ls8c_ard_3-0-0_103082_2018-08-02_final
2018-08-02 10:39:32	ga_ls8c_ard_3-0-0_103083_2018-08-02_final
2018-08-03 09:43:56	ga_ls8c_ard_3-0-0_094083_2018-08-03_final
2018-08-03 11:22:25	ga_ls8c_ard_3-0-0_110082_2018-08-03_final
2018-08-03 11:22:49	ga_ls8c_ard_3-0-0_110083_2018-08-03_final
2018-08-04 10:27:12	ga_ls8c_ard_3-0-0_101083_2018-08-04_final
2018-09-16 10:08:58	ga_ls8c_ard_3-0-0_098083_2018-09-16_final
2018-09-17 09:13:20	ga_ls8c_ard_3-0-0_089083_2018-09-16_final
2018-09-17 10:52:13	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 09:13:34	ga_ls8c_ard_3-0-0_089083_2019-01-06_final
2019-01-07 10:52:27	ga_ls8c_ard_3-0-0_105083_2019-01-07_final
2022-11-11 09:39:02	ga_ls8c_ard_3-2-1_093083_2022-11-11_final
2022-11-11 11:17:55	ga_ls8c_ard_3-2-1_109083_2022-11-11_final
2022-11-12 10:22:17	ga_ls8c_ard_3-2-1_100083_2022-11-12_final
2022-11-13 09:26:39	ga_ls8c_ard_3-2-1_091083_2022-11-12_final
2022-11-13 11:05:32	ga_ls8c_ard_3-2-1_107083_2022-11-13_final
2022-11-14 10:09:54	ga_ls8c_ard_3-2-1_098083_2022-11-14_final
2022-11-15 09:14:16	ga_ls8c_ard_3-2-1_089083_2022-11-14_final
2022-11-15 10:53:09	ga_ls8c_ard_3-2-1_105083_2022-11-15_final
2022-11-16 09:57:31	ga_ls8c_ard_3-2-1_096083_2022-11-16_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
2022-11-27 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
2022-12-01 09:14:16	ga_ls8c_ard_3-2-1_089083_2022-11-30_final
2022-12-01 10:53:09	ga_ls8c_ard_3-2-1_105083_2022-12-01_final
2022-12-02 09:57:32	ga_ls8c_ard_3-2-1_096083_2022-12-02_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
2022-12-07 10:16:04	ga_ls8c_ard_3-2-1_099083_2022-12-07_final
2023-05-20 09:50:04	ga_ls8c_ard_3-2-1_095083_2023-05-20_final
2023-05-20 11:28:57	ga_ls8c_ard_3-2-1_111083_2023-05-20_final
2023-05-22 09:37:43	ga_ls8c_ard_3-2-1_093083_2023-05-22_final
2023-05-22 11:16:36	ga_ls8c_ard_3-2-1_109083_2023-05-22_final
2023-05-23 10:20:59	ga_ls8c_ard_3-2-1_100083_2023-05-23_final
2023-05-24 09:25:22	ga_ls8c_ard_3-2-1_091083_2023-05-23_final
2023-05-24 11:04:15	ga_ls8c_ard_3-2-1_107083_2023-05-24_final
2023-05-25 10:08:38	ga_ls8c_ard_3-2-1_098083_2023-05-25_final
2023-05-26 09:13:01	ga_ls8c_ard_3-2-1_089083_2023-05-25_final
2023-05-26 10:51:54	ga_ls8c_ard_3-2-1_105083_2023-05-26_final
2023-05-31 09:31:34	ga_ls8c_ard_3-2-1_092083_2023-05-31_final
2023-05-31 11:10:27	ga_ls8c_ard_3-2-1_108083_2023-05-31_final
2023-06-01 10:14:49	ga_ls8c_ard_3-2-1_099083_2023-06-01_final
2023-06-02 10:58:05	ga_ls8c_ard_3-2-1_106083_2023-06-02_final
2023-07-03 10:14:45	ga_ls8c_ard_3-2-1_099082_2023-07-03_final
2023-07-03 10:15:09	ga_ls8c_ard_3-2-1_099083_2023-07-03_final
2023-07-04 09:19:08	ga_ls8c_ard_3-2-1_090082_2023-07-03_final
2023-07-04 09:19:32	ga_ls8c_ard_3-2-1_090083_2023-07-03_final
2023-07-04 10:58:01	ga_ls8c_ard_3-2-1_106082_2023-07-04_final
2023-07-04 10:58:25	ga_ls8c_ard_3-2-1_106083_2023-07-04_final
2023-07-05 10:02:48	ga_ls8c_ard_3-2-1_097083_2023-07-05_final
2023-07-05 11:41:41	ga_ls8c_ard_3-2-1_113083_2023-07-05_final
2023-07-06 09:07:12	ga_ls8c_ard_3-2-1_088083_2023-07-05_final
2023-07-07 09:50:28	ga_ls8c_ard_3-2-1_095083_2023-07-07_final
2023-07-07 11:29:21	ga_ls8c_ard_3-2-1_111083_2023-07-07_final
2023-07-09 11:17:00	ga_ls8c_ard_3-2-1_109083_2023-07-09_final
2023-07-10 10:21:23	ga_ls8c_ard_3-2-1_100083_2023-07-10_final
2023-07-11 09:25:46	ga_ls8c_ard_3-2-1_091083_2023-07-10_final
2023-07-11 11:04:39	ga_ls8c_ard_3-2-1_107083_2023-07-11_final
2023-07-12 10:09:02	ga_ls8c_ard_3-2-1_098083_2023-07-12_final
2023-07-13 09:13:25	ga_ls8c_ard_3-2-1_089083_2023-07-12_final
2023-07-13 10:52:18	ga_ls8c_ard_3-2-1_105083_2023-07-13_final
2023-07-14 09:56:41	ga_ls8c_ard_3-2-1_096083_2023-07-14_final
2023-07-14 11:35:34	ga_ls8c_ard_3-2-1_112083_2023-07-14_final
2023-07-16 09:43:55	ga_ls8c_ard_3-2-1_094082_2023-07-16_final
2023-07-16 09:44:19	ga_ls8c_ard_3-2-1_094083_2023-07-16_final
2023-07-16 11:23:12	ga_ls8c_ard_3-2-1_110083_2023-07-16_final
2023-07-17 08:48:18	ga_ls8c_ard_3-2-1_085082_2023-07-16_final
2023-07-17 10:27:35	ga_ls8c_ard_3-2-1_101083_2023-07-17_final
2023-09-02 09:44:36	ga_ls8c_ard_3-2-1_094083_2023-09-02_final
2023-09-15 10:52:39	ga_ls8c_ard_3-2-1_105083_2023-09-15_final
2023-09-16 09:57:02	ga_ls8c_ard_3-2-1_096083_2023-09-16_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