Search ga_ls9c_ard_3 across August 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
2023-08-01 10:27:46	ga_ls9c_ard_3-2-1_102068_2023-08-01_final
2023-08-01 10:28:10	ga_ls9c_ard_3-2-1_102069_2023-08-01_final
2023-08-01 10:28:34	ga_ls9c_ard_3-2-1_102070_2023-08-01_final
2023-08-01 10:28:58	ga_ls9c_ard_3-2-1_102071_2023-08-01_final
2023-08-01 10:29:22	ga_ls9c_ard_3-2-1_102072_2023-08-01_final
2023-08-01 10:29:46	ga_ls9c_ard_3-2-1_102073_2023-08-01_final
2023-08-01 10:30:10	ga_ls9c_ard_3-2-1_102074_2023-08-01_final
2023-08-01 10:30:34	ga_ls9c_ard_3-2-1_102075_2023-08-01_final
2023-08-01 10:30:58	ga_ls9c_ard_3-2-1_102076_2023-08-01_final
2023-08-01 10:31:22	ga_ls9c_ard_3-2-1_102077_2023-08-01_final
2023-08-01 10:31:45	ga_ls9c_ard_3-2-1_102078_2023-08-01_final
2023-08-01 10:32:09	ga_ls9c_ard_3-2-1_102079_2023-08-01_final
2023-08-01 10:32:33	ga_ls9c_ard_3-2-1_102080_2023-08-01_final
2023-08-01 10:32:57	ga_ls9c_ard_3-2-1_102081_2023-08-01_final
2023-08-01 10:33:21	ga_ls9c_ard_3-2-1_102082_2023-08-01_final
2023-08-02 09:33:21	ga_ls9c_ard_3-2-1_093071_2023-08-02_final
2023-08-02 09:33:45	ga_ls9c_ard_3-2-1_093072_2023-08-02_final
2023-08-02 09:34:09	ga_ls9c_ard_3-2-1_093073_2023-08-02_final
2023-08-02 09:34:33	ga_ls9c_ard_3-2-1_093074_2023-08-02_final
2023-08-02 09:34:57	ga_ls9c_ard_3-2-1_093075_2023-08-02_final
2023-08-02 09:35:21	ga_ls9c_ard_3-2-1_093076_2023-08-02_final
2023-08-02 09:35:45	ga_ls9c_ard_3-2-1_093077_2023-08-02_final
2023-08-02 09:36:09	ga_ls9c_ard_3-2-1_093078_2023-08-02_final
2023-08-02 09:36:33	ga_ls9c_ard_3-2-1_093079_2023-08-02_final
2023-08-02 09:36:57	ga_ls9c_ard_3-2-1_093080_2023-08-02_final
2023-08-02 09:37:21	ga_ls9c_ard_3-2-1_093081_2023-08-02_final
2023-08-02 09:37:45	ga_ls9c_ard_3-2-1_093082_2023-08-02_final
2023-08-02 09:38:09	ga_ls9c_ard_3-2-1_093083_2023-08-02_final
2023-08-02 09:38:33	ga_ls9c_ard_3-2-1_093084_2023-08-02_final
2023-08-02 09:38:57	ga_ls9c_ard_3-2-1_093085_2023-08-02_final
2023-08-02 09:39:21	ga_ls9c_ard_3-2-1_093086_2023-08-02_final
2023-08-02 09:39:44	ga_ls9c_ard_3-2-1_093087_2023-08-02_final
2023-08-02 09:40:08	ga_ls9c_ard_3-2-1_093088_2023-08-02_final
2023-08-06 09:15:51	ga_ls9c_ard_3-2-1_089089_2023-08-05_final
2023-08-06 09:16:15	ga_ls9c_ard_3-2-1_089090_2023-08-05_final
2023-08-06 10:45:58	ga_ls9c_ard_3-2-1_105067_2023-08-06_final
2023-08-06 10:46:22	ga_ls9c_ard_3-2-1_105068_2023-08-06_final
2023-08-06 10:46:46	ga_ls9c_ard_3-2-1_105069_2023-08-06_final
2023-08-06 10:47:10	ga_ls9c_ard_3-2-1_105070_2023-08-06_final
2023-08-06 10:47:57	ga_ls9c_ard_3-2-1_105072_2023-08-06_final
2023-08-06 10:48:21	ga_ls9c_ard_3-2-1_105073_2023-08-06_final
2023-08-06 10:48:45	ga_ls9c_ard_3-2-1_105074_2023-08-06_final
2023-08-06 10:49:09	ga_ls9c_ard_3-2-1_105075_2023-08-06_final
2023-08-06 10:49:33	ga_ls9c_ard_3-2-1_105076_2023-08-06_final
2023-08-06 10:49:57	ga_ls9c_ard_3-2-1_105077_2023-08-06_final
2023-08-06 10:50:21	ga_ls9c_ard_3-2-1_105078_2023-08-06_final
2023-08-06 10:50:45	ga_ls9c_ard_3-2-1_105079_2023-08-06_final
2023-08-06 10:51:09	ga_ls9c_ard_3-2-1_105080_2023-08-06_final
2023-08-06 10:51:33	ga_ls9c_ard_3-2-1_105081_2023-08-06_final
2023-08-06 10:51:57	ga_ls9c_ard_3-2-1_105082_2023-08-06_final
2023-08-06 10:52:21	ga_ls9c_ard_3-2-1_105083_2023-08-06_final
2023-08-08 10:34:01	ga_ls9c_ard_3-2-1_103068_2023-08-08_final
2023-08-08 10:34:25	ga_ls9c_ard_3-2-1_103069_2023-08-08_final
2023-08-08 10:34:49	ga_ls9c_ard_3-2-1_103070_2023-08-08_final
2023-08-08 10:35:13	ga_ls9c_ard_3-2-1_103071_2023-08-08_final
2023-08-08 10:35:36	ga_ls9c_ard_3-2-1_103072_2023-08-08_final
2023-08-08 10:36:00	ga_ls9c_ard_3-2-1_103073_2023-08-08_final
2023-08-08 10:36:24	ga_ls9c_ard_3-2-1_103074_2023-08-08_final
2023-08-08 10:36:48	ga_ls9c_ard_3-2-1_103075_2023-08-08_final
2023-08-08 10:37:12	ga_ls9c_ard_3-2-1_103076_2023-08-08_final
2023-08-08 10:37:36	ga_ls9c_ard_3-2-1_103077_2023-08-08_final
2023-08-08 10:38:00	ga_ls9c_ard_3-2-1_103078_2023-08-08_final
2023-08-08 10:38:24	ga_ls9c_ard_3-2-1_103079_2023-08-08_final
2023-08-08 10:38:48	ga_ls9c_ard_3-2-1_103080_2023-08-08_final
2023-08-08 10:39:12	ga_ls9c_ard_3-2-1_103081_2023-08-08_final
2023-08-08 10:39:36	ga_ls9c_ard_3-2-1_103082_2023-08-08_final
2023-08-08 14:03:22	ga_ls9c_ard_3-2-1_135097_2023-08-08_final
2023-08-09 09:39:35	ga_ls9c_ard_3-2-1_094071_2023-08-09_final
2023-08-09 09:39:59	ga_ls9c_ard_3-2-1_094072_2023-08-09_final
2023-08-09 09:40:23	ga_ls9c_ard_3-2-1_094073_2023-08-09_final
2023-08-09 09:40:47	ga_ls9c_ard_3-2-1_094074_2023-08-09_final
2023-08-09 09:41:11	ga_ls9c_ard_3-2-1_094075_2023-08-09_final
2023-08-09 09:41:35	ga_ls9c_ard_3-2-1_094076_2023-08-09_final
2023-08-09 09:41:59	ga_ls9c_ard_3-2-1_094077_2023-08-09_final
2023-08-09 09:42:23	ga_ls9c_ard_3-2-1_094078_2023-08-09_final
2023-08-09 09:42:47	ga_ls9c_ard_3-2-1_094079_2023-08-09_final
2023-08-09 09:43:11	ga_ls9c_ard_3-2-1_094080_2023-08-09_final
2023-08-09 09:43:35	ga_ls9c_ard_3-2-1_094081_2023-08-09_final
2023-08-09 09:43:59	ga_ls9c_ard_3-2-1_094082_2023-08-09_final
2023-08-09 09:44:23	ga_ls9c_ard_3-2-1_094083_2023-08-09_final
2023-08-09 09:44:47	ga_ls9c_ard_3-2-1_094084_2023-08-09_final
2023-08-09 09:45:11	ga_ls9c_ard_3-2-1_094085_2023-08-09_final
2023-08-09 09:45:35	ga_ls9c_ard_3-2-1_094086_2023-08-09_final
2023-08-09 09:45:59	ga_ls9c_ard_3-2-1_094087_2023-08-09_final
2023-08-09 11:17:41	ga_ls9c_ard_3-2-1_110069_2023-08-09_final
2023-08-09 11:18:05	ga_ls9c_ard_3-2-1_110070_2023-08-09_final
2023-08-09 11:18:29	ga_ls9c_ard_3-2-1_110071_2023-08-09_final
2023-08-09 11:18:52	ga_ls9c_ard_3-2-1_110072_2023-08-09_final
2023-08-09 11:19:16	ga_ls9c_ard_3-2-1_110073_2023-08-09_final
2023-08-09 11:19:40	ga_ls9c_ard_3-2-1_110074_2023-08-09_final
2023-08-09 11:20:04	ga_ls9c_ard_3-2-1_110075_2023-08-09_final
2023-08-09 11:20:28	ga_ls9c_ard_3-2-1_110076_2023-08-09_final
2023-08-09 11:20:52	ga_ls9c_ard_3-2-1_110077_2023-08-09_final
2023-08-09 11:21:16	ga_ls9c_ard_3-2-1_110078_2023-08-09_final
2023-08-09 11:21:40	ga_ls9c_ard_3-2-1_110079_2023-08-09_final
2023-08-09 11:22:04	ga_ls9c_ard_3-2-1_110080_2023-08-09_final
2023-08-09 11:22:28	ga_ls9c_ard_3-2-1_110081_2023-08-09_final
2023-08-09 11:22:52	ga_ls9c_ard_3-2-1_110082_2023-08-09_final
2023-08-09 11:23:16	ga_ls9c_ard_3-2-1_110083_2023-08-09_final
2023-08-09 11:23:40	ga_ls9c_ard_3-2-1_110084_2023-08-09_final

Return to ga_ls9c_ard_3 across August 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

August

All days