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
2022-10-17 09:41:33	ga_ls8c_ard_3-2-1_094074_2022-10-17_final
2022-10-17 09:43:09	ga_ls8c_ard_3-2-1_094078_2022-10-17_final
2022-10-22 11:41:26	ga_ls8c_ard_3-2-1_113080_2022-10-22_final
2022-10-26 09:37:03	ga_ls8c_ard_3-2-1_093078_2022-10-26_final
2022-11-01 10:37:41	ga_ls8c_ard_3-2-1_103075_2022-11-01_final
2022-11-04 09:31:42	ga_ls8c_ard_3-2-1_092080_2022-11-04_final
2022-11-04 11:09:23	ga_ls8c_ard_3-2-1_108077_2022-11-04_final
2022-11-05 10:11:22	ga_ls8c_ard_3-2-1_099071_2022-11-05_final
2022-11-06 10:54:37	ga_ls8c_ard_3-2-1_106071_2022-11-06_final
2022-11-07 10:04:35	ga_ls8c_ard_3-2-1_097085_2022-11-07_final
2022-11-07 11:39:52	ga_ls8c_ard_3-2-1_113076_2022-11-07_final
2022-11-07 11:40:40	ga_ls8c_ard_3-2-1_113078_2022-11-07_final
2022-11-09 09:49:01	ga_ls8c_ard_3-2-1_095077_2022-11-09_final
2022-11-09 09:52:12	ga_ls8c_ard_3-2-1_095085_2022-11-09_final
2022-11-09 11:30:18	ga_ls8c_ard_3-2-1_111083_2022-11-09_final
2022-11-10 10:32:40	ga_ls8c_ard_3-2-1_102078_2022-11-10_final
2022-11-10 10:33:04	ga_ls8c_ard_3-2-1_102079_2022-11-10_final
2022-11-16 09:56:19	ga_ls8c_ard_3-2-1_096080_2022-11-16_final
2022-11-18 11:19:13	ga_ls8c_ard_3-2-1_110071_2022-11-18_final
2022-11-18 11:22:01	ga_ls8c_ard_3-2-1_110078_2022-11-18_final
2022-11-21 10:13:15	ga_ls8c_ard_3-2-1_099076_2022-11-21_final
2022-11-23 11:39:47	ga_ls8c_ard_3-2-1_113076_2022-11-23_final
2022-11-27 11:15:29	ga_ls8c_ard_3-2-1_109077_2022-11-27_final
2022-11-28 11:58:45	ga_ls8c_ard_3-2-1_116077_2022-11-28_final
2022-11-29 09:25:02	ga_ls8c_ard_3-2-1_091079_2022-11-28_final
2022-11-30 10:09:06	ga_ls8c_ard_3-2-1_098081_2022-11-30_final
2022-12-02 09:56:20	ga_ls8c_ard_3-2-1_096080_2022-12-02_final
2022-12-03 10:37:36	ga_ls8c_ard_3-2-1_103075_2022-12-03_final
2022-12-03 10:38:00	ga_ls8c_ard_3-2-1_103076_2022-12-03_final
2022-12-03 10:39:12	ga_ls8c_ard_3-2-1_103079_2022-12-03_final
2022-12-04 09:42:23	ga_ls8c_ard_3-2-1_094076_2022-12-04_final
2022-12-04 09:43:11	ga_ls8c_ard_3-2-1_094078_2022-12-04_final
2022-12-05 10:26:02	ga_ls8c_ard_3-2-1_101077_2022-12-05_final
2022-12-05 10:26:26	ga_ls8c_ard_3-2-1_101078_2022-12-05_final
2022-12-10 10:46:09	ga_ls8c_ard_3-2-1_104081_2022-12-10_final
2022-12-11 09:47:20	ga_ls8c_ard_3-2-1_095073_2022-12-11_final
2022-12-11 09:48:55	ga_ls8c_ard_3-2-1_095077_2022-12-11_final
2022-12-16 10:08:37	ga_ls8c_ard_3-2-1_098080_2022-12-16_final
2022-12-17 10:51:04	ga_ls8c_ard_3-2-1_105078_2022-12-17_final
2022-12-19 10:39:04	ga_ls8c_ard_3-2-1_103079_2022-12-19_final
2022-12-20 11:23:07	ga_ls8c_ard_3-2-1_110081_2022-12-20_final
2022-12-22 09:31:02	ga_ls8c_ard_3-2-1_092079_2022-12-22_final
2022-12-26 10:41:13	ga_ls8c_ard_3-2-1_104069_2022-12-26_final
2022-12-27 09:48:48	ga_ls8c_ard_3-2-1_095077_2022-12-27_final
2022-12-27 11:28:53	ga_ls8c_ard_3-2-1_111080_2022-12-27_final
2022-12-29 09:38:27	ga_ls8c_ard_3-2-1_093082_2022-12-29_final
2022-12-29 11:15:44	ga_ls8c_ard_3-2-1_109078_2022-12-29_final
2022-12-29 11:16:08	ga_ls8c_ard_3-2-1_109079_2022-12-29_final
2022-12-31 09:29:17	ga_ls8c_ard_3-2-1_091090_2022-12-30_final
2022-12-31 11:02:59	ga_ls8c_ard_3-2-1_107077_2022-12-31_final
2023-01-02 09:14:08	ga_ls8c_ard_3-2-1_089083_2023-01-01_final
2023-01-03 11:34:17	ga_ls8c_ard_3-2-1_112078_2023-01-03_final
2023-01-05 11:23:07	ga_ls8c_ard_3-2-1_110081_2023-01-05_final
2023-01-05 11:23:31	ga_ls8c_ard_3-2-1_110082_2023-01-05_final
2023-01-07 11:10:20	ga_ls8c_ard_3-2-1_108080_2023-01-07_final
2023-01-07 11:11:08	ga_ls8c_ard_3-2-1_108082_2023-01-07_final
2023-01-08 10:15:31	ga_ls8c_ard_3-2-1_099082_2023-01-08_final
2023-01-09 09:18:41	ga_ls8c_ard_3-2-1_090079_2023-01-08_final
2023-01-09 10:53:35	ga_ls8c_ard_3-2-1_106069_2023-01-09_final
2023-01-10 09:57:33	ga_ls8c_ard_3-2-1_097068_2023-01-10_final
2023-01-10 11:39:38	ga_ls8c_ard_3-2-1_113076_2023-01-10_final
2023-01-11 10:40:48	ga_ls8c_ard_3-2-1_104068_2023-01-11_final
2023-01-11 10:41:12	ga_ls8c_ard_3-2-1_104069_2023-01-11_final
2023-01-14 09:36:46	ga_ls8c_ard_3-2-1_093078_2023-01-14_final
2023-01-18 10:50:28	ga_ls8c_ard_3-2-1_105077_2023-01-18_final
2023-01-21 09:44:56	ga_ls8c_ard_3-2-1_094083_2023-01-21_final
2023-01-22 10:23:25	ga_ls8c_ard_3-2-1_101071_2023-01-22_final
2023-01-24 11:51:34	ga_ls8c_ard_3-2-1_115075_2023-01-24_final
2023-01-25 09:18:39	ga_ls8c_ard_3-2-1_090079_2023-01-24_final
2023-01-26 11:39:13	ga_ls8c_ard_3-2-1_113075_2023-01-26_final
2023-01-30 09:35:37	ga_ls8c_ard_3-2-1_093075_2023-01-30_final
2023-01-30 09:36:01	ga_ls8c_ard_3-2-1_093076_2023-01-30_final
2023-01-30 09:36:25	ga_ls8c_ard_3-2-1_093077_2023-01-30_final
2023-01-30 09:40:25	ga_ls8c_ard_3-2-1_093087_2023-01-30_final
2023-01-30 11:15:42	ga_ls8c_ard_3-2-1_109078_2023-01-30_final
2023-01-31 10:20:29	ga_ls8c_ard_3-2-1_100079_2023-01-31_final
2023-02-05 10:39:01	ga_ls8c_ard_3-2-1_103079_2023-02-05_final
2023-02-06 11:19:29	ga_ls8c_ard_3-2-1_110072_2023-02-06_final
2023-02-07 10:28:14	ga_ls8c_ard_3-2-1_101083_2023-02-07_final
2023-02-08 09:29:49	ga_ls8c_ard_3-2-1_092076_2023-02-07_final
2023-02-08 09:31:01	ga_ls8c_ard_3-2-1_092079_2023-02-08_final
2023-02-08 11:09:06	ga_ls8c_ard_3-2-1_108077_2023-02-08_final
2023-02-09 10:13:04	ga_ls8c_ard_3-2-1_099076_2023-02-09_final
2023-02-13 11:28:46	ga_ls8c_ard_3-2-1_111080_2023-02-13_final
2023-02-13 11:29:34	ga_ls8c_ard_3-2-1_111082_2023-02-13_final
2023-02-15 09:37:30	ga_ls8c_ard_3-2-1_093080_2023-02-15_final
2023-02-15 11:12:48	ga_ls8c_ard_3-2-1_109071_2023-02-15_final
2023-02-16 10:18:21	ga_ls8c_ard_3-2-1_100074_2023-02-16_final
2023-02-17 11:00:24	ga_ls8c_ard_3-2-1_107071_2023-02-17_final
2023-02-17 11:02:48	ga_ls8c_ard_3-2-1_107077_2023-02-17_final
2023-02-17 11:04:00	ga_ls8c_ard_3-2-1_107080_2023-02-17_final
2023-02-21 10:37:12	ga_ls8c_ard_3-2-1_103075_2023-02-21_final
2023-02-21 10:39:59	ga_ls8c_ard_3-2-1_103082_2023-02-21_final
2023-02-23 10:26:23	ga_ls8c_ard_3-2-1_101079_2023-02-23_final
2023-02-26 09:18:45	ga_ls8c_ard_3-2-1_090080_2023-02-25_final
2023-02-28 09:06:47	ga_ls8c_ard_3-2-1_088081_2023-02-27_final
2023-03-03 09:36:53	ga_ls8c_ard_3-2-1_093079_2023-03-03_final
2023-03-05 11:03:47	ga_ls8c_ard_3-2-1_107080_2023-03-05_final
2023-03-06 10:05:22	ga_ls8c_ard_3-2-1_098073_2023-03-06_final
2023-03-06 11:47:02	ga_ls8c_ard_3-2-1_114080_2023-03-06_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