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
2022-07-29 09:41:25	ga_ls8c_ard_3-2-1_094074_2022-07-29_final
2022-07-31 11:10:21	ga_ls8c_ard_3-2-1_108080_2022-07-31_final
2022-08-23 09:36:11	ga_ls8c_ard_3-2-1_093076_2022-08-23_final
2022-08-23 09:37:22	ga_ls8c_ard_3-2-1_093079_2022-08-23_final
2022-09-02 10:15:38	ga_ls8c_ard_3-2-1_099082_2022-09-02_final
2022-09-03 10:54:31	ga_ls8c_ard_3-2-1_106071_2022-09-03_final
2022-09-05 10:42:58	ga_ls8c_ard_3-2-1_104073_2022-09-05_final
2022-09-05 10:43:22	ga_ls8c_ard_3-2-1_104074_2022-09-05_final
2022-09-06 09:46:58	ga_ls8c_ard_3-2-1_095072_2022-09-06_final
2022-09-06 11:24:15	ga_ls8c_ard_3-2-1_111068_2022-09-06_final
2022-09-12 10:48:25	ga_ls8c_ard_3-2-1_105071_2022-09-12_final
2022-09-13 09:52:48	ga_ls8c_ard_3-2-1_096071_2022-09-13_final
2022-09-14 10:35:40	ga_ls8c_ard_3-2-1_103070_2022-09-14_final
2022-09-15 09:46:02	ga_ls8c_ard_3-2-1_094085_2022-09-15_final
2022-09-15 11:22:56	ga_ls8c_ard_3-2-1_110080_2022-09-15_final
2022-09-19 09:20:56	ga_ls8c_ard_3-2-1_090084_2022-09-18_final
2022-09-24 09:36:17	ga_ls8c_ard_3-2-1_093076_2022-09-24_final
2022-09-27 10:04:48	ga_ls8c_ard_3-2-1_098070_2022-09-27_final
2022-09-27 11:45:40	ga_ls8c_ard_3-2-1_114075_2022-09-27_final
2022-09-27 11:47:40	ga_ls8c_ard_3-2-1_114080_2022-09-27_final
2022-09-28 10:48:27	ga_ls8c_ard_3-2-1_105071_2022-09-28_final
2022-09-28 10:48:51	ga_ls8c_ard_3-2-1_105072_2022-09-28_final
2022-09-30 10:39:41	ga_ls8c_ard_3-2-1_103080_2022-09-30_final
2022-10-03 09:31:41	ga_ls8c_ard_3-2-1_092080_2022-10-03_final
2022-10-06 10:02:57	ga_ls8c_ard_3-2-1_097081_2022-10-06_final
2022-10-09 10:32:13	ga_ls8c_ard_3-2-1_102077_2022-10-09_final
2022-10-10 09:38:59	ga_ls8c_ard_3-2-1_093083_2022-10-10_final
2022-10-11 11:58:19	ga_ls8c_ard_3-2-1_116076_2022-10-11_final
2022-10-13 11:45:31	ga_ls8c_ard_3-2-1_114075_2022-10-13_final
2022-10-14 10:47:54	ga_ls8c_ard_3-2-1_105070_2022-10-14_final
2022-10-17 11:19:15	ga_ls8c_ard_3-2-1_110071_2022-10-17_final
2022-10-20 10:13:17	ga_ls8c_ard_3-2-1_099076_2022-10-20_final
2022-10-23 10:41:26	ga_ls8c_ard_3-2-1_104069_2022-10-23_final
2022-10-24 09:50:12	ga_ls8c_ard_3-2-1_095080_2022-10-24_final
2022-10-26 09:37:27	ga_ls8c_ard_3-2-1_093079_2022-10-26_final
2022-10-27 11:59:13	ga_ls8c_ard_3-2-1_116078_2022-10-27_final
2022-10-28 11:03:36	ga_ls8c_ard_3-2-1_107078_2022-10-28_final
2022-10-29 10:09:10	ga_ls8c_ard_3-2-1_098081_2022-10-29_final
2022-11-01 10:35:42	ga_ls8c_ard_3-2-1_103070_2022-11-01_final
2022-11-01 10:36:53	ga_ls8c_ard_3-2-1_103073_2022-11-01_final
2022-11-01 10:39:17	ga_ls8c_ard_3-2-1_103079_2022-11-01_final
2022-11-03 10:24:32	ga_ls8c_ard_3-2-1_101073_2022-11-03_final
2022-11-03 10:25:20	ga_ls8c_ard_3-2-1_101075_2022-11-03_final
2022-11-07 11:39:29	ga_ls8c_ard_3-2-1_113075_2022-11-07_final
2022-11-07 11:42:16	ga_ls8c_ard_3-2-1_113082_2022-11-07_final
2022-11-09 09:51:25	ga_ls8c_ard_3-2-1_095083_2022-11-09_final
2022-11-09 11:27:30	ga_ls8c_ard_3-2-1_111076_2022-11-09_final
2022-11-10 10:30:16	ga_ls8c_ard_3-2-1_102072_2022-11-10_final
2022-11-14 10:09:06	ga_ls8c_ard_3-2-1_098081_2022-11-14_final
2022-11-14 11:47:35	ga_ls8c_ard_3-2-1_114080_2022-11-14_final
2022-11-16 09:55:55	ga_ls8c_ard_3-2-1_096079_2022-11-16_final
2022-11-16 09:57:07	ga_ls8c_ard_3-2-1_096082_2022-11-16_final
2022-11-17 10:35:58	ga_ls8c_ard_3-2-1_103071_2022-11-17_final
2022-11-17 10:37:58	ga_ls8c_ard_3-2-1_103076_2022-11-17_final
2022-11-18 09:44:19	ga_ls8c_ard_3-2-1_094081_2022-11-18_final
2022-11-20 09:32:47	ga_ls8c_ard_3-2-1_092083_2022-11-20_final
2022-11-23 11:41:23	ga_ls8c_ard_3-2-1_113080_2022-11-23_final
2022-11-23 11:41:47	ga_ls8c_ard_3-2-1_113081_2022-11-23_final
2022-11-23 11:42:11	ga_ls8c_ard_3-2-1_113082_2022-11-23_final
2022-11-23 11:42:35	ga_ls8c_ard_3-2-1_113083_2022-11-23_final
2022-11-29 09:25:02	ga_ls8c_ard_3-2-1_091079_2022-11-28_final
2022-11-30 11:45:35	ga_ls8c_ard_3-2-1_114075_2022-11-30_final
2022-12-02 09:53:33	ga_ls8c_ard_3-2-1_096073_2022-12-02_final
2022-12-03 10:38:24	ga_ls8c_ard_3-2-1_103077_2022-12-03_final
2022-12-05 10:25:14	ga_ls8c_ard_3-2-1_101075_2022-12-05_final
2022-12-08 09:19:14	ga_ls8c_ard_3-2-1_090080_2022-12-07_final
2022-12-09 11:41:23	ga_ls8c_ard_3-2-1_113080_2022-12-09_final
2022-12-16 10:08:37	ga_ls8c_ard_3-2-1_098080_2022-12-16_final
2022-12-19 10:36:41	ga_ls8c_ard_3-2-1_103073_2022-12-19_final
2022-12-23 10:15:29	ga_ls8c_ard_3-2-1_099082_2022-12-23_final
2022-12-30 10:18:55	ga_ls8c_ard_3-2-1_100075_2022-12-30_final
2022-12-30 11:59:00	ga_ls8c_ard_3-2-1_116078_2022-12-30_final
2022-12-31 09:26:29	ga_ls8c_ard_3-2-1_091083_2022-12-30_final
2022-12-31 09:26:53	ga_ls8c_ard_3-2-1_091084_2022-12-30_final
2023-01-01 10:07:21	ga_ls8c_ard_3-2-1_098077_2023-01-01_final
2023-01-03 09:54:12	ga_ls8c_ard_3-2-1_096075_2023-01-03_final
2023-01-07 09:30:40	ga_ls8c_ard_3-2-1_092078_2023-01-07_final
2023-01-09 10:57:58	ga_ls8c_ard_3-2-1_106080_2023-01-09_final
2023-01-12 09:46:22	ga_ls8c_ard_3-2-1_095071_2023-01-12_final
2023-01-16 09:25:34	ga_ls8c_ard_3-2-1_091081_2023-01-15_final
2023-01-16 09:26:46	ga_ls8c_ard_3-2-1_091084_2023-01-15_final
2023-01-16 11:02:52	ga_ls8c_ard_3-2-1_107077_2023-01-16_final
2023-01-17 11:44:54	ga_ls8c_ard_3-2-1_114074_2023-01-17_final
2023-01-20 10:36:33	ga_ls8c_ard_3-2-1_103073_2023-01-20_final
2023-01-21 09:42:08	ga_ls8c_ard_3-2-1_094076_2023-01-21_final
2023-01-21 09:44:08	ga_ls8c_ard_3-2-1_094081_2023-01-21_final
2023-01-21 09:44:56	ga_ls8c_ard_3-2-1_094083_2023-01-21_final
2023-01-23 11:11:53	ga_ls8c_ard_3-2-1_108084_2023-01-23_final
2023-01-31 10:20:29	ga_ls8c_ard_3-2-1_100079_2023-01-31_final
2023-01-31 10:20:53	ga_ls8c_ard_3-2-1_100080_2023-01-31_final
2023-02-06 09:45:47	ga_ls8c_ard_3-2-1_094085_2023-02-06_final
2023-02-06 11:23:52	ga_ls8c_ard_3-2-1_110083_2023-02-06_final
2023-02-08 09:31:01	ga_ls8c_ard_3-2-1_092079_2023-02-08_final
2023-02-09 11:53:33	ga_ls8c_ard_3-2-1_115080_2023-02-09_final
2023-02-15 09:40:42	ga_ls8c_ard_3-2-1_093088_2023-02-15_final
2023-02-15 11:17:11	ga_ls8c_ard_3-2-1_109082_2023-02-15_final
2023-02-17 11:04:23	ga_ls8c_ard_3-2-1_107081_2023-02-17_final
2023-02-19 10:50:24	ga_ls8c_ard_3-2-1_105077_2023-02-19_final
2023-02-22 11:24:25	ga_ls8c_ard_3-2-1_110085_2023-02-22_final
2023-03-01 09:51:15	ga_ls8c_ard_3-2-1_095084_2023-03-01_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