Search ga_ls9c_ard_3 across November 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
2023-11-01 09:16:27	ga_ls9c_ard_3-2-1_090074_2023-10-31_final
2023-11-01 09:16:51	ga_ls9c_ard_3-2-1_090075_2023-10-31_final
2023-11-01 09:17:15	ga_ls9c_ard_3-2-1_090076_2023-10-31_final
2023-11-01 09:17:39	ga_ls9c_ard_3-2-1_090077_2023-10-31_final
2023-11-01 09:18:03	ga_ls9c_ard_3-2-1_090078_2023-10-31_final
2023-11-01 09:18:27	ga_ls9c_ard_3-2-1_090079_2023-10-31_final
2023-11-01 09:18:50	ga_ls9c_ard_3-2-1_090080_2023-10-31_final
2023-11-01 09:19:14	ga_ls9c_ard_3-2-1_090081_2023-10-31_final
2023-11-01 09:19:38	ga_ls9c_ard_3-2-1_090082_2023-10-31_final
2023-11-01 09:20:02	ga_ls9c_ard_3-2-1_090083_2023-10-31_final
2023-11-01 09:20:26	ga_ls9c_ard_3-2-1_090084_2023-10-31_final
2023-11-01 09:20:50	ga_ls9c_ard_3-2-1_090085_2023-10-31_final
2023-11-01 09:21:14	ga_ls9c_ard_3-2-1_090086_2023-10-31_final
2023-11-01 09:21:38	ga_ls9c_ard_3-2-1_090087_2023-10-31_final
2023-11-01 09:22:02	ga_ls9c_ard_3-2-1_090088_2023-10-31_final
2023-11-01 09:22:26	ga_ls9c_ard_3-2-1_090089_2023-10-31_final
2023-11-01 09:22:50	ga_ls9c_ard_3-2-1_090090_2023-10-31_final
2023-11-01 10:52:56	ga_ls9c_ard_3-2-1_106068_2023-11-01_final
2023-11-01 10:53:20	ga_ls9c_ard_3-2-1_106069_2023-11-01_final
2023-11-01 10:53:44	ga_ls9c_ard_3-2-1_106070_2023-11-01_final
2023-11-01 10:54:08	ga_ls9c_ard_3-2-1_106071_2023-11-01_final
2023-11-01 10:54:32	ga_ls9c_ard_3-2-1_106072_2023-11-01_final
2023-11-01 10:54:56	ga_ls9c_ard_3-2-1_106073_2023-11-01_final
2023-11-01 10:55:20	ga_ls9c_ard_3-2-1_106074_2023-11-01_final
2023-11-01 10:55:44	ga_ls9c_ard_3-2-1_106075_2023-11-01_final
2023-11-01 10:56:08	ga_ls9c_ard_3-2-1_106076_2023-11-01_final
2023-11-01 10:56:32	ga_ls9c_ard_3-2-1_106077_2023-11-01_final
2023-11-01 10:56:55	ga_ls9c_ard_3-2-1_106078_2023-11-01_final
2023-11-01 10:57:19	ga_ls9c_ard_3-2-1_106079_2023-11-01_final
2023-11-01 10:57:43	ga_ls9c_ard_3-2-1_106080_2023-11-01_final
2023-11-01 10:58:07	ga_ls9c_ard_3-2-1_106081_2023-11-01_final
2023-11-01 10:58:31	ga_ls9c_ard_3-2-1_106082_2023-11-01_final
2023-11-01 10:58:55	ga_ls9c_ard_3-2-1_106083_2023-11-01_final
2023-11-01 12:31:25	ga_ls9c_ard_3-2-1_122067_2023-11-01_final
2023-11-02 09:56:54	ga_ls9c_ard_3-2-1_097067_2023-11-02_final
2023-11-02 09:57:18	ga_ls9c_ard_3-2-1_097068_2023-11-02_final
2023-11-02 09:57:42	ga_ls9c_ard_3-2-1_097069_2023-11-02_final
2023-11-02 09:58:06	ga_ls9c_ard_3-2-1_097070_2023-11-02_final
2023-11-02 09:58:29	ga_ls9c_ard_3-2-1_097071_2023-11-02_final
2023-11-02 09:58:53	ga_ls9c_ard_3-2-1_097072_2023-11-02_final
2023-11-02 09:59:17	ga_ls9c_ard_3-2-1_097073_2023-11-02_final
2023-11-02 09:59:41	ga_ls9c_ard_3-2-1_097074_2023-11-02_final
2023-11-02 10:00:05	ga_ls9c_ard_3-2-1_097075_2023-11-02_final
2023-11-02 10:00:29	ga_ls9c_ard_3-2-1_097076_2023-11-02_final
2023-11-02 10:00:53	ga_ls9c_ard_3-2-1_097077_2023-11-02_final
2023-11-02 10:01:17	ga_ls9c_ard_3-2-1_097078_2023-11-02_final
2023-11-02 10:01:41	ga_ls9c_ard_3-2-1_097079_2023-11-02_final
2023-11-02 10:02:05	ga_ls9c_ard_3-2-1_097080_2023-11-02_final
2023-11-02 10:02:29	ga_ls9c_ard_3-2-1_097081_2023-11-02_final
2023-11-02 10:02:53	ga_ls9c_ard_3-2-1_097082_2023-11-02_final
2023-11-02 10:03:17	ga_ls9c_ard_3-2-1_097083_2023-11-02_final
2023-11-02 10:03:41	ga_ls9c_ard_3-2-1_097084_2023-11-02_final
2023-11-02 10:04:05	ga_ls9c_ard_3-2-1_097085_2023-11-02_final
2023-11-08 10:59:56	ga_ls9c_ard_3-2-1_107070_2023-11-08_final
2023-11-08 11:00:20	ga_ls9c_ard_3-2-1_107071_2023-11-08_final
2023-11-08 11:00:44	ga_ls9c_ard_3-2-1_107072_2023-11-08_final
2023-11-08 11:01:08	ga_ls9c_ard_3-2-1_107073_2023-11-08_final
2023-11-08 11:01:32	ga_ls9c_ard_3-2-1_107074_2023-11-08_final
2023-11-08 11:01:56	ga_ls9c_ard_3-2-1_107075_2023-11-08_final
2023-11-08 11:02:20	ga_ls9c_ard_3-2-1_107076_2023-11-08_final
2023-11-08 11:02:44	ga_ls9c_ard_3-2-1_107077_2023-11-08_final
2023-11-08 11:03:08	ga_ls9c_ard_3-2-1_107078_2023-11-08_final
2023-11-08 11:03:32	ga_ls9c_ard_3-2-1_107079_2023-11-08_final
2023-11-08 11:03:56	ga_ls9c_ard_3-2-1_107080_2023-11-08_final
2023-11-08 11:04:20	ga_ls9c_ard_3-2-1_107081_2023-11-08_final
2023-11-08 11:04:44	ga_ls9c_ard_3-2-1_107082_2023-11-08_final
2023-11-08 11:05:08	ga_ls9c_ard_3-2-1_107083_2023-11-08_final
2023-11-08 11:05:32	ga_ls9c_ard_3-2-1_107084_2023-11-08_final
2023-11-09 10:03:08	ga_ls9c_ard_3-2-1_098067_2023-11-09_final
2023-11-09 10:03:31	ga_ls9c_ard_3-2-1_098068_2023-11-09_final
2023-11-09 10:03:55	ga_ls9c_ard_3-2-1_098069_2023-11-09_final
2023-11-09 10:04:19	ga_ls9c_ard_3-2-1_098070_2023-11-09_final
2023-11-09 10:04:43	ga_ls9c_ard_3-2-1_098071_2023-11-09_final
2023-11-09 10:05:07	ga_ls9c_ard_3-2-1_098072_2023-11-09_final
2023-11-09 10:06:43	ga_ls9c_ard_3-2-1_098076_2023-11-09_final
2023-11-09 10:07:07	ga_ls9c_ard_3-2-1_098077_2023-11-09_final
2023-11-09 10:07:31	ga_ls9c_ard_3-2-1_098078_2023-11-09_final
2023-11-09 10:07:55	ga_ls9c_ard_3-2-1_098079_2023-11-09_final
2023-11-09 10:08:19	ga_ls9c_ard_3-2-1_098080_2023-11-09_final
2023-11-09 10:08:43	ga_ls9c_ard_3-2-1_098081_2023-11-09_final
2023-11-09 10:09:07	ga_ls9c_ard_3-2-1_098082_2023-11-09_final
2023-11-09 10:09:31	ga_ls9c_ard_3-2-1_098083_2023-11-09_final
2023-11-09 10:09:55	ga_ls9c_ard_3-2-1_098084_2023-11-09_final
2023-11-09 10:10:19	ga_ls9c_ard_3-2-1_098085_2023-11-09_final
2023-11-09 11:44:48	ga_ls9c_ard_3-2-1_114074_2023-11-09_final
2023-11-09 11:45:12	ga_ls9c_ard_3-2-1_114075_2023-11-09_final
2023-11-09 11:45:36	ga_ls9c_ard_3-2-1_114076_2023-11-09_final
2023-11-09 11:46:00	ga_ls9c_ard_3-2-1_114077_2023-11-09_final
2023-11-09 11:46:24	ga_ls9c_ard_3-2-1_114078_2023-11-09_final
2023-11-09 11:46:48	ga_ls9c_ard_3-2-1_114079_2023-11-09_final
2023-11-09 11:47:12	ga_ls9c_ard_3-2-1_114080_2023-11-09_final
2023-11-09 11:47:36	ga_ls9c_ard_3-2-1_114081_2023-11-09_final
2023-11-10 09:11:54	ga_ls9c_ard_3-2-1_089078_2023-11-09_final
2023-11-10 09:12:18	ga_ls9c_ard_3-2-1_089079_2023-11-09_final
2023-11-10 09:12:42	ga_ls9c_ard_3-2-1_089080_2023-11-09_final
2023-11-10 09:13:06	ga_ls9c_ard_3-2-1_089081_2023-11-09_final
2023-11-10 09:13:29	ga_ls9c_ard_3-2-1_089082_2023-11-09_final
2023-11-10 09:13:53	ga_ls9c_ard_3-2-1_089083_2023-11-09_final
2023-11-10 09:14:17	ga_ls9c_ard_3-2-1_089084_2023-11-09_final
2023-11-10 09:14:41	ga_ls9c_ard_3-2-1_089085_2023-11-09_final

Return to ga_ls9c_ard_3 across November 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

November

All days