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
2022-10-15 09:54:17	ga_ls8c_ard_3-2-1_096075_2022-10-15_final
2022-10-15 11:35:10	ga_ls8c_ard_3-2-1_112080_2022-10-15_final
2022-10-24 11:28:41	ga_ls8c_ard_3-2-1_111079_2022-10-24_final
2022-10-30 10:51:38	ga_ls8c_ard_3-2-1_105079_2022-10-30_final
2022-11-01 10:37:41	ga_ls8c_ard_3-2-1_103075_2022-11-01_final
2022-11-02 11:22:09	ga_ls8c_ard_3-2-1_110078_2022-11-02_final
2022-11-08 10:45:27	ga_ls8c_ard_3-2-1_104079_2022-11-08_final
2022-11-09 09:49:25	ga_ls8c_ard_3-2-1_095078_2022-11-09_final
2022-11-10 10:31:28	ga_ls8c_ard_3-2-1_102075_2022-11-10_final
2022-11-10 10:33:28	ga_ls8c_ard_3-2-1_102080_2022-11-10_final
2022-11-19 10:27:12	ga_ls8c_ard_3-2-1_101080_2022-11-19_final
2022-11-23 10:00:30	ga_ls8c_ard_3-2-1_097075_2022-11-23_final
2022-11-25 09:50:09	ga_ls8c_ard_3-2-1_095080_2022-11-25_final
2022-11-25 11:28:38	ga_ls8c_ard_3-2-1_111079_2022-11-25_final
2022-11-28 10:21:03	ga_ls8c_ard_3-2-1_100080_2022-11-28_final
2022-12-02 09:54:45	ga_ls8c_ard_3-2-1_096076_2022-12-02_final
2022-12-11 11:28:36	ga_ls8c_ard_3-2-1_111079_2022-12-11_final
2022-12-13 09:38:32	ga_ls8c_ard_3-2-1_093082_2022-12-13_final
2022-12-30 10:20:55	ga_ls8c_ard_3-2-1_100080_2022-12-30_final
2023-01-02 10:52:37	ga_ls8c_ard_3-2-1_105082_2023-01-02_final
2023-01-03 09:54:36	ga_ls8c_ard_3-2-1_096076_2023-01-03_final
2023-01-03 09:55:00	ga_ls8c_ard_3-2-1_096077_2023-01-03_final
2023-01-05 11:21:55	ga_ls8c_ard_3-2-1_110078_2023-01-05_final
2023-01-12 09:49:33	ga_ls8c_ard_3-2-1_095079_2023-01-12_final
2023-01-12 11:28:26	ga_ls8c_ard_3-2-1_111079_2023-01-12_final
2023-01-15 10:20:49	ga_ls8c_ard_3-2-1_100080_2023-01-15_final
2023-02-06 11:21:52	ga_ls8c_ard_3-2-1_110078_2023-02-06_final
2023-02-06 11:22:16	ga_ls8c_ard_3-2-1_110079_2023-02-06_final
2023-02-08 09:31:25	ga_ls8c_ard_3-2-1_092080_2023-02-08_final
2023-02-13 11:28:22	ga_ls8c_ard_3-2-1_111079_2023-02-13_final
2023-02-19 10:51:36	ga_ls8c_ard_3-2-1_105080_2023-02-19_final
2023-02-20 09:56:45	ga_ls8c_ard_3-2-1_096082_2023-02-20_final
2023-02-22 09:43:09	ga_ls8c_ard_3-2-1_094079_2023-02-22_final
2023-02-22 11:22:02	ga_ls8c_ard_3-2-1_110079_2023-02-22_final
2023-03-03 11:16:10	ga_ls8c_ard_3-2-1_109080_2023-03-03_final
2023-03-04 10:20:56	ga_ls8c_ard_3-2-1_100081_2023-03-04_final
2023-03-08 09:55:45	ga_ls8c_ard_3-2-1_096080_2023-03-08_final
2023-03-08 09:56:33	ga_ls8c_ard_3-2-1_096082_2023-03-08_final
2023-03-08 11:33:51	ga_ls8c_ard_3-2-1_112078_2023-03-08_final
2023-03-08 11:34:15	ga_ls8c_ard_3-2-1_112079_2023-03-08_final
2023-03-10 09:43:24	ga_ls8c_ard_3-2-1_094080_2023-03-10_final
2023-03-10 09:44:35	ga_ls8c_ard_3-2-1_094083_2023-03-10_final
2023-03-14 10:56:21	ga_ls8c_ard_3-2-1_106077_2023-03-14_final
2023-03-15 10:02:43	ga_ls8c_ard_3-2-1_097082_2023-03-15_final
2023-03-16 10:44:46	ga_ls8c_ard_3-2-1_104079_2023-03-16_final
2023-03-17 09:48:20	ga_ls8c_ard_3-2-1_095077_2023-03-17_final
2023-03-17 11:27:13	ga_ls8c_ard_3-2-1_111077_2023-03-17_final
2023-03-19 09:37:09	ga_ls8c_ard_3-2-1_093080_2023-03-19_final
2023-03-19 11:14:50	ga_ls8c_ard_3-2-1_109077_2023-03-19_final
2023-03-24 09:55:13	ga_ls8c_ard_3-2-1_096079_2023-03-24_final
2023-03-24 09:55:37	ga_ls8c_ard_3-2-1_096080_2023-03-24_final
2023-03-26 09:42:51	ga_ls8c_ard_3-2-1_094079_2023-03-26_final
2023-03-31 09:59:45	ga_ls8c_ard_3-2-1_097075_2023-03-31_final
2023-04-02 09:47:46	ga_ls8c_ard_3-2-1_095076_2023-04-02_final
2023-04-09 09:53:23	ga_ls8c_ard_3-2-1_096075_2023-04-09_final
2023-04-09 09:53:47	ga_ls8c_ard_3-2-1_096076_2023-04-09_final
2023-04-09 09:54:59	ga_ls8c_ard_3-2-1_096079_2023-04-09_final
2023-04-09 11:33:28	ga_ls8c_ard_3-2-1_112078_2023-04-09_final
2023-04-09 11:33:52	ga_ls8c_ard_3-2-1_112079_2023-04-09_final
2023-04-11 09:41:23	ga_ls8c_ard_3-2-1_094076_2023-04-11_final
2023-04-11 09:41:47	ga_ls8c_ard_3-2-1_094077_2023-04-11_final
2023-04-11 09:42:59	ga_ls8c_ard_3-2-1_094080_2023-04-11_final
2023-04-11 09:44:10	ga_ls8c_ard_3-2-1_094083_2023-04-11_final
2023-04-12 10:26:14	ga_ls8c_ard_3-2-1_101080_2023-04-12_final
2023-04-18 11:26:48	ga_ls8c_ard_3-2-1_111077_2023-04-18_final
2023-04-18 11:28:24	ga_ls8c_ard_3-2-1_111081_2023-04-18_final
2023-04-19 10:30:46	ga_ls8c_ard_3-2-1_102076_2023-04-19_final
2023-04-21 10:20:00	ga_ls8c_ard_3-2-1_100080_2023-04-21_final
2023-04-25 09:55:17	ga_ls8c_ard_3-2-1_096080_2023-04-25_final
2023-04-25 11:34:11	ga_ls8c_ard_3-2-1_112080_2023-04-25_final
2023-04-27 09:42:31	ga_ls8c_ard_3-2-1_094079_2023-04-27_final
2023-04-27 09:42:55	ga_ls8c_ard_3-2-1_094080_2023-04-27_final
2023-04-28 10:25:47	ga_ls8c_ard_3-2-1_101079_2023-04-28_final
2023-05-02 09:59:26	ga_ls8c_ard_3-2-1_097075_2023-05-02_final
2023-05-03 10:43:28	ga_ls8c_ard_3-2-1_104077_2023-05-03_final
2023-05-03 10:45:04	ga_ls8c_ard_3-2-1_104081_2023-05-03_final
2023-05-04 09:49:02	ga_ls8c_ard_3-2-1_095080_2023-05-04_final
2023-05-04 11:26:43	ga_ls8c_ard_3-2-1_111077_2023-05-04_final
2023-05-04 11:27:55	ga_ls8c_ard_3-2-1_111080_2023-05-04_final
2023-05-05 10:31:53	ga_ls8c_ard_3-2-1_102079_2023-05-05_final
2023-05-06 09:35:51	ga_ls8c_ard_3-2-1_093078_2023-05-06_final
2023-05-06 09:36:15	ga_ls8c_ard_3-2-1_093079_2023-05-06_final
2023-05-06 09:36:39	ga_ls8c_ard_3-2-1_093080_2023-05-06_final
2023-05-06 11:15:08	ga_ls8c_ard_3-2-1_109079_2023-05-06_final
2023-05-08 11:03:56	ga_ls8c_ard_3-2-1_107082_2023-05-08_final
2023-05-09 10:07:54	ga_ls8c_ard_3-2-1_098081_2023-05-09_final
2023-05-11 09:53:06	ga_ls8c_ard_3-2-1_096075_2023-05-11_final
2023-05-11 09:54:41	ga_ls8c_ard_3-2-1_096079_2023-05-11_final
2023-05-11 09:55:05	ga_ls8c_ard_3-2-1_096080_2023-05-11_final
2023-05-12 10:37:32	ga_ls8c_ard_3-2-1_103078_2023-05-12_final
2023-05-13 09:41:31	ga_ls8c_ard_3-2-1_094077_2023-05-13_final
2023-05-13 11:20:48	ga_ls8c_ard_3-2-1_110078_2023-05-13_final
2023-05-13 11:21:11	ga_ls8c_ard_3-2-1_110079_2023-05-13_final
2023-05-16 11:50:04	ga_ls8c_ard_3-2-1_115074_2023-05-16_final
2023-05-18 09:59:37	ga_ls8c_ard_3-2-1_097076_2023-05-18_final
2023-05-19 10:43:17	ga_ls8c_ard_3-2-1_104077_2023-05-19_final
2023-05-20 11:26:57	ga_ls8c_ard_3-2-1_111078_2023-05-20_final
2023-05-27 09:53:05	ga_ls8c_ard_3-2-1_096075_2023-05-27_final
2023-05-27 09:55:05	ga_ls8c_ard_3-2-1_096080_2023-05-27_final
2023-05-27 11:33:10	ga_ls8c_ard_3-2-1_112078_2023-05-27_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