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
2021-11-02 10:53:39	ga_ls9c_ard_3-2-1_106075_2021-11-02_final
2021-11-07 10:56:08	ga_ls9c_ard_3-2-1_106075_2021-11-07_final
2021-11-22 11:03:32	ga_ls9c_ard_3-2-1_107075_2021-11-22_final
2021-12-06 10:49:48	ga_ls9c_ard_3-2-1_105075_2021-12-06_final
2021-12-08 10:37:25	ga_ls9c_ard_3-2-1_103075_2021-12-08_final
2021-12-09 09:42:11	ga_ls9c_ard_3-2-1_094076_2021-12-09_final
2021-12-13 10:55:54	ga_ls9c_ard_3-2-1_106075_2021-12-13_final
2021-12-16 09:48:16	ga_ls9c_ard_3-2-1_095076_2021-12-16_final
2022-01-08 09:54:26	ga_ls9c_ard_3-2-1_096076_2022-01-08_final
2022-01-12 11:08:11	ga_ls9c_ard_3-2-1_108075_2022-01-12_final
2022-01-14 10:55:49	ga_ls9c_ard_3-2-1_106075_2022-01-14_final
2022-01-17 09:48:15	ga_ls9c_ard_3-2-1_095076_2022-01-17_final
2022-01-23 10:49:40	ga_ls9c_ard_3-2-1_105075_2022-01-23_final
2022-01-25 10:37:19	ga_ls9c_ard_3-2-1_103075_2022-01-25_final
2022-01-30 10:55:51	ga_ls9c_ard_3-2-1_106075_2022-01-30_final
2022-02-08 09:11:10	ga_ls9c_ard_3-2-1_089076_2022-02-07_final
2022-02-09 09:54:25	ga_ls9c_ard_3-2-1_096076_2022-02-09_final
2022-02-11 09:42:03	ga_ls9c_ard_3-2-1_094076_2022-02-11_final
2022-02-18 09:48:10	ga_ls9c_ard_3-2-1_095076_2022-02-18_final
2022-02-24 09:11:01	ga_ls9c_ard_3-2-1_089076_2022-02-23_final
2022-02-25 09:54:16	ga_ls9c_ard_3-2-1_096076_2022-02-25_final
2022-03-06 09:48:02	ga_ls9c_ard_3-2-1_095076_2022-03-06_final
2022-03-12 09:10:57	ga_ls9c_ard_3-2-1_089076_2022-03-11_final
2022-03-22 09:47:59	ga_ls9c_ard_3-2-1_095076_2022-03-22_final
2022-03-28 09:10:52	ga_ls9c_ard_3-2-1_089076_2022-03-27_final
2022-03-30 10:36:59	ga_ls9c_ard_3-2-1_103075_2022-03-30_final
2022-04-13 09:10:47	ga_ls9c_ard_3-2-1_089076_2022-04-12_final
2022-04-14 09:54:02	ga_ls9c_ard_3-2-1_096076_2022-04-14_final
2022-04-15 10:36:53	ga_ls9c_ard_3-2-1_103075_2022-04-15_final
2022-04-16 09:41:39	ga_ls9c_ard_3-2-1_094076_2022-04-16_final
2022-04-21 10:00:07	ga_ls9c_ard_3-2-1_097076_2022-04-21_final
2022-05-06 10:55:17	ga_ls9c_ard_3-2-1_106075_2022-05-06_final
2022-05-07 10:00:03	ga_ls9c_ard_3-2-1_097076_2022-05-07_final
2022-05-13 11:01:23	ga_ls9c_ard_3-2-1_107075_2022-05-13_final
2022-05-16 09:53:45	ga_ls9c_ard_3-2-1_096076_2022-05-16_final
2022-05-18 09:41:22	ga_ls9c_ard_3-2-1_094076_2022-05-18_final
2022-05-25 09:47:30	ga_ls9c_ard_3-2-1_095076_2022-05-25_final
2022-05-29 11:01:17	ga_ls9c_ard_3-2-1_107075_2022-05-29_final
2022-05-31 10:48:56	ga_ls9c_ard_3-2-1_105075_2022-05-31_final
2022-06-01 09:53:42	ga_ls9c_ard_3-2-1_096076_2022-06-01_final
2022-06-02 10:36:34	ga_ls9c_ard_3-2-1_103075_2022-06-02_final
2022-06-05 11:07:29	ga_ls9c_ard_3-2-1_108075_2022-06-05_final
2022-06-07 10:55:07	ga_ls9c_ard_3-2-1_106075_2022-06-07_final
2022-06-08 09:59:54	ga_ls9c_ard_3-2-1_097076_2022-06-08_final
2022-06-17 09:53:49	ga_ls9c_ard_3-2-1_096076_2022-06-17_final
2022-06-18 10:36:42	ga_ls9c_ard_3-2-1_103075_2022-06-18_final
2022-06-23 10:55:25	ga_ls9c_ard_3-2-1_106075_2022-06-23_final
2022-06-26 09:47:53	ga_ls9c_ard_3-2-1_095076_2022-06-26_final
2022-06-27 10:30:45	ga_ls9c_ard_3-2-1_102075_2022-06-27_final
2022-06-30 11:01:38	ga_ls9c_ard_3-2-1_107075_2022-06-30_final
2022-07-03 09:54:03	ga_ls9c_ard_3-2-1_096076_2022-07-03_final
2022-07-05 09:41:41	ga_ls9c_ard_3-2-1_094076_2022-07-05_final
2022-07-09 10:55:25	ga_ls9c_ard_3-2-1_106075_2022-07-09_final
2022-07-12 09:47:49	ga_ls9c_ard_3-2-1_095076_2022-07-12_final
2022-07-13 10:30:40	ga_ls9c_ard_3-2-1_102075_2022-07-13_final
2022-07-19 09:54:03	ga_ls9c_ard_3-2-1_096076_2022-07-19_final
2022-07-23 11:07:53	ga_ls9c_ard_3-2-1_108075_2022-07-23_final
2022-07-25 10:55:33	ga_ls9c_ard_3-2-1_106075_2022-07-25_final
2022-07-28 09:48:01	ga_ls9c_ard_3-2-1_095076_2022-07-28_final
2022-08-01 11:01:50	ga_ls9c_ard_3-2-1_107075_2022-08-01_final
2022-08-03 10:49:29	ga_ls9c_ard_3-2-1_105075_2022-08-03_final
2022-08-04 09:54:17	ga_ls9c_ard_3-2-1_096076_2022-08-04_final
2022-08-06 09:41:56	ga_ls9c_ard_3-2-1_094076_2022-08-06_final
2022-08-10 10:55:44	ga_ls9c_ard_3-2-1_106075_2022-08-10_final
2022-08-13 09:48:11	ga_ls9c_ard_3-2-1_095076_2022-08-13_final
2022-08-15 09:35:50	ga_ls9c_ard_3-2-1_093076_2022-08-15_final
2022-08-17 11:01:58	ga_ls9c_ard_3-2-1_107075_2022-08-17_final
2022-08-20 09:54:24	ga_ls9c_ard_3-2-1_096076_2022-08-20_final
2022-08-22 09:42:03	ga_ls9c_ard_3-2-1_094076_2022-08-22_final
2022-08-24 11:08:10	ga_ls9c_ard_3-2-1_108075_2022-08-24_final
2022-08-28 10:43:27	ga_ls9c_ard_3-2-1_104075_2022-08-28_final
2022-08-29 09:48:14	ga_ls9c_ard_3-2-1_095076_2022-08-29_final
2022-08-30 10:31:06	ga_ls9c_ard_3-2-1_102075_2022-08-30_final
2022-08-31 09:35:53	ga_ls9c_ard_3-2-1_093076_2022-08-31_final
2022-09-05 09:54:24	ga_ls9c_ard_3-2-1_096076_2022-09-05_final
2022-09-06 10:37:16	ga_ls9c_ard_3-2-1_103075_2022-09-06_final
2022-09-07 09:42:02	ga_ls9c_ard_3-2-1_094076_2022-09-07_final
2022-09-11 10:55:50	ga_ls9c_ard_3-2-1_106075_2022-09-11_final
2022-09-12 10:00:37	ga_ls9c_ard_3-2-1_097076_2022-09-12_final
2022-09-22 10:37:23	ga_ls9c_ard_3-2-1_103075_2022-09-22_final
2022-09-27 10:55:56	ga_ls9c_ard_3-2-1_106075_2022-09-27_final
2022-09-29 10:43:35	ga_ls9c_ard_3-2-1_104075_2022-09-29_final
2022-09-30 09:48:22	ga_ls9c_ard_3-2-1_095076_2022-09-30_final
2022-10-06 09:11:16	ga_ls9c_ard_3-2-1_089076_2022-10-05_final
2022-10-09 09:42:12	ga_ls9c_ard_3-2-1_094076_2022-10-09_final
2022-10-18 09:36:05	ga_ls9c_ard_3-2-1_093076_2022-10-18_final
2022-10-22 09:11:22	ga_ls9c_ard_3-2-1_089076_2022-10-21_final
2022-11-07 09:11:21	ga_ls9c_ard_3-2-1_089076_2022-11-06_final
2022-11-23 09:11:23	ga_ls9c_ard_3-2-1_089076_2022-11-22_final
2022-12-09 09:11:22	ga_ls9c_ard_3-2-1_089076_2022-12-08_final
2022-12-25 09:11:19	ga_ls9c_ard_3-2-1_089076_2022-12-24_final
2023-01-10 09:11:21	ga_ls9c_ard_3-2-1_089076_2023-01-09_final
2023-01-26 09:11:18	ga_ls9c_ard_3-2-1_089076_2023-01-25_final
2023-02-11 09:11:25	ga_ls9c_ard_3-2-1_089076_2023-02-10_final
2023-02-27 09:11:11	ga_ls9c_ard_3-2-1_089076_2023-02-26_final
2023-03-15 09:11:04	ga_ls9c_ard_3-2-1_089076_2023-03-14_final
2023-03-31 09:10:52	ga_ls9c_ard_3-2-1_089076_2023-03-30_final
2023-04-16 09:10:46	ga_ls9c_ard_3-2-1_089076_2023-04-15_final
2023-05-02 09:10:37	ga_ls9c_ard_3-2-1_089076_2023-05-01_final
2023-05-18 09:10:30	ga_ls9c_ard_3-2-1_089076_2023-05-17_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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