Search ga_ls8c_ard_3 across 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
2023-01-01 10:03:22	ga_ls8c_ard_3-2-1_098067_2023-01-01_final
2023-01-01 10:05:22	ga_ls8c_ard_3-2-1_098072_2023-01-01_final
2023-01-01 10:05:46	ga_ls8c_ard_3-2-1_098073_2023-01-01_final
2023-01-01 10:06:10	ga_ls8c_ard_3-2-1_098074_2023-01-01_final
2023-01-01 10:06:33	ga_ls8c_ard_3-2-1_098075_2023-01-01_final
2023-01-01 10:06:57	ga_ls8c_ard_3-2-1_098076_2023-01-01_final
2023-01-01 10:07:21	ga_ls8c_ard_3-2-1_098077_2023-01-01_final
2023-01-01 10:07:45	ga_ls8c_ard_3-2-1_098078_2023-01-01_final
2023-01-01 10:08:09	ga_ls8c_ard_3-2-1_098079_2023-01-01_final
2023-01-01 10:08:33	ga_ls8c_ard_3-2-1_098080_2023-01-01_final
2023-01-01 10:08:57	ga_ls8c_ard_3-2-1_098081_2023-01-01_final
2023-01-01 10:09:21	ga_ls8c_ard_3-2-1_098082_2023-01-01_final
2023-01-01 10:09:45	ga_ls8c_ard_3-2-1_098083_2023-01-01_final
2023-01-01 10:10:09	ga_ls8c_ard_3-2-1_098084_2023-01-01_final
2023-01-01 11:45:03	ga_ls8c_ard_3-2-1_114074_2023-01-01_final
2023-01-01 11:45:27	ga_ls8c_ard_3-2-1_114075_2023-01-01_final
2023-01-01 11:45:50	ga_ls8c_ard_3-2-1_114076_2023-01-01_final
2023-01-01 11:46:14	ga_ls8c_ard_3-2-1_114077_2023-01-01_final
2023-01-01 11:46:38	ga_ls8c_ard_3-2-1_114078_2023-01-01_final
2023-01-01 11:47:02	ga_ls8c_ard_3-2-1_114079_2023-01-01_final
2023-01-01 11:47:26	ga_ls8c_ard_3-2-1_114080_2023-01-01_final
2023-01-02 09:10:32	ga_ls8c_ard_3-2-1_089074_2023-01-01_final
2023-01-02 09:10:56	ga_ls8c_ard_3-2-1_089075_2023-01-01_final
2023-01-02 09:11:20	ga_ls8c_ard_3-2-1_089076_2023-01-01_final
2023-01-02 09:11:44	ga_ls8c_ard_3-2-1_089077_2023-01-01_final
2023-01-02 09:12:08	ga_ls8c_ard_3-2-1_089078_2023-01-01_final
2023-01-02 09:12:32	ga_ls8c_ard_3-2-1_089079_2023-01-01_final
2023-01-02 09:12:56	ga_ls8c_ard_3-2-1_089080_2023-01-01_final
2023-01-02 09:13:20	ga_ls8c_ard_3-2-1_089081_2023-01-01_final
2023-01-02 09:13:44	ga_ls8c_ard_3-2-1_089082_2023-01-01_final
2023-01-02 09:14:08	ga_ls8c_ard_3-2-1_089083_2023-01-01_final
2023-01-02 09:14:32	ga_ls8c_ard_3-2-1_089084_2023-01-01_final
2023-01-02 09:14:56	ga_ls8c_ard_3-2-1_089085_2023-01-01_final
2023-01-02 09:15:20	ga_ls8c_ard_3-2-1_089086_2023-01-01_final
2023-01-02 09:16:08	ga_ls8c_ard_3-2-1_089088_2023-01-01_final
2023-01-02 09:16:31	ga_ls8c_ard_3-2-1_089089_2023-01-01_final
2023-01-02 09:16:55	ga_ls8c_ard_3-2-1_089090_2023-01-01_final
2023-01-02 10:46:38	ga_ls8c_ard_3-2-1_105067_2023-01-02_final
2023-01-02 10:47:02	ga_ls8c_ard_3-2-1_105068_2023-01-02_final
2023-01-02 10:47:26	ga_ls8c_ard_3-2-1_105069_2023-01-02_final
2023-01-02 10:47:49	ga_ls8c_ard_3-2-1_105070_2023-01-02_final
2023-01-02 10:48:13	ga_ls8c_ard_3-2-1_105071_2023-01-02_final
2023-01-02 10:48:37	ga_ls8c_ard_3-2-1_105072_2023-01-02_final
2023-01-02 10:49:01	ga_ls8c_ard_3-2-1_105073_2023-01-02_final
2023-01-02 10:49:25	ga_ls8c_ard_3-2-1_105074_2023-01-02_final
2023-01-02 10:49:49	ga_ls8c_ard_3-2-1_105075_2023-01-02_final
2023-01-02 10:50:13	ga_ls8c_ard_3-2-1_105076_2023-01-02_final
2023-01-02 10:50:37	ga_ls8c_ard_3-2-1_105077_2023-01-02_final
2023-01-02 10:51:01	ga_ls8c_ard_3-2-1_105078_2023-01-02_final
2023-01-02 10:51:25	ga_ls8c_ard_3-2-1_105079_2023-01-02_final
2023-01-02 10:51:49	ga_ls8c_ard_3-2-1_105080_2023-01-02_final
2023-01-02 10:52:13	ga_ls8c_ard_3-2-1_105081_2023-01-02_final
2023-01-02 10:52:37	ga_ls8c_ard_3-2-1_105082_2023-01-02_final
2023-01-02 10:53:01	ga_ls8c_ard_3-2-1_105083_2023-01-02_final
2023-01-03 08:24:30	ga_ls8c_ard_3-2-1_080098_2023-01-02_final
2023-01-03 09:52:12	ga_ls8c_ard_3-2-1_096070_2023-01-03_final
2023-01-03 09:52:36	ga_ls8c_ard_3-2-1_096071_2023-01-03_final
2023-01-03 09:53:00	ga_ls8c_ard_3-2-1_096072_2023-01-03_final
2023-01-03 09:53:24	ga_ls8c_ard_3-2-1_096073_2023-01-03_final
2023-01-03 09:53:48	ga_ls8c_ard_3-2-1_096074_2023-01-03_final
2023-01-03 09:54:12	ga_ls8c_ard_3-2-1_096075_2023-01-03_final
2023-01-03 09:54:36	ga_ls8c_ard_3-2-1_096076_2023-01-03_final
2023-01-03 09:55:00	ga_ls8c_ard_3-2-1_096077_2023-01-03_final
2023-01-03 09:55:24	ga_ls8c_ard_3-2-1_096078_2023-01-03_final
2023-01-03 09:55:48	ga_ls8c_ard_3-2-1_096079_2023-01-03_final
2023-01-03 09:56:12	ga_ls8c_ard_3-2-1_096080_2023-01-03_final
2023-01-03 09:56:35	ga_ls8c_ard_3-2-1_096081_2023-01-03_final
2023-01-03 09:56:59	ga_ls8c_ard_3-2-1_096082_2023-01-03_final
2023-01-03 09:57:23	ga_ls8c_ard_3-2-1_096083_2023-01-03_final
2023-01-03 09:57:47	ga_ls8c_ard_3-2-1_096084_2023-01-03_final
2023-01-03 09:58:11	ga_ls8c_ard_3-2-1_096085_2023-01-03_final
2023-01-03 09:58:35	ga_ls8c_ard_3-2-1_096086_2023-01-03_final
2023-01-03 11:31:53	ga_ls8c_ard_3-2-1_112072_2023-01-03_final
2023-01-03 11:32:17	ga_ls8c_ard_3-2-1_112073_2023-01-03_final
2023-01-03 11:32:41	ga_ls8c_ard_3-2-1_112074_2023-01-03_final
2023-01-03 11:33:05	ga_ls8c_ard_3-2-1_112075_2023-01-03_final
2023-01-03 11:33:29	ga_ls8c_ard_3-2-1_112076_2023-01-03_final
2023-01-03 11:33:53	ga_ls8c_ard_3-2-1_112077_2023-01-03_final
2023-01-03 11:34:17	ga_ls8c_ard_3-2-1_112078_2023-01-03_final
2023-01-03 11:34:41	ga_ls8c_ard_3-2-1_112079_2023-01-03_final
2023-01-03 11:35:05	ga_ls8c_ard_3-2-1_112080_2023-01-03_final
2023-01-03 11:35:29	ga_ls8c_ard_3-2-1_112081_2023-01-03_final
2023-01-03 11:35:52	ga_ls8c_ard_3-2-1_112082_2023-01-03_final
2023-01-03 11:36:16	ga_ls8c_ard_3-2-1_112083_2023-01-03_final
2023-01-03 11:36:40	ga_ls8c_ard_3-2-1_112084_2023-01-03_final
2023-01-04 10:34:40	ga_ls8c_ard_3-2-1_103068_2023-01-04_final
2023-01-04 10:35:04	ga_ls8c_ard_3-2-1_103069_2023-01-04_final
2023-01-04 10:35:28	ga_ls8c_ard_3-2-1_103070_2023-01-04_final
2023-01-04 10:35:52	ga_ls8c_ard_3-2-1_103071_2023-01-04_final
2023-01-04 10:36:16	ga_ls8c_ard_3-2-1_103072_2023-01-04_final
2023-01-04 10:36:40	ga_ls8c_ard_3-2-1_103073_2023-01-04_final
2023-01-04 10:37:03	ga_ls8c_ard_3-2-1_103074_2023-01-04_final
2023-01-04 10:37:27	ga_ls8c_ard_3-2-1_103075_2023-01-04_final
2023-01-04 10:37:51	ga_ls8c_ard_3-2-1_103076_2023-01-04_final
2023-01-04 10:38:15	ga_ls8c_ard_3-2-1_103077_2023-01-04_final
2023-01-04 10:38:39	ga_ls8c_ard_3-2-1_103078_2023-01-04_final
2023-01-04 10:39:03	ga_ls8c_ard_3-2-1_103079_2023-01-04_final
2023-01-04 10:39:27	ga_ls8c_ard_3-2-1_103080_2023-01-04_final
2023-01-04 10:39:51	ga_ls8c_ard_3-2-1_103081_2023-01-04_final
2023-01-04 10:40:15	ga_ls8c_ard_3-2-1_103082_2023-01-04_final

Return to ga_ls8c_ard_3 across 2023 overview

ga_ls8c_ard_3: Geoscience Australia Landsat 8 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

All months