Search ga_ls9c_ard_3 across June 2023

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
2023-06-01 09:21:09	ga_ls9c_ard_3-2-1_091072_2023-05-31_final
2023-06-01 09:21:33	ga_ls9c_ard_3-2-1_091073_2023-05-31_final
2023-06-01 09:21:57	ga_ls9c_ard_3-2-1_091074_2023-05-31_final
2023-06-01 09:22:21	ga_ls9c_ard_3-2-1_091075_2023-05-31_final
2023-06-01 09:22:45	ga_ls9c_ard_3-2-1_091076_2023-05-31_final
2023-06-01 09:23:09	ga_ls9c_ard_3-2-1_091077_2023-05-31_final
2023-06-01 09:23:33	ga_ls9c_ard_3-2-1_091078_2023-05-31_final
2023-06-01 09:23:57	ga_ls9c_ard_3-2-1_091079_2023-05-31_final
2023-06-01 09:24:21	ga_ls9c_ard_3-2-1_091080_2023-05-31_final
2023-06-01 09:24:45	ga_ls9c_ard_3-2-1_091081_2023-05-31_final
2023-06-01 09:25:09	ga_ls9c_ard_3-2-1_091082_2023-05-31_final
2023-06-01 09:25:33	ga_ls9c_ard_3-2-1_091083_2023-05-31_final
2023-06-01 09:25:57	ga_ls9c_ard_3-2-1_091084_2023-05-31_final
2023-06-01 09:26:20	ga_ls9c_ard_3-2-1_091085_2023-05-31_final
2023-06-01 09:26:44	ga_ls9c_ard_3-2-1_091086_2023-05-31_final
2023-06-01 09:27:08	ga_ls9c_ard_3-2-1_091087_2023-05-31_final
2023-06-01 09:27:32	ga_ls9c_ard_3-2-1_091088_2023-05-31_final
2023-06-01 09:27:56	ga_ls9c_ard_3-2-1_091089_2023-05-31_final
2023-06-01 09:28:20	ga_ls9c_ard_3-2-1_091090_2023-05-31_final
2023-06-01 10:58:50	ga_ls9c_ard_3-2-1_107069_2023-06-01_final
2023-06-01 10:59:14	ga_ls9c_ard_3-2-1_107070_2023-06-01_final
2023-06-01 10:59:38	ga_ls9c_ard_3-2-1_107071_2023-06-01_final
2023-06-01 11:00:02	ga_ls9c_ard_3-2-1_107072_2023-06-01_final
2023-06-01 11:00:26	ga_ls9c_ard_3-2-1_107073_2023-06-01_final
2023-06-01 11:00:50	ga_ls9c_ard_3-2-1_107074_2023-06-01_final
2023-06-01 11:01:14	ga_ls9c_ard_3-2-1_107075_2023-06-01_final
2023-06-01 11:01:38	ga_ls9c_ard_3-2-1_107076_2023-06-01_final
2023-06-01 11:02:02	ga_ls9c_ard_3-2-1_107077_2023-06-01_final
2023-06-01 11:02:26	ga_ls9c_ard_3-2-1_107078_2023-06-01_final
2023-06-01 11:02:50	ga_ls9c_ard_3-2-1_107079_2023-06-01_final
2023-06-01 11:03:14	ga_ls9c_ard_3-2-1_107080_2023-06-01_final
2023-06-01 11:03:38	ga_ls9c_ard_3-2-1_107081_2023-06-01_final
2023-06-01 11:04:02	ga_ls9c_ard_3-2-1_107082_2023-06-01_final
2023-06-01 11:04:26	ga_ls9c_ard_3-2-1_107083_2023-06-01_final
2023-06-01 11:04:50	ga_ls9c_ard_3-2-1_107084_2023-06-01_final
2023-06-01 12:36:56	ga_ls9c_ard_3-2-1_123067_2023-06-01_final
2023-06-02 10:02:01	ga_ls9c_ard_3-2-1_098066_2023-06-02_final
2023-06-02 10:02:25	ga_ls9c_ard_3-2-1_098067_2023-06-02_final
2023-06-02 10:02:49	ga_ls9c_ard_3-2-1_098068_2023-06-02_final
2023-06-02 10:03:13	ga_ls9c_ard_3-2-1_098069_2023-06-02_final
2023-06-02 10:03:37	ga_ls9c_ard_3-2-1_098070_2023-06-02_final
2023-06-02 10:04:01	ga_ls9c_ard_3-2-1_098071_2023-06-02_final
2023-06-02 10:04:25	ga_ls9c_ard_3-2-1_098072_2023-06-02_final
2023-06-02 10:04:49	ga_ls9c_ard_3-2-1_098073_2023-06-02_final
2023-06-02 10:05:13	ga_ls9c_ard_3-2-1_098074_2023-06-02_final
2023-06-02 10:05:36	ga_ls9c_ard_3-2-1_098075_2023-06-02_final
2023-06-02 10:06:00	ga_ls9c_ard_3-2-1_098076_2023-06-02_final
2023-06-02 10:06:24	ga_ls9c_ard_3-2-1_098077_2023-06-02_final
2023-06-02 10:06:48	ga_ls9c_ard_3-2-1_098078_2023-06-02_final
2023-06-02 10:07:12	ga_ls9c_ard_3-2-1_098079_2023-06-02_final
2023-06-02 10:07:36	ga_ls9c_ard_3-2-1_098080_2023-06-02_final
2023-06-02 10:08:00	ga_ls9c_ard_3-2-1_098081_2023-06-02_final
2023-06-02 10:08:24	ga_ls9c_ard_3-2-1_098082_2023-06-02_final
2023-06-02 10:08:48	ga_ls9c_ard_3-2-1_098083_2023-06-02_final
2023-06-02 10:09:12	ga_ls9c_ard_3-2-1_098084_2023-06-02_final
2023-06-02 10:09:36	ga_ls9c_ard_3-2-1_098085_2023-06-02_final
2023-06-02 11:44:06	ga_ls9c_ard_3-2-1_114074_2023-06-02_final
2023-06-02 11:44:30	ga_ls9c_ard_3-2-1_114075_2023-06-02_final
2023-06-02 11:44:53	ga_ls9c_ard_3-2-1_114076_2023-06-02_final
2023-06-02 11:45:17	ga_ls9c_ard_3-2-1_114077_2023-06-02_final
2023-06-02 11:45:41	ga_ls9c_ard_3-2-1_114078_2023-06-02_final
2023-06-02 11:46:05	ga_ls9c_ard_3-2-1_114079_2023-06-02_final
2023-06-02 11:46:29	ga_ls9c_ard_3-2-1_114080_2023-06-02_final
2023-06-02 11:46:53	ga_ls9c_ard_3-2-1_114081_2023-06-02_final
2023-06-03 09:09:35	ga_ls9c_ard_3-2-1_089074_2023-06-02_final
2023-06-03 09:09:59	ga_ls9c_ard_3-2-1_089075_2023-06-02_final
2023-06-03 09:10:23	ga_ls9c_ard_3-2-1_089076_2023-06-02_final
2023-06-03 09:10:47	ga_ls9c_ard_3-2-1_089077_2023-06-02_final
2023-06-03 09:11:11	ga_ls9c_ard_3-2-1_089078_2023-06-02_final
2023-06-03 09:11:35	ga_ls9c_ard_3-2-1_089079_2023-06-02_final
2023-06-03 09:11:59	ga_ls9c_ard_3-2-1_089080_2023-06-02_final
2023-06-03 09:12:23	ga_ls9c_ard_3-2-1_089081_2023-06-02_final
2023-06-03 09:12:46	ga_ls9c_ard_3-2-1_089082_2023-06-02_final
2023-06-03 09:13:10	ga_ls9c_ard_3-2-1_089083_2023-06-02_final
2023-06-03 09:13:34	ga_ls9c_ard_3-2-1_089084_2023-06-02_final
2023-06-09 10:12:08	ga_ls9c_ard_3-2-1_099076_2023-06-09_final
2023-06-09 10:12:32	ga_ls9c_ard_3-2-1_099077_2023-06-09_final
2023-06-09 10:12:56	ga_ls9c_ard_3-2-1_099078_2023-06-09_final
2023-06-09 10:13:44	ga_ls9c_ard_3-2-1_099080_2023-06-09_final
2023-06-09 10:14:08	ga_ls9c_ard_3-2-1_099081_2023-06-09_final
2023-06-09 10:14:31	ga_ls9c_ard_3-2-1_099082_2023-06-09_final
2023-06-09 10:14:55	ga_ls9c_ard_3-2-1_099083_2023-06-09_final
2023-06-09 10:15:19	ga_ls9c_ard_3-2-1_099084_2023-06-09_final
2023-06-09 10:15:43	ga_ls9c_ard_3-2-1_099085_2023-06-09_final
2023-06-09 11:50:13	ga_ls9c_ard_3-2-1_115074_2023-06-09_final
2023-06-09 11:50:37	ga_ls9c_ard_3-2-1_115075_2023-06-09_final
2023-06-09 11:51:01	ga_ls9c_ard_3-2-1_115076_2023-06-09_final
2023-06-09 11:51:25	ga_ls9c_ard_3-2-1_115077_2023-06-09_final
2023-06-09 11:51:49	ga_ls9c_ard_3-2-1_115078_2023-06-09_final
2023-06-09 11:52:13	ga_ls9c_ard_3-2-1_115079_2023-06-09_final
2023-06-09 11:52:37	ga_ls9c_ard_3-2-1_115080_2023-06-09_final
2023-06-10 09:15:42	ga_ls9c_ard_3-2-1_090074_2023-06-09_final
2023-06-10 09:16:06	ga_ls9c_ard_3-2-1_090075_2023-06-09_final
2023-06-10 09:16:30	ga_ls9c_ard_3-2-1_090076_2023-06-09_final
2023-06-10 09:17:42	ga_ls9c_ard_3-2-1_090079_2023-06-09_final
2023-06-10 09:18:06	ga_ls9c_ard_3-2-1_090080_2023-06-09_final
2023-06-10 09:18:30	ga_ls9c_ard_3-2-1_090081_2023-06-09_final
2023-06-10 09:18:53	ga_ls9c_ard_3-2-1_090082_2023-06-09_final
2023-06-10 09:19:17	ga_ls9c_ard_3-2-1_090083_2023-06-09_final
2023-06-10 09:19:41	ga_ls9c_ard_3-2-1_090084_2023-06-09_final

Return to ga_ls9c_ard_3 across June 2023 overview

ga_ls9c_ard_3: Geoscience Australia Landsat 9 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

GA Collection 3

USGS Products

Collection 2 NBAR

Collection 2 NBAR Tiled

Pixel Quality

Collection 2 Level1

Tidal

Water Observations

Fractional Cover

Sentinel 2

Ingested Pixel Quality

Geomedians

TMAD

Telemetry data

Summary

Other Products

2023

June

All days