Search ga_ls8c_ard_3 across August 2022

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
2022-08-01 10:09:09	ga_ls8c_ard_3-2-1_099066_2022-08-01_final
2022-08-01 10:09:33	ga_ls8c_ard_3-2-1_099067_2022-08-01_final
2022-08-01 10:09:57	ga_ls8c_ard_3-2-1_099068_2022-08-01_final
2022-08-01 10:10:21	ga_ls8c_ard_3-2-1_099069_2022-08-01_final
2022-08-01 10:10:45	ga_ls8c_ard_3-2-1_099070_2022-08-01_final
2022-08-01 10:11:09	ga_ls8c_ard_3-2-1_099071_2022-08-01_final
2022-08-01 10:11:33	ga_ls8c_ard_3-2-1_099072_2022-08-01_final
2022-08-01 10:11:57	ga_ls8c_ard_3-2-1_099073_2022-08-01_final
2022-08-01 10:12:21	ga_ls8c_ard_3-2-1_099074_2022-08-01_final
2022-08-01 10:12:45	ga_ls8c_ard_3-2-1_099075_2022-08-01_final
2022-08-01 10:13:09	ga_ls8c_ard_3-2-1_099076_2022-08-01_final
2022-08-01 10:13:33	ga_ls8c_ard_3-2-1_099077_2022-08-01_final
2022-08-01 10:13:56	ga_ls8c_ard_3-2-1_099078_2022-08-01_final
2022-08-01 10:14:20	ga_ls8c_ard_3-2-1_099079_2022-08-01_final
2022-08-01 10:14:44	ga_ls8c_ard_3-2-1_099080_2022-08-01_final
2022-08-01 10:15:08	ga_ls8c_ard_3-2-1_099081_2022-08-01_final
2022-08-01 10:15:32	ga_ls8c_ard_3-2-1_099082_2022-08-01_final
2022-08-01 10:15:56	ga_ls8c_ard_3-2-1_099083_2022-08-01_final
2022-08-01 10:16:20	ga_ls8c_ard_3-2-1_099084_2022-08-01_final
2022-08-01 10:16:44	ga_ls8c_ard_3-2-1_099085_2022-08-01_final
2022-08-01 11:51:14	ga_ls8c_ard_3-2-1_115074_2022-08-01_final
2022-08-01 11:51:38	ga_ls8c_ard_3-2-1_115075_2022-08-01_final
2022-08-01 11:52:02	ga_ls8c_ard_3-2-1_115076_2022-08-01_final
2022-08-01 11:52:26	ga_ls8c_ard_3-2-1_115077_2022-08-01_final
2022-08-01 11:52:50	ga_ls8c_ard_3-2-1_115078_2022-08-01_final
2022-08-01 11:53:14	ga_ls8c_ard_3-2-1_115079_2022-08-01_final
2022-08-01 11:53:37	ga_ls8c_ard_3-2-1_115080_2022-08-01_final
2022-08-02 09:16:44	ga_ls8c_ard_3-2-1_090074_2022-08-01_final
2022-08-02 09:17:08	ga_ls8c_ard_3-2-1_090075_2022-08-01_final
2022-08-02 09:17:32	ga_ls8c_ard_3-2-1_090076_2022-08-01_final
2022-08-02 09:17:56	ga_ls8c_ard_3-2-1_090077_2022-08-01_final
2022-08-02 09:18:20	ga_ls8c_ard_3-2-1_090078_2022-08-01_final
2022-08-02 09:18:44	ga_ls8c_ard_3-2-1_090079_2022-08-01_final
2022-08-02 09:19:08	ga_ls8c_ard_3-2-1_090080_2022-08-01_final
2022-08-02 09:19:32	ga_ls8c_ard_3-2-1_090081_2022-08-01_final
2022-08-02 09:19:56	ga_ls8c_ard_3-2-1_090082_2022-08-01_final
2022-08-02 09:20:19	ga_ls8c_ard_3-2-1_090083_2022-08-01_final
2022-08-02 09:20:43	ga_ls8c_ard_3-2-1_090084_2022-08-01_final
2022-08-02 09:21:07	ga_ls8c_ard_3-2-1_090085_2022-08-01_final
2022-08-02 09:21:31	ga_ls8c_ard_3-2-1_090086_2022-08-01_final
2022-08-02 09:21:55	ga_ls8c_ard_3-2-1_090087_2022-08-01_final
2022-08-02 09:22:19	ga_ls8c_ard_3-2-1_090088_2022-08-01_final
2022-08-02 09:22:43	ga_ls8c_ard_3-2-1_090089_2022-08-01_final
2022-08-02 09:23:07	ga_ls8c_ard_3-2-1_090090_2022-08-01_final
2022-08-02 09:23:31	ga_ls8c_ard_3-2-1_090091_2022-08-01_final
2022-08-02 10:52:49	ga_ls8c_ard_3-2-1_106067_2022-08-02_final
2022-08-02 10:53:13	ga_ls8c_ard_3-2-1_106068_2022-08-02_final
2022-08-02 10:53:37	ga_ls8c_ard_3-2-1_106069_2022-08-02_final
2022-08-02 10:54:01	ga_ls8c_ard_3-2-1_106070_2022-08-02_final
2022-08-02 10:54:25	ga_ls8c_ard_3-2-1_106071_2022-08-02_final
2022-08-02 10:54:49	ga_ls8c_ard_3-2-1_106072_2022-08-02_final
2022-08-02 10:55:13	ga_ls8c_ard_3-2-1_106073_2022-08-02_final
2022-08-02 10:55:37	ga_ls8c_ard_3-2-1_106074_2022-08-02_final
2022-08-02 10:56:01	ga_ls8c_ard_3-2-1_106075_2022-08-02_final
2022-08-02 10:56:25	ga_ls8c_ard_3-2-1_106076_2022-08-02_final
2022-08-02 10:56:49	ga_ls8c_ard_3-2-1_106077_2022-08-02_final
2022-08-02 10:57:13	ga_ls8c_ard_3-2-1_106078_2022-08-02_final
2022-08-02 10:57:37	ga_ls8c_ard_3-2-1_106079_2022-08-02_final
2022-08-02 10:58:01	ga_ls8c_ard_3-2-1_106080_2022-08-02_final
2022-08-02 10:58:25	ga_ls8c_ard_3-2-1_106081_2022-08-02_final
2022-08-02 10:58:49	ga_ls8c_ard_3-2-1_106082_2022-08-02_final
2022-08-02 10:59:12	ga_ls8c_ard_3-2-1_106083_2022-08-02_final
2022-08-02 12:31:43	ga_ls8c_ard_3-2-1_122067_2022-08-02_final
2022-08-07 09:39:18	ga_ls8c_ard_3-2-1_093084_2022-08-07_final
2022-08-07 09:39:42	ga_ls8c_ard_3-2-1_093085_2022-08-07_final
2022-08-07 09:40:06	ga_ls8c_ard_3-2-1_093086_2022-08-07_final
2022-08-07 09:40:30	ga_ls8c_ard_3-2-1_093087_2022-08-07_final
2022-08-07 09:40:54	ga_ls8c_ard_3-2-1_093088_2022-08-07_final
2022-08-07 11:12:12	ga_ls8c_ard_3-2-1_109069_2022-08-07_final
2022-08-07 11:12:36	ga_ls8c_ard_3-2-1_109070_2022-08-07_final
2022-08-07 11:13:00	ga_ls8c_ard_3-2-1_109071_2022-08-07_final
2022-08-07 11:13:24	ga_ls8c_ard_3-2-1_109072_2022-08-07_final
2022-08-07 11:13:48	ga_ls8c_ard_3-2-1_109073_2022-08-07_final
2022-08-07 11:14:12	ga_ls8c_ard_3-2-1_109074_2022-08-07_final
2022-08-07 11:14:36	ga_ls8c_ard_3-2-1_109075_2022-08-07_final
2022-08-07 11:15:00	ga_ls8c_ard_3-2-1_109076_2022-08-07_final
2022-08-07 11:15:24	ga_ls8c_ard_3-2-1_109077_2022-08-07_final
2022-08-07 11:15:48	ga_ls8c_ard_3-2-1_109078_2022-08-07_final
2022-08-07 11:16:12	ga_ls8c_ard_3-2-1_109079_2022-08-07_final
2022-08-07 11:16:36	ga_ls8c_ard_3-2-1_109080_2022-08-07_final
2022-08-07 11:17:00	ga_ls8c_ard_3-2-1_109081_2022-08-07_final
2022-08-07 11:17:24	ga_ls8c_ard_3-2-1_109082_2022-08-07_final
2022-08-07 11:17:48	ga_ls8c_ard_3-2-1_109083_2022-08-07_final
2022-08-07 11:18:11	ga_ls8c_ard_3-2-1_109084_2022-08-07_final
2022-08-08 10:17:47	ga_ls8c_ard_3-2-1_100072_2022-08-08_final
2022-08-08 10:18:11	ga_ls8c_ard_3-2-1_100073_2022-08-08_final
2022-08-08 10:18:35	ga_ls8c_ard_3-2-1_100074_2022-08-08_final
2022-08-08 10:18:59	ga_ls8c_ard_3-2-1_100075_2022-08-08_final
2022-08-08 10:19:23	ga_ls8c_ard_3-2-1_100076_2022-08-08_final
2022-08-08 10:19:47	ga_ls8c_ard_3-2-1_100077_2022-08-08_final
2022-08-08 10:20:11	ga_ls8c_ard_3-2-1_100078_2022-08-08_final
2022-08-08 10:20:35	ga_ls8c_ard_3-2-1_100079_2022-08-08_final
2022-08-08 10:20:59	ga_ls8c_ard_3-2-1_100080_2022-08-08_final
2022-08-08 10:21:23	ga_ls8c_ard_3-2-1_100081_2022-08-08_final
2022-08-08 10:21:47	ga_ls8c_ard_3-2-1_100082_2022-08-08_final
2022-08-08 10:22:11	ga_ls8c_ard_3-2-1_100083_2022-08-08_final
2022-08-08 11:58:16	ga_ls8c_ard_3-2-1_116076_2022-08-08_final
2022-08-08 11:58:40	ga_ls8c_ard_3-2-1_116077_2022-08-08_final
2022-08-09 09:22:10	ga_ls8c_ard_3-2-1_091072_2022-08-08_final
2022-08-09 09:22:34	ga_ls8c_ard_3-2-1_091073_2022-08-08_final

Return to ga_ls8c_ard_3 across August 2022 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

2022

August

All days