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
2016-12-30 12:37:41	ga_ls8c_ard_3-2-1_123067_2016-12-30_final
2020-05-11 08:10:07	ga_ls8c_ard_3-2-1_079080_2020-05-10_final
2021-03-24 12:31:05	ga_ls8c_ard_3-2-1_122067_2021-03-24_final
2023-02-03 10:50:59	ga_ls8c_ard_3-2-1_105078_2023-02-03_final
2023-02-04 11:34:38	ga_ls8c_ard_3-2-1_112079_2023-02-04_final
2023-04-25 09:54:54	ga_ls8c_ard_3-2-1_096079_2023-04-25_final
2023-04-28 10:25:47	ga_ls8c_ard_3-2-1_101079_2023-04-28_final
2023-04-30 10:14:12	ga_ls8c_ard_3-2-1_099081_2023-04-30_final
2023-05-04 09:47:26	ga_ls8c_ard_3-2-1_095076_2023-05-04_final
2023-05-06 11:15:08	ga_ls8c_ard_3-2-1_109079_2023-05-06_final
2023-05-10 10:49:56	ga_ls8c_ard_3-2-1_105078_2023-05-10_final
2023-05-11 09:54:18	ga_ls8c_ard_3-2-1_096078_2023-05-11_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
2023-05-14 10:26:22	ga_ls8c_ard_3-2-1_101081_2023-05-14_final
2023-05-16 10:13:59	ga_ls8c_ard_3-2-1_099081_2023-05-16_final
2023-05-22 11:15:01	ga_ls8c_ard_3-2-1_109079_2023-05-22_final
2023-05-22 11:15:25	ga_ls8c_ard_3-2-1_109080_2023-05-22_final
2023-05-29 09:41:32	ga_ls8c_ard_3-2-1_094077_2023-05-29_final
2023-05-30 10:25:35	ga_ls8c_ard_3-2-1_101079_2023-05-30_final
2023-06-02 10:56:05	ga_ls8c_ard_3-2-1_106078_2023-06-02_final
2023-06-05 11:26:38	ga_ls8c_ard_3-2-1_111077_2023-06-05_final
2023-06-05 11:27:02	ga_ls8c_ard_3-2-1_111078_2023-06-05_final
2023-06-06 10:31:50	ga_ls8c_ard_3-2-1_102079_2023-06-06_final
2023-06-10 10:08:21	ga_ls8c_ard_3-2-1_098082_2023-06-10_final
2023-06-12 09:54:01	ga_ls8c_ard_3-2-1_096077_2023-06-12_final
2023-06-13 10:36:53	ga_ls8c_ard_3-2-1_103076_2023-06-13_final
2023-06-14 09:42:04	ga_ls8c_ard_3-2-1_094078_2023-06-14_final
2023-06-17 10:14:11	ga_ls8c_ard_3-2-1_099081_2023-06-17_final
2023-06-21 09:45:28	ga_ls8c_ard_3-2-1_095071_2023-06-21_final
2023-06-22 10:31:55	ga_ls8c_ard_3-2-1_102079_2023-06-22_final
2023-06-25 11:02:28	ga_ls8c_ard_3-2-1_107078_2023-06-25_final
2023-06-28 11:33:02	ga_ls8c_ard_3-2-1_112077_2023-06-28_final
2023-06-30 09:42:37	ga_ls8c_ard_3-2-1_094079_2023-06-30_final
2023-07-06 10:44:05	ga_ls8c_ard_3-2-1_104078_2023-07-06_final
2023-07-08 10:31:44	ga_ls8c_ard_3-2-1_102078_2023-07-08_final
2023-07-09 11:15:48	ga_ls8c_ard_3-2-1_109080_2023-07-09_final
2023-07-12 10:08:38	ga_ls8c_ard_3-2-1_098082_2023-07-12_final
2023-07-14 09:54:17	ga_ls8c_ard_3-2-1_096077_2023-07-14_final
2023-07-14 11:32:22	ga_ls8c_ard_3-2-1_112075_2023-07-14_final
2023-07-14 11:32:46	ga_ls8c_ard_3-2-1_112076_2023-07-14_final
2023-07-17 10:25:59	ga_ls8c_ard_3-2-1_101079_2023-07-17_final
2023-07-18 11:09:15	ga_ls8c_ard_3-2-1_108079_2023-07-18_final
2023-07-19 10:14:25	ga_ls8c_ard_3-2-1_099081_2023-07-19_final
2023-07-27 11:02:45	ga_ls8c_ard_3-2-1_107078_2023-07-27_final
2023-07-29 10:51:13	ga_ls8c_ard_3-2-1_105080_2023-07-29_final
2023-07-30 09:54:48	ga_ls8c_ard_3-2-1_096078_2023-07-30_final
2023-08-04 10:14:34	ga_ls8c_ard_3-2-1_099081_2023-08-04_final
2023-08-10 09:37:05	ga_ls8c_ard_3-2-1_093080_2023-08-10_final
2023-08-15 09:55:17	ga_ls8c_ard_3-2-1_096079_2023-08-15_final
2023-08-15 11:34:35	ga_ls8c_ard_3-2-1_112080_2023-08-15_final
2023-08-20 10:14:41	ga_ls8c_ard_3-2-1_099081_2023-08-20_final
2023-08-22 11:39:14	ga_ls8c_ard_3-2-1_113076_2023-08-22_final
2023-08-24 09:49:35	ga_ls8c_ard_3-2-1_095080_2023-08-24_final
2023-08-27 11:58:11	ga_ls8c_ard_3-2-1_116077_2023-08-27_final
2023-08-31 09:55:46	ga_ls8c_ard_3-2-1_096080_2023-08-31_final
2023-08-31 11:34:39	ga_ls8c_ard_3-2-1_112080_2023-08-31_final
2023-09-02 09:42:13	ga_ls8c_ard_3-2-1_094077_2023-09-02_final
2023-09-02 11:21:29	ga_ls8c_ard_3-2-1_110078_2023-09-02_final
2023-09-08 10:44:48	ga_ls8c_ard_3-2-1_104079_2023-09-08_final
2023-09-11 11:15:20	ga_ls8c_ard_3-2-1_109078_2023-09-11_final
2023-09-16 09:55:50	ga_ls8c_ard_3-2-1_096080_2023-09-16_final
2023-09-17 10:38:42	ga_ls8c_ard_3-2-1_103079_2023-09-17_final
2023-09-25 11:27:23	ga_ls8c_ard_3-2-1_111077_2023-09-25_final
2023-10-05 10:26:47	ga_ls8c_ard_3-2-1_101080_2023-10-05_final
2023-10-06 09:30:22	ga_ls8c_ard_3-2-1_092078_2023-10-06_final
2023-10-06 11:08:51	ga_ls8c_ard_3-2-1_108077_2023-10-06_final
2023-10-10 10:44:58	ga_ls8c_ard_3-2-1_104079_2023-10-10_final
2023-11-03 11:33:40	ga_ls8c_ard_3-2-1_112077_2023-11-03_final
2023-11-05 11:21:42	ga_ls8c_ard_3-2-1_110078_2023-11-05_final
2023-11-06 10:26:52	ga_ls8c_ard_3-2-1_101080_2023-11-06_final
2023-11-16 11:03:10	ga_ls8c_ard_3-2-1_107078_2023-11-16_final
2023-11-22 10:26:55	ga_ls8c_ard_3-2-1_101080_2023-11-22_final
2023-11-27 10:45:51	ga_ls8c_ard_3-2-1_104081_2023-11-27_final
2023-11-28 09:48:38	ga_ls8c_ard_3-2-1_095077_2023-11-28_final
2023-12-05 09:54:18	ga_ls8c_ard_3-2-1_096076_2023-12-05_final
2023-12-09 11:09:15	ga_ls8c_ard_3-2-1_108078_2023-12-09_final
2023-12-11 10:57:43	ga_ls8c_ard_3-2-1_106080_2023-12-11_final
2023-12-14 11:28:16	ga_ls8c_ard_3-2-1_111079_2023-12-14_final
2023-12-21 09:53:12	ga_ls8c_ard_3-2-1_096073_2023-12-21_final
2024-01-05 10:50:40	ga_ls8c_ard_3-2-1_105078_2024-01-05_final
2024-01-15 09:49:19	ga_ls8c_ard_3-2-1_095079_2024-01-15_final
2024-01-31 11:28:08	ga_ls8c_ard_3-2-1_111079_2024-01-31_final
2024-02-04 11:03:03	ga_ls8c_ard_3-2-1_107078_2024-02-04_final
2024-02-08 10:37:09	ga_ls8c_ard_3-2-1_103075_2024-02-08_final
2024-02-10 10:26:47	ga_ls8c_ard_3-2-1_101080_2024-02-10_final
2024-02-16 09:48:28	ga_ls8c_ard_3-2-1_095077_2024-02-16_final
2024-02-16 11:28:09	ga_ls8c_ard_3-2-1_111079_2024-02-16_final
2024-02-27 09:35:04	ga_ls8c_ard_3-2-1_092090_2024-02-27_final
2024-03-10 11:33:19	ga_ls8c_ard_3-2-1_112077_2024-03-10_final
2024-03-20 10:31:26	ga_ls8c_ard_3-2-1_102077_2024-03-20_nrt
2024-03-24 10:08:37	ga_ls8c_ard_3-2-1_098082_2024-03-24_nrt
2024-03-26 11:32:42	ga_ls8c_ard_3-2-1_112076_2024-03-26_nrt
2024-03-26 11:33:54	ga_ls8c_ard_3-2-1_112079_2024-03-26_nrt
2024-03-27 10:34:39	ga_ls8c_ard_3-2-1_103070_2024-03-27_nrt
2024-04-04 11:26:54	ga_ls8c_ard_3-2-1_111077_2024-04-04_nrt
2024-04-13 09:42:11	ga_ls8c_ard_3-2-1_094078_2024-04-13_nrt
2024-04-18 11:38:44	ga_ls8c_ard_3-2-1_113076_2024-04-18_nrt
2024-04-19 10:43:29	ga_ls8c_ard_3-2-1_104077_2024-04-19_nrt
2024-04-19 10:44:17	ga_ls8c_ard_3-2-1_104079_2024-04-19_nrt

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