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:

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First 100 results (query limit)

Time (local)	Label
2021-12-13 10:56:41	ga_ls9c_ard_3-2-1_106077_2021-12-13_final
2021-12-18 11:15:12	ga_ls9c_ard_3-2-1_109077_2021-12-18_final
2021-12-25 11:21:24	ga_ls9c_ard_3-2-1_110077_2021-12-25_final
2021-12-27 11:09:02	ga_ls9c_ard_3-2-1_108077_2021-12-27_final
2022-01-04 10:19:34	ga_ls9c_ard_3-2-1_100077_2022-01-04_final
2022-01-12 11:08:59	ga_ls9c_ard_3-2-1_108077_2022-01-12_final
2022-01-14 10:56:37	ga_ls9c_ard_3-2-1_106077_2022-01-14_final
2022-01-19 11:15:11	ga_ls9c_ard_3-2-1_109077_2022-01-19_final
2022-01-20 10:19:34	ga_ls9c_ard_3-2-1_100077_2022-01-20_final
2022-01-27 10:25:45	ga_ls9c_ard_3-2-1_101077_2022-01-27_final
2022-01-30 10:56:39	ga_ls9c_ard_3-2-1_106077_2022-01-30_final
2022-02-11 11:21:20	ga_ls9c_ard_3-2-1_110077_2022-02-11_final
2022-02-12 10:25:42	ga_ls9c_ard_3-2-1_101077_2022-02-12_final
2022-02-13 11:08:57	ga_ls9c_ard_3-2-1_108077_2022-02-13_final
2022-02-15 10:56:35	ga_ls9c_ard_3-2-1_106077_2022-02-15_final
2022-02-19 10:31:49	ga_ls9c_ard_3-2-1_102077_2022-02-19_final
2022-02-20 11:15:04	ga_ls9c_ard_3-2-1_109077_2022-02-20_final
2022-02-21 10:19:26	ga_ls9c_ard_3-2-1_100077_2022-02-21_final
2022-02-28 10:25:31	ga_ls9c_ard_3-2-1_101077_2022-02-28_final
2022-03-07 10:31:41	ga_ls9c_ard_3-2-1_102077_2022-03-07_final
2022-03-08 11:14:57	ga_ls9c_ard_3-2-1_109077_2022-03-08_final
2022-03-24 11:14:53	ga_ls9c_ard_3-2-1_109077_2022-03-24_final
2022-04-02 11:08:41	ga_ls9c_ard_3-2-1_108077_2022-04-02_final
2022-04-03 10:13:04	ga_ls9c_ard_3-2-1_099077_2022-04-03_final
2022-04-09 11:14:50	ga_ls9c_ard_3-2-1_109077_2022-04-09_final
2022-04-13 10:50:04	ga_ls9c_ard_3-2-1_105077_2022-04-13_final
2022-04-16 11:20:56	ga_ls9c_ard_3-2-1_110077_2022-04-16_final
2022-04-18 11:08:33	ga_ls9c_ard_3-2-1_108077_2022-04-18_final
2022-04-19 10:12:55	ga_ls9c_ard_3-2-1_099077_2022-04-19_final
2022-04-25 11:14:41	ga_ls9c_ard_3-2-1_109077_2022-04-25_final
2022-04-29 10:49:57	ga_ls9c_ard_3-2-1_105077_2022-04-29_final
2022-05-03 10:25:12	ga_ls9c_ard_3-2-1_101077_2022-05-03_final
2022-05-04 11:08:28	ga_ls9c_ard_3-2-1_108077_2022-05-04_final
2022-05-06 10:56:05	ga_ls9c_ard_3-2-1_106077_2022-05-06_final
2022-05-11 11:14:34	ga_ls9c_ard_3-2-1_109077_2022-05-11_final
2022-05-13 11:02:11	ga_ls9c_ard_3-2-1_107077_2022-05-13_final
2022-05-18 11:20:39	ga_ls9c_ard_3-2-1_110077_2022-05-18_final
2022-05-19 10:25:00	ga_ls9c_ard_3-2-1_101077_2022-05-19_final
2022-05-21 10:12:38	ga_ls9c_ard_3-2-1_099077_2022-05-21_final
2022-05-22 10:55:53	ga_ls9c_ard_3-2-1_106077_2022-05-22_final
2022-05-26 10:31:10	ga_ls9c_ard_3-2-1_102077_2022-05-26_final
2022-05-29 11:02:05	ga_ls9c_ard_3-2-1_107077_2022-05-29_final
2022-06-06 10:12:39	ga_ls9c_ard_3-2-1_099077_2022-06-06_final
2022-06-07 10:55:55	ga_ls9c_ard_3-2-1_106077_2022-06-07_final
2022-06-16 10:49:50	ga_ls9c_ard_3-2-1_105077_2022-06-16_final
2022-06-22 10:12:55	ga_ls9c_ard_3-2-1_099077_2022-06-22_final
2022-06-28 11:14:48	ga_ls9c_ard_3-2-1_109077_2022-06-28_final
2022-06-30 11:02:26	ga_ls9c_ard_3-2-1_107077_2022-06-30_final
2022-07-01 10:06:49	ga_ls9c_ard_3-2-1_098077_2022-07-01_final
2022-07-02 10:50:04	ga_ls9c_ard_3-2-1_105077_2022-07-02_final
2022-07-13 10:31:28	ga_ls9c_ard_3-2-1_102077_2022-07-13_final
2022-07-14 11:14:43	ga_ls9c_ard_3-2-1_109077_2022-07-14_final
2022-07-15 10:19:06	ga_ls9c_ard_3-2-1_100077_2022-07-15_final
2022-07-18 10:50:03	ga_ls9c_ard_3-2-1_105077_2022-07-18_final
2022-07-24 10:13:04	ga_ls9c_ard_3-2-1_099077_2022-07-24_final
2022-07-25 10:56:21	ga_ls9c_ard_3-2-1_106077_2022-07-25_final
2022-08-15 11:15:07	ga_ls9c_ard_3-2-1_109077_2022-08-15_final
2022-08-17 11:02:46	ga_ls9c_ard_3-2-1_107077_2022-08-17_final
2022-08-24 11:08:58	ga_ls9c_ard_3-2-1_108077_2022-08-24_final
2022-09-01 10:19:32	ga_ls9c_ard_3-2-1_100077_2022-09-01_final
2022-09-10 10:13:21	ga_ls9c_ard_3-2-1_099077_2022-09-10_final
2022-09-15 10:31:57	ga_ls9c_ard_3-2-1_102077_2022-09-15_final
2022-09-16 11:15:13	ga_ls9c_ard_3-2-1_109077_2022-09-16_final
2022-09-24 10:25:50	ga_ls9c_ard_3-2-1_101077_2022-09-24_final
2022-10-10 10:25:52	ga_ls9c_ard_3-2-1_101077_2022-10-10_final
2022-10-26 10:25:56	ga_ls9c_ard_3-2-1_101077_2022-10-26_final
2022-11-13 10:13:35	ga_ls9c_ard_3-2-1_099077_2022-11-13_final
2022-11-27 10:25:55	ga_ls9c_ard_3-2-1_101077_2022-11-27_final
2022-11-29 10:13:33	ga_ls9c_ard_3-2-1_099077_2022-11-29_final
2022-12-15 10:13:34	ga_ls9c_ard_3-2-1_099077_2022-12-15_final
2022-12-21 11:15:20	ga_ls9c_ard_3-2-1_109077_2022-12-21_final
2022-12-28 11:21:32	ga_ls9c_ard_3-2-1_110077_2022-12-28_final
2022-12-30 11:09:11	ga_ls9c_ard_3-2-1_108077_2022-12-30_final
2022-12-31 10:13:34	ga_ls9c_ard_3-2-1_099077_2022-12-31_final
2023-01-05 10:32:07	ga_ls9c_ard_3-2-1_102077_2023-01-05_final
2023-01-16 10:13:29	ga_ls9c_ard_3-2-1_099077_2023-01-16_final
2023-01-22 11:15:14	ga_ls9c_ard_3-2-1_109077_2023-01-22_final
2023-01-29 11:21:32	ga_ls9c_ard_3-2-1_110077_2023-01-29_final
2023-01-31 11:09:12	ga_ls9c_ard_3-2-1_108077_2023-01-31_final
2023-02-01 10:13:35	ga_ls9c_ard_3-2-1_099077_2023-02-01_final
2023-02-10 10:07:27	ga_ls9c_ard_3-2-1_098077_2023-02-10_final
2023-02-14 11:21:35	ga_ls9c_ard_3-2-1_110077_2023-02-14_final
2023-02-16 11:09:11	ga_ls9c_ard_3-2-1_108077_2023-02-16_final
2023-02-17 10:13:33	ga_ls9c_ard_3-2-1_099077_2023-02-17_final
2023-02-23 11:15:12	ga_ls9c_ard_3-2-1_109077_2023-02-23_final
2023-03-02 11:21:21	ga_ls9c_ard_3-2-1_110077_2023-03-02_final
2023-03-11 11:15:04	ga_ls9c_ard_3-2-1_109077_2023-03-11_final
2023-03-18 11:21:14	ga_ls9c_ard_3-2-1_110077_2023-03-18_final
2023-03-27 11:14:56	ga_ls9c_ard_3-2-1_109077_2023-03-27_final
2023-04-03 11:21:04	ga_ls9c_ard_3-2-1_110077_2023-04-03_final
2023-04-05 11:08:42	ga_ls9c_ard_3-2-1_108077_2023-04-05_final
2023-04-12 11:14:48	ga_ls9c_ard_3-2-1_109077_2023-04-12_final
2023-04-19 11:20:57	ga_ls9c_ard_3-2-1_110077_2023-04-19_final
2023-04-21 11:08:35	ga_ls9c_ard_3-2-1_108077_2023-04-21_final
2023-04-28 11:14:42	ga_ls9c_ard_3-2-1_109077_2023-04-28_final
2023-05-05 11:20:45	ga_ls9c_ard_3-2-1_110077_2023-05-05_final
2023-05-07 11:08:24	ga_ls9c_ard_3-2-1_108077_2023-05-07_final
2023-05-14 11:14:33	ga_ls9c_ard_3-2-1_109077_2023-05-14_final
2023-05-21 11:20:38	ga_ls9c_ard_3-2-1_110077_2023-05-21_final
2023-05-23 11:08:14	ga_ls9c_ard_3-2-1_108077_2023-05-23_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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