Search ga_ls9c_ard_3 whole collection

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
2021-11-01 10:12:54	ga_ls9c_ard_3-2-1_099073_2021-11-01_final
2021-11-06 10:15:47	ga_ls9c_ard_3-2-1_100074_2021-11-06_final
2021-11-08 10:00:13	ga_ls9c_ard_3-2-1_097082_2021-11-08_final
2021-11-08 10:00:37	ga_ls9c_ard_3-2-1_097083_2021-11-08_final
2021-11-13 10:03:05	ga_ls9c_ard_3-2-1_097083_2021-11-13_final
2021-11-18 10:05:33	ga_ls9c_ard_3-2-1_097083_2021-11-18_final
2021-11-23 10:07:36	ga_ls9c_ard_3-2-1_098082_2021-11-23_final
2021-12-14 10:03:27	ga_ls9c_ard_3-2-1_097083_2021-12-14_final
2021-12-21 10:09:13	ga_ls9c_ard_3-2-1_098082_2021-12-21_final
2021-12-28 10:11:49	ga_ls9c_ard_3-2-1_099073_2021-12-28_final
2021-12-30 10:03:26	ga_ls9c_ard_3-2-1_097083_2021-12-30_final
2022-01-06 10:09:12	ga_ls9c_ard_3-2-1_098082_2022-01-06_final
2022-01-15 10:03:23	ga_ls9c_ard_3-2-1_097083_2022-01-15_final
2022-01-22 10:09:12	ga_ls9c_ard_3-2-1_098082_2022-01-22_final
2022-01-31 10:03:26	ga_ls9c_ard_3-2-1_097083_2022-01-31_final
2022-02-07 10:09:11	ga_ls9c_ard_3-2-1_098082_2022-02-07_final
2022-02-16 10:03:21	ga_ls9c_ard_3-2-1_097083_2022-02-16_final
2022-03-04 10:03:10	ga_ls9c_ard_3-2-1_097083_2022-03-04_final
2022-03-20 10:03:09	ga_ls9c_ard_3-2-1_097083_2022-03-20_final
2022-04-05 10:02:41	ga_ls9c_ard_3-2-1_097082_2022-04-05_final
2022-04-05 10:03:05	ga_ls9c_ard_3-2-1_097083_2022-04-05_final
2022-04-19 10:11:19	ga_ls9c_ard_3-2-1_099073_2022-04-19_final
2022-04-19 10:11:43	ga_ls9c_ard_3-2-1_099074_2022-04-19_final
2022-04-21 10:02:55	ga_ls9c_ard_3-2-1_097083_2022-04-21_final
2022-05-07 10:02:51	ga_ls9c_ard_3-2-1_097083_2022-05-07_final
2022-05-21 10:11:02	ga_ls9c_ard_3-2-1_099073_2022-05-21_final
2022-05-23 10:02:40	ga_ls9c_ard_3-2-1_097083_2022-05-23_final
2022-06-06 10:11:04	ga_ls9c_ard_3-2-1_099073_2022-06-06_final
2022-06-08 10:02:17	ga_ls9c_ard_3-2-1_097082_2022-06-08_final
2022-06-08 10:02:41	ga_ls9c_ard_3-2-1_097083_2022-06-08_final
2022-06-22 10:11:19	ga_ls9c_ard_3-2-1_099073_2022-06-22_final
2022-07-08 10:11:22	ga_ls9c_ard_3-2-1_099073_2022-07-08_final
2022-07-10 10:02:59	ga_ls9c_ard_3-2-1_097083_2022-07-10_final
2022-07-24 10:11:29	ga_ls9c_ard_3-2-1_099073_2022-07-24_final
2022-07-26 10:03:08	ga_ls9c_ard_3-2-1_097083_2022-07-26_final
2022-08-09 10:12:04	ga_ls9c_ard_3-2-1_099074_2022-08-09_final
2022-08-11 10:02:55	ga_ls9c_ard_3-2-1_097082_2022-08-11_final
2022-08-11 10:03:19	ga_ls9c_ard_3-2-1_097083_2022-08-11_final
2022-08-25 10:11:45	ga_ls9c_ard_3-2-1_099073_2022-08-25_final
2022-08-25 10:12:09	ga_ls9c_ard_3-2-1_099074_2022-08-25_final
2022-09-19 10:09:15	ga_ls9c_ard_3-2-1_098082_2022-09-19_final
2022-09-26 10:11:53	ga_ls9c_ard_3-2-1_099073_2022-09-26_final
2022-09-28 10:03:07	ga_ls9c_ard_3-2-1_097082_2022-09-28_final
2022-11-06 10:09:21	ga_ls9c_ard_3-2-1_098082_2022-11-06_final
2022-11-13 10:11:59	ga_ls9c_ard_3-2-1_099073_2022-11-13_final
2022-11-15 10:03:38	ga_ls9c_ard_3-2-1_097083_2022-11-15_final
2022-11-29 10:11:57	ga_ls9c_ard_3-2-1_099073_2022-11-29_final
2022-11-29 10:12:21	ga_ls9c_ard_3-2-1_099074_2022-11-29_final
2022-12-01 10:03:10	ga_ls9c_ard_3-2-1_097082_2022-12-01_final
2022-12-01 10:03:34	ga_ls9c_ard_3-2-1_097083_2022-12-01_final
2022-12-08 10:09:23	ga_ls9c_ard_3-2-1_098082_2022-12-08_final
2022-12-15 10:11:58	ga_ls9c_ard_3-2-1_099073_2022-12-15_final
2022-12-15 10:12:22	ga_ls9c_ard_3-2-1_099074_2022-12-15_final
2022-12-17 10:03:12	ga_ls9c_ard_3-2-1_097082_2022-12-17_final
2022-12-17 10:03:36	ga_ls9c_ard_3-2-1_097083_2022-12-17_final
2022-12-31 10:11:58	ga_ls9c_ard_3-2-1_099073_2022-12-31_final
2023-01-02 10:03:36	ga_ls9c_ard_3-2-1_097083_2023-01-02_final
2023-01-09 10:09:23	ga_ls9c_ard_3-2-1_098082_2023-01-09_final
2023-01-16 10:11:54	ga_ls9c_ard_3-2-1_099073_2023-01-16_final
2023-01-18 10:03:05	ga_ls9c_ard_3-2-1_097082_2023-01-18_final
2023-02-01 10:11:59	ga_ls9c_ard_3-2-1_099073_2023-02-01_final
2023-02-03 10:03:38	ga_ls9c_ard_3-2-1_097083_2023-02-03_final
2023-02-17 10:12:21	ga_ls9c_ard_3-2-1_099074_2023-02-17_final
2023-02-19 10:03:08	ga_ls9c_ard_3-2-1_097082_2023-02-19_final
2023-02-19 10:03:32	ga_ls9c_ard_3-2-1_097083_2023-02-19_final
2023-03-05 10:11:45	ga_ls9c_ard_3-2-1_099073_2023-03-05_final
2023-03-05 10:12:09	ga_ls9c_ard_3-2-1_099074_2023-03-05_final
2023-03-07 10:03:20	ga_ls9c_ard_3-2-1_097083_2023-03-07_final
2023-03-14 10:09:05	ga_ls9c_ard_3-2-1_098082_2023-03-14_final
2023-03-21 10:11:38	ga_ls9c_ard_3-2-1_099073_2023-03-21_final
2023-03-23 10:03:15	ga_ls9c_ard_3-2-1_097083_2023-03-23_final
2023-04-06 10:11:28	ga_ls9c_ard_3-2-1_099073_2023-04-06_final
2023-04-08 10:03:05	ga_ls9c_ard_3-2-1_097083_2023-04-08_final
2023-04-22 10:11:22	ga_ls9c_ard_3-2-1_099073_2023-04-22_final
2023-04-24 10:02:59	ga_ls9c_ard_3-2-1_097083_2023-04-24_final
2023-05-08 10:11:10	ga_ls9c_ard_3-2-1_099073_2023-05-08_final
2023-05-10 10:02:48	ga_ls9c_ard_3-2-1_097083_2023-05-10_final
2023-05-24 10:11:00	ga_ls9c_ard_3-2-1_099073_2023-05-24_final
2023-05-26 10:02:38	ga_ls9c_ard_3-2-1_097083_2023-05-26_final
2023-06-09 10:10:56	ga_ls9c_ard_3-2-1_099073_2023-06-09_final
2023-06-25 10:10:50	ga_ls9c_ard_3-2-1_099073_2023-06-25_final
2023-07-11 10:11:06	ga_ls9c_ard_3-2-1_099073_2023-07-11_final
2023-07-27 10:11:08	ga_ls9c_ard_3-2-1_099073_2023-07-27_final
2023-08-12 10:11:18	ga_ls9c_ard_3-2-1_099073_2023-08-12_final
2023-08-28 10:11:26	ga_ls9c_ard_3-2-1_099073_2023-08-28_final
2023-09-13 10:11:36	ga_ls9c_ard_3-2-1_099073_2023-09-13_final
2023-09-29 10:11:32	ga_ls9c_ard_3-2-1_099073_2023-09-29_final
2023-10-15 10:11:45	ga_ls9c_ard_3-2-1_099073_2023-10-15_final
2023-10-31 10:11:41	ga_ls9c_ard_3-2-1_099073_2023-10-31_final
2023-11-16 10:11:42	ga_ls9c_ard_3-2-1_099073_2023-11-16_final
2023-12-02 10:11:49	ga_ls9c_ard_3-2-1_099073_2023-12-02_final
2023-12-18 10:11:51	ga_ls9c_ard_3-2-1_099073_2023-12-18_final
2024-01-03 10:11:47	ga_ls9c_ard_3-2-1_099073_2024-01-03_final
2024-01-19 10:11:47	ga_ls9c_ard_3-2-1_099073_2024-01-19_final
2024-02-04 10:11:50	ga_ls9c_ard_3-2-1_099073_2024-02-04_final
2024-02-20 10:11:40	ga_ls9c_ard_3-2-1_099073_2024-02-20_final
2024-03-23 10:11:39	ga_ls9c_ard_3-2-1_099073_2024-03-23_final
2024-04-08 10:11:30	ga_ls9c_ard_3-2-1_099073_2024-04-08_final
2024-04-24 10:11:08	ga_ls9c_ard_3-2-1_099073_2024-04-24_final
2024-05-10 10:11:07	ga_ls9c_ard_3-2-1_099073_2024-05-10_final

Return to ga_ls9c_ard_3 whole collection 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

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