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
2022-07-26 10:50:58	ga_ls8c_ard_3-2-1_105078_2022-07-26_final
2022-07-27 09:54:57	ga_ls8c_ard_3-2-1_096077_2022-07-27_final
2022-07-27 09:55:21	ga_ls8c_ard_3-2-1_096078_2022-07-27_final
2022-07-27 11:35:02	ga_ls8c_ard_3-2-1_112080_2022-07-27_final
2022-07-28 10:37:02	ga_ls8c_ard_3-2-1_103074_2022-07-28_final
2022-08-05 11:28:56	ga_ls8c_ard_3-2-1_111080_2022-08-05_final
2022-08-11 10:51:06	ga_ls8c_ard_3-2-1_105078_2022-08-11_final
2022-08-11 10:51:30	ga_ls8c_ard_3-2-1_105079_2022-08-11_final
2022-08-11 10:51:54	ga_ls8c_ard_3-2-1_105080_2022-08-11_final
2022-08-12 09:55:05	ga_ls8c_ard_3-2-1_096077_2022-08-12_final
2022-09-26 11:03:13	ga_ls8c_ard_3-2-1_107077_2022-09-26_final
2022-09-28 10:51:39	ga_ls8c_ard_3-2-1_105079_2022-09-28_final
2022-09-29 09:55:37	ga_ls8c_ard_3-2-1_096078_2022-09-29_final
2022-09-29 09:56:25	ga_ls8c_ard_3-2-1_096080_2022-09-29_final
2022-09-29 11:33:42	ga_ls8c_ard_3-2-1_112076_2022-09-29_final
2022-09-29 11:34:30	ga_ls8c_ard_3-2-1_112078_2022-09-29_final
2022-10-02 10:24:07	ga_ls8c_ard_3-2-1_101072_2022-10-02_final
2022-10-08 11:28:15	ga_ls8c_ard_3-2-1_111078_2022-10-08_final
2022-10-08 11:29:03	ga_ls8c_ard_3-2-1_111080_2022-10-08_final
2022-10-12 11:05:04	ga_ls8c_ard_3-2-1_107082_2022-10-12_final
2022-10-14 09:13:24	ga_ls8c_ard_3-2-1_089081_2022-10-13_final
2022-10-15 09:54:17	ga_ls8c_ard_3-2-1_096075_2022-10-15_final
2022-10-15 09:54:41	ga_ls8c_ard_3-2-1_096076_2022-10-15_final
2022-10-17 11:22:02	ga_ls8c_ard_3-2-1_110078_2022-10-17_final
2022-10-22 10:00:33	ga_ls8c_ard_3-2-1_097075_2022-10-22_final
2023-03-19 09:37:09	ga_ls8c_ard_3-2-1_093080_2023-03-19_final
2023-03-24 09:53:37	ga_ls8c_ard_3-2-1_096075_2023-03-24_final
2023-05-02 09:59:49	ga_ls8c_ard_3-2-1_097076_2023-05-02_final
2023-05-04 11:27:55	ga_ls8c_ard_3-2-1_111080_2023-05-04_final
2023-05-05 10:31:29	ga_ls8c_ard_3-2-1_102078_2023-05-05_final
2023-05-06 09:36:39	ga_ls8c_ard_3-2-1_093080_2023-05-06_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 09:55:05	ga_ls8c_ard_3-2-1_096080_2023-05-11_final
2023-05-12 10:36:20	ga_ls8c_ard_3-2-1_103075_2023-05-12_final
2023-05-12 10:37:32	ga_ls8c_ard_3-2-1_103078_2023-05-12_final
2023-05-12 10:38:20	ga_ls8c_ard_3-2-1_103080_2023-05-12_final
2023-05-13 09:41:54	ga_ls8c_ard_3-2-1_094078_2023-05-13_final
2023-05-16 11:50:04	ga_ls8c_ard_3-2-1_115074_2023-05-16_final
2023-05-17 10:56:02	ga_ls8c_ard_3-2-1_106078_2023-05-17_final
2023-05-18 09:59:13	ga_ls8c_ard_3-2-1_097075_2023-05-18_final
2023-05-19 10:43:17	ga_ls8c_ard_3-2-1_104077_2023-05-19_final
2023-05-19 10:44:53	ga_ls8c_ard_3-2-1_104081_2023-05-19_final
2023-05-20 09:47:17	ga_ls8c_ard_3-2-1_095076_2023-05-20_final
2023-05-20 11:26:34	ga_ls8c_ard_3-2-1_111077_2023-05-20_final
2023-05-20 11:26:57	ga_ls8c_ard_3-2-1_111078_2023-05-20_final
2023-05-24 11:02:16	ga_ls8c_ard_3-2-1_107078_2023-05-24_final
2023-05-26 10:49:54	ga_ls8c_ard_3-2-1_105078_2023-05-26_final
2023-05-27 09:54:41	ga_ls8c_ard_3-2-1_096079_2023-05-27_final
2023-05-27 11:31:59	ga_ls8c_ard_3-2-1_112075_2023-05-27_final
2023-05-27 11:33:10	ga_ls8c_ard_3-2-1_112078_2023-05-27_final
2023-05-27 11:33:34	ga_ls8c_ard_3-2-1_112079_2023-05-27_final
2023-05-30 10:25:59	ga_ls8c_ard_3-2-1_101080_2023-05-30_final
2023-05-31 09:29:34	ga_ls8c_ard_3-2-1_092078_2023-05-30_final
2023-06-07 09:36:13	ga_ls8c_ard_3-2-1_093079_2023-06-07_final
2023-06-09 11:02:22	ga_ls8c_ard_3-2-1_107078_2023-06-09_final
2023-06-12 11:34:06	ga_ls8c_ard_3-2-1_112080_2023-06-12_final
2023-06-14 09:42:28	ga_ls8c_ard_3-2-1_094079_2023-06-14_final
2023-06-15 10:25:44	ga_ls8c_ard_3-2-1_101079_2023-06-15_final
2023-06-16 09:30:55	ga_ls8c_ard_3-2-1_092081_2023-06-16_final
2023-06-20 10:42:18	ga_ls8c_ard_3-2-1_104074_2023-06-20_final
2023-06-21 09:47:52	ga_ls8c_ard_3-2-1_095077_2023-06-21_final
2023-06-21 11:27:09	ga_ls8c_ard_3-2-1_111078_2023-06-21_final
2023-06-23 11:14:48	ga_ls8c_ard_3-2-1_109078_2023-06-23_final
2023-06-24 10:19:35	ga_ls8c_ard_3-2-1_100079_2023-06-24_final
2023-06-28 11:32:38	ga_ls8c_ard_3-2-1_112076_2023-06-28_final
2023-07-05 11:38:54	ga_ls8c_ard_3-2-1_113076_2023-07-05_final
2023-07-07 11:28:09	ga_ls8c_ard_3-2-1_111080_2023-07-07_final
2023-07-14 11:33:34	ga_ls8c_ard_3-2-1_112078_2023-07-14_final
2023-07-16 09:41:55	ga_ls8c_ard_3-2-1_094077_2023-07-16_final
2023-07-21 11:38:57	ga_ls8c_ard_3-2-1_113076_2023-07-21_final
2023-07-22 10:43:44	ga_ls8c_ard_3-2-1_104077_2023-07-22_final
2023-07-23 11:27:01	ga_ls8c_ard_3-2-1_111077_2023-07-23_final
2023-07-25 11:15:05	ga_ls8c_ard_3-2-1_109078_2023-07-25_final
2023-07-29 10:50:01	ga_ls8c_ard_3-2-1_105077_2023-07-29_final
2023-07-30 11:32:29	ga_ls8c_ard_3-2-1_112075_2023-07-30_final
2023-08-01 09:42:27	ga_ls8c_ard_3-2-1_094078_2023-08-01_final
2023-08-02 10:26:07	ga_ls8c_ard_3-2-1_101079_2023-08-02_final
2023-08-05 10:57:50	ga_ls8c_ard_3-2-1_106081_2023-08-05_final
2023-08-06 11:39:06	ga_ls8c_ard_3-2-1_113076_2023-08-06_final
2023-08-06 11:39:30	ga_ls8c_ard_3-2-1_113077_2023-08-06_final
2023-08-07 10:43:29	ga_ls8c_ard_3-2-1_104076_2023-08-07_final
2023-08-09 10:32:19	ga_ls8c_ard_3-2-1_102079_2023-08-09_final
2023-08-15 09:53:42	ga_ls8c_ard_3-2-1_096075_2023-08-15_final
2023-08-15 11:32:35	ga_ls8c_ard_3-2-1_112075_2023-08-15_final
2023-08-17 09:42:09	ga_ls8c_ard_3-2-1_094077_2023-08-17_final
2023-08-19 09:30:13	ga_ls8c_ard_3-2-1_092078_2023-08-19_final
2023-08-23 10:44:01	ga_ls8c_ard_3-2-1_104077_2023-08-23_final
2023-08-23 10:44:48	ga_ls8c_ard_3-2-1_104079_2023-08-23_final
2023-08-24 09:49:59	ga_ls8c_ard_3-2-1_095081_2023-08-24_final
2023-08-24 11:27:17	ga_ls8c_ard_3-2-1_111077_2023-08-24_final
2023-08-24 11:28:28	ga_ls8c_ard_3-2-1_111080_2023-08-24_final
2023-08-29 10:08:32	ga_ls8c_ard_3-2-1_098081_2023-08-29_final
2023-08-29 10:08:56	ga_ls8c_ard_3-2-1_098082_2023-08-29_final
2023-08-31 11:32:40	ga_ls8c_ard_3-2-1_112075_2023-08-31_final
2023-09-03 10:26:40	ga_ls8c_ard_3-2-1_101080_2023-09-03_final
2023-09-07 10:00:43	ga_ls8c_ard_3-2-1_097077_2023-09-07_final
2023-09-07 11:39:12	ga_ls8c_ard_3-2-1_113076_2023-09-07_final
2023-09-13 11:02:36	ga_ls8c_ard_3-2-1_107077_2023-09-13_final
2023-09-14 10:08:35	ga_ls8c_ard_3-2-1_098081_2023-09-14_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