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
2021-10-30 11:24:43	ga_ls8c_ard_3-2-0_110085_2021-10-30_final
2021-11-09 11:57:47	ga_ls8c_ard_3-2-0_116075_2021-11-09_final
2021-11-11 10:05:43	ga_ls8c_ard_3-2-0_098073_2021-11-11_final
2021-11-11 11:45:48	ga_ls8c_ard_3-2-0_114076_2021-11-11_final
2021-11-22 09:48:20	ga_ls8c_ard_3-2-0_095076_2021-11-22_final
2021-12-03 09:32:13	ga_ls8c_ard_3-2-0_092082_2021-12-03_final
2021-12-04 11:53:34	ga_ls8c_ard_3-2-0_115080_2021-12-04_final
2021-12-05 10:57:32	ga_ls8c_ard_3-2-1_106079_2021-12-05_final
2021-12-17 11:21:50	ga_ls8c_ard_3-2-1_110078_2021-12-17_final
2021-12-20 11:53:32	ga_ls8c_ard_3-2-1_115080_2021-12-20_final
2021-12-21 10:57:30	ga_ls8c_ard_3-2-1_106079_2021-12-21_final
2022-01-01 10:39:17	ga_ls8c_ard_3-2-1_103080_2022-01-01_final
2022-01-01 10:40:05	ga_ls8c_ard_3-2-1_103082_2022-01-01_final
2022-01-02 09:44:28	ga_ls8c_ard_3-2-1_094082_2022-01-02_final
2022-01-04 09:35:18	ga_ls8c_ard_3-2-1_092090_2022-01-04_final
2022-01-04 11:07:00	ga_ls8c_ard_3-2-1_108072_2022-01-04_final
2022-01-06 10:57:49	ga_ls8c_ard_3-2-1_106080_2022-01-06_final
2022-01-12 11:58:01	ga_ls8c_ard_3-2-1_116076_2022-01-12_final
2022-01-13 09:24:18	ga_ls8c_ard_3-2-1_091078_2022-01-12_final
2022-01-15 09:16:44	ga_ls8c_ard_3-2-1_089090_2022-01-14_final
2022-02-03 11:21:38	ga_ls8c_ard_3-2-1_110078_2022-02-03_final
2022-02-05 09:29:35	ga_ls8c_ard_3-2-1_092076_2022-02-04_final
2022-02-07 09:19:37	ga_ls8c_ard_3-2-1_090082_2022-02-06_final
2022-02-12 09:37:20	ga_ls8c_ard_3-2-1_093080_2022-02-12_final
2022-02-20 10:24:19	ga_ls8c_ard_3-2-1_101074_2022-02-20_final
2022-02-21 09:29:53	ga_ls8c_ard_3-2-1_092077_2022-02-20_final
2022-03-05 11:31:52	ga_ls8c_ard_3-2-1_112073_2022-03-05_final
2022-03-09 11:08:20	ga_ls8c_ard_3-2-1_108076_2022-03-09_final
2022-03-18 11:00:28	ga_ls8c_ard_3-2-1_107072_2022-03-18_final
2022-03-21 11:31:44	ga_ls8c_ard_3-2-1_112073_2022-03-21_final
2022-03-24 10:23:19	ga_ls8c_ard_3-2-1_101072_2022-03-24_final
2022-03-25 11:06:09	ga_ls8c_ard_3-2-1_108071_2022-03-25_final
2022-03-29 10:42:58	ga_ls8c_ard_3-2-1_104075_2022-03-29_final
2022-04-13 11:40:40	ga_ls8c_ard_3-2-1_113080_2022-04-13_final
2022-04-15 09:47:26	ga_ls8c_ard_3-2-1_095075_2022-04-15_final
2022-04-24 11:20:54	ga_ls8c_ard_3-2-1_110077_2022-04-24_final
2022-04-26 09:34:50	ga_ls8c_ard_3-2-1_092090_2022-04-26_final
2022-04-26 11:09:19	ga_ls8c_ard_3-2-1_108079_2022-04-26_final
2022-05-04 10:17:32	ga_ls8c_ard_3-2-1_100073_2022-05-04_final
2022-05-05 11:00:48	ga_ls8c_ard_3-2-1_107073_2022-05-05_final
2022-05-19 11:12:52	ga_ls8c_ard_3-2-1_109072_2022-05-19_final
2022-05-25 10:38:10	ga_ls8c_ard_3-2-1_103078_2022-05-25_final
2022-05-31 10:00:44	ga_ls8c_ard_3-2-1_097077_2022-05-31_final
2022-06-02 11:29:17	ga_ls8c_ard_3-2-1_111082_2022-06-02_final
2022-06-12 10:26:49	ga_ls8c_ard_3-2-1_101080_2022-06-12_final
2022-06-17 10:44:12	ga_ls8c_ard_3-2-1_104077_2022-06-17_final
2022-06-18 09:48:12	ga_ls8c_ard_3-2-1_095076_2022-06-18_final
2022-06-21 10:21:07	ga_ls8c_ard_3-2-1_100081_2022-06-21_final
2022-07-08 11:01:12	ga_ls8c_ard_3-2-1_107073_2022-07-08_final
2022-07-11 09:55:37	ga_ls8c_ard_3-2-1_096079_2022-07-11_final
2022-07-11 11:32:06	ga_ls8c_ard_3-2-1_112073_2022-07-11_final
2022-07-15 09:31:40	ga_ls8c_ard_3-2-1_092081_2022-07-15_final
2022-07-15 11:09:45	ga_ls8c_ard_3-2-1_108079_2022-07-15_final
2022-07-26 10:48:34	ga_ls8c_ard_3-2-1_105072_2022-07-26_final
2022-07-29 09:43:48	ga_ls8c_ard_3-2-1_094080_2022-07-29_final
2022-07-30 10:24:41	ga_ls8c_ard_3-2-1_101074_2022-07-30_final
2022-07-30 10:25:05	ga_ls8c_ard_3-2-1_101075_2022-07-30_final
2022-08-05 09:50:27	ga_ls8c_ard_3-2-1_095081_2022-08-05_final
2022-08-08 10:18:11	ga_ls8c_ard_3-2-1_100073_2022-08-08_final
2022-08-11 10:49:06	ga_ls8c_ard_3-2-1_105073_2022-08-11_final
2022-08-16 11:10:04	ga_ls8c_ard_3-2-1_108079_2022-08-16_final
2022-08-31 10:25:13	ga_ls8c_ard_3-2-1_101075_2022-08-31_final
2022-09-20 11:40:17	ga_ls8c_ard_3-2-1_113077_2022-09-20_final
2022-09-21 10:43:52	ga_ls8c_ard_3-2-1_104075_2022-09-21_final
2022-09-30 10:38:29	ga_ls8c_ard_3-2-1_103077_2022-09-30_final
2022-10-04 10:12:08	ga_ls8c_ard_3-2-1_099073_2022-10-04_final
2022-10-07 10:45:48	ga_ls8c_ard_3-2-1_104080_2022-10-07_final
2022-10-12 11:04:40	ga_ls8c_ard_3-2-1_107081_2022-10-12_final
2022-10-15 09:56:17	ga_ls8c_ard_3-2-1_096080_2022-10-15_final
2022-10-16 10:38:46	ga_ls8c_ard_3-2-1_103078_2022-10-16_final
2022-10-19 11:10:30	ga_ls8c_ard_3-2-1_108080_2022-10-19_final
2022-10-19 11:10:54	ga_ls8c_ard_3-2-1_108081_2022-10-19_final
2022-10-26 11:12:21	ga_ls8c_ard_3-2-1_109069_2022-10-26_final
2022-10-27 11:58:25	ga_ls8c_ard_3-2-1_116076_2022-10-27_final
2022-10-27 11:59:13	ga_ls8c_ard_3-2-1_116078_2022-10-27_final
2022-10-31 11:34:54	ga_ls8c_ard_3-2-1_112079_2022-10-31_final
2022-11-04 09:30:54	ga_ls8c_ard_3-2-1_092078_2022-11-04_final
2022-11-04 11:06:12	ga_ls8c_ard_3-2-1_108069_2022-11-04_final
2022-11-11 11:13:31	ga_ls8c_ard_3-2-1_109072_2022-11-11_final
2022-11-15 10:49:09	ga_ls8c_ard_3-2-1_105073_2022-11-15_final
2022-11-28 11:58:21	ga_ls8c_ard_3-2-1_116076_2022-11-28_final
2022-11-30 11:47:11	ga_ls8c_ard_3-2-1_114079_2022-11-30_final
2022-12-01 10:48:22	ga_ls8c_ard_3-2-1_105071_2022-12-01_final
2022-12-02 09:56:44	ga_ls8c_ard_3-2-1_096081_2022-12-02_final
2022-12-04 09:41:59	ga_ls8c_ard_3-2-1_094075_2022-12-04_final
2022-12-06 09:30:49	ga_ls8c_ard_3-2-1_092078_2022-12-06_final
2022-12-08 10:56:56	ga_ls8c_ard_3-2-1_106077_2022-12-08_final
2022-12-18 09:53:50	ga_ls8c_ard_3-2-1_096074_2022-12-18_final
2022-12-24 10:57:34	ga_ls8c_ard_3-2-1_106079_2022-12-24_final
2022-12-27 09:50:24	ga_ls8c_ard_3-2-1_095081_2022-12-27_final
2023-01-01 11:47:02	ga_ls8c_ard_3-2-1_114079_2023-01-01_final
2023-01-02 10:51:49	ga_ls8c_ard_3-2-1_105080_2023-01-02_final
2023-01-13 10:32:00	ga_ls8c_ard_3-2-1_102077_2023-01-13_final
2023-01-15 10:20:25	ga_ls8c_ard_3-2-1_100079_2023-01-15_final
2023-01-20 10:38:09	ga_ls8c_ard_3-2-1_103077_2023-01-20_final
2023-02-09 10:12:40	ga_ls8c_ard_3-2-1_099075_2023-02-09_final
2023-02-15 11:15:59	ga_ls8c_ard_3-2-1_109079_2023-02-15_final
2023-02-17 11:00:00	ga_ls8c_ard_3-2-1_107070_2023-02-17_final
2023-02-18 11:45:38	ga_ls8c_ard_3-2-1_114076_2023-02-18_final
2023-02-19 10:48:24	ga_ls8c_ard_3-2-1_105072_2023-02-19_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