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
2022-07-08 10:14:57	ga_ls9c_ard_3-2-1_099082_2022-07-08_final
2022-07-09 10:58:13	ga_ls9c_ard_3-2-1_106082_2022-07-09_final
2022-07-10 10:02:35	ga_ls9c_ard_3-2-1_097082_2022-07-10_final
2022-07-10 11:41:28	ga_ls9c_ard_3-2-1_113082_2022-07-10_final
2022-07-11 09:06:57	ga_ls9c_ard_3-2-1_088082_2022-07-10_final
2022-07-11 10:45:50	ga_ls9c_ard_3-2-1_104082_2022-07-11_final
2022-07-12 11:29:06	ga_ls9c_ard_3-2-1_111082_2022-07-12_final
2022-07-13 10:33:28	ga_ls9c_ard_3-2-1_102082_2022-07-13_final
2022-07-14 11:16:43	ga_ls9c_ard_3-2-1_109082_2022-07-14_final
2022-07-16 09:25:29	ga_ls9c_ard_3-2-1_091082_2022-07-15_final
2022-07-16 11:04:22	ga_ls9c_ard_3-2-1_107082_2022-07-16_final
2022-07-17 10:08:46	ga_ls9c_ard_3-2-1_098082_2022-07-17_final
2022-07-21 11:23:00	ga_ls9c_ard_3-2-1_110082_2022-07-21_final
2022-07-22 08:48:31	ga_ls9c_ard_3-2-1_085082_2022-07-21_final
2022-07-22 10:27:24	ga_ls9c_ard_3-2-1_101082_2022-07-22_final
2022-07-23 09:31:48	ga_ls9c_ard_3-2-1_092082_2022-07-23_final
2022-07-25 09:19:28	ga_ls9c_ard_3-2-1_090082_2022-07-24_final
2022-07-25 10:58:21	ga_ls9c_ard_3-2-1_106082_2022-07-25_final
2022-07-26 10:02:44	ga_ls9c_ard_3-2-1_097082_2022-07-26_final
2022-07-26 11:41:37	ga_ls9c_ard_3-2-1_113082_2022-07-26_final
2022-07-27 09:07:08	ga_ls9c_ard_3-2-1_088082_2022-07-26_final
2022-07-27 10:46:01	ga_ls9c_ard_3-2-1_104082_2022-07-27_final
2022-07-28 09:50:24	ga_ls9c_ard_3-2-1_095082_2022-07-28_final
2022-08-05 10:39:57	ga_ls9c_ard_3-2-1_103082_2022-08-05_final
2022-08-06 09:44:20	ga_ls9c_ard_3-2-1_094082_2022-08-06_final
2022-08-06 11:23:13	ga_ls9c_ard_3-2-1_110082_2022-08-06_final
2022-08-07 08:48:43	ga_ls9c_ard_3-2-1_085082_2022-08-06_final
2022-08-07 10:27:36	ga_ls9c_ard_3-2-1_101082_2022-08-07_final
2022-08-08 09:32:00	ga_ls9c_ard_3-2-1_092082_2022-08-08_final
2022-08-08 11:10:53	ga_ls9c_ard_3-2-1_108082_2022-08-08_final
2022-08-11 10:02:55	ga_ls9c_ard_3-2-1_097082_2022-08-11_final
2022-08-31 09:38:16	ga_ls9c_ard_3-2-1_093082_2022-08-31_final
2022-09-06 10:40:04	ga_ls9c_ard_3-2-1_103082_2022-09-06_final
2022-09-07 09:44:26	ga_ls9c_ard_3-2-1_094082_2022-09-07_final
2022-09-07 11:23:19	ga_ls9c_ard_3-2-1_110082_2022-09-07_final
2022-10-01 10:34:01	ga_ls9c_ard_3-2-1_102082_2022-10-01_final
2022-10-02 09:38:24	ga_ls9c_ard_3-2-1_093082_2022-10-02_final
2022-10-02 11:17:17	ga_ls9c_ard_3-2-1_109082_2022-10-02_final
2022-10-03 08:42:46	ga_ls9c_ard_3-2-1_084082_2022-10-02_final
2022-10-03 10:21:39	ga_ls9c_ard_3-2-1_100082_2022-10-03_final
2022-10-04 09:26:02	ga_ls9c_ard_3-2-1_091082_2022-10-03_final
2022-10-04 11:04:55	ga_ls9c_ard_3-2-1_107082_2022-10-04_final
2022-10-07 09:56:55	ga_ls9c_ard_3-2-1_096082_2022-10-07_final
2022-10-07 11:35:48	ga_ls9c_ard_3-2-1_112082_2022-10-07_final
2022-10-08 10:40:12	ga_ls9c_ard_3-2-1_103082_2022-10-08_final
2022-10-13 09:19:55	ga_ls9c_ard_3-2-1_090082_2022-10-12_final
2022-10-13 10:58:48	ga_ls9c_ard_3-2-1_106082_2022-10-13_final
2022-10-14 10:03:11	ga_ls9c_ard_3-2-1_097082_2022-10-14_final
2022-10-14 11:42:04	ga_ls9c_ard_3-2-1_113082_2022-10-14_final
2022-10-15 09:07:34	ga_ls9c_ard_3-2-1_088082_2022-10-14_final
2022-10-15 10:46:27	ga_ls9c_ard_3-2-1_104082_2022-10-15_final
2022-10-16 09:50:50	ga_ls9c_ard_3-2-1_095082_2022-10-16_final
2022-10-16 11:29:43	ga_ls9c_ard_3-2-1_111082_2022-10-16_final
2022-10-17 10:34:06	ga_ls9c_ard_3-2-1_102082_2022-10-17_final
2022-10-18 09:38:29	ga_ls9c_ard_3-2-1_093082_2022-10-18_final
2022-10-27 11:11:11	ga_ls9c_ard_3-2-1_108082_2022-10-27_final
2022-10-28 10:15:34	ga_ls9c_ard_3-2-1_099082_2022-10-28_final
2022-10-29 09:19:56	ga_ls9c_ard_3-2-1_090082_2022-10-28_final
2022-10-30 11:42:04	ga_ls9c_ard_3-2-1_113082_2022-10-30_final
2022-10-31 09:07:34	ga_ls9c_ard_3-2-1_088082_2022-10-30_final
2022-11-05 09:26:05	ga_ls9c_ard_3-2-1_091082_2022-11-04_final
2022-11-05 11:04:58	ga_ls9c_ard_3-2-1_107082_2022-11-05_final
2022-11-06 10:09:21	ga_ls9c_ard_3-2-1_098082_2022-11-06_final
2022-11-10 11:23:33	ga_ls9c_ard_3-2-1_110082_2022-11-10_final
2022-11-11 08:49:03	ga_ls9c_ard_3-2-1_085082_2022-11-10_final
2022-11-11 10:27:56	ga_ls9c_ard_3-2-1_101082_2022-11-11_final
2022-11-12 09:32:19	ga_ls9c_ard_3-2-1_092082_2022-11-12_final
2022-11-18 10:34:08	ga_ls9c_ard_3-2-1_102082_2022-11-18_final
2022-11-19 09:38:30	ga_ls9c_ard_3-2-1_093082_2022-11-19_final
2022-11-19 11:17:23	ga_ls9c_ard_3-2-1_109082_2022-11-19_final
2022-11-20 08:42:53	ga_ls9c_ard_3-2-1_084082_2022-11-19_final
2022-11-20 10:21:46	ga_ls9c_ard_3-2-1_100082_2022-11-20_final
2022-11-21 09:26:08	ga_ls9c_ard_3-2-1_091082_2022-11-20_final
2022-11-21 11:05:01	ga_ls9c_ard_3-2-1_107082_2022-11-21_final
2022-11-22 10:09:24	ga_ls9c_ard_3-2-1_098082_2022-11-22_final
2022-11-23 09:13:46	ga_ls9c_ard_3-2-1_089082_2022-11-22_final
2022-11-23 10:52:39	ga_ls9c_ard_3-2-1_105082_2022-11-23_final
2022-11-24 09:57:02	ga_ls9c_ard_3-2-1_096082_2022-11-24_final
2022-11-24 11:35:55	ga_ls9c_ard_3-2-1_112082_2022-11-24_final
2022-11-30 09:19:55	ga_ls9c_ard_3-2-1_090082_2022-11-29_final
2022-11-30 10:58:48	ga_ls9c_ard_3-2-1_106082_2022-11-30_final
2023-03-11 09:38:10	ga_ls9c_ard_3-2-1_093082_2023-03-11_final
2023-03-11 11:17:03	ga_ls9c_ard_3-2-1_109082_2023-03-11_final
2023-03-12 08:42:33	ga_ls9c_ard_3-2-1_084082_2023-03-11_final
2023-03-12 10:21:26	ga_ls9c_ard_3-2-1_100082_2023-03-12_final
2023-03-13 09:25:49	ga_ls9c_ard_3-2-1_091082_2023-03-12_final
2023-03-13 11:04:42	ga_ls9c_ard_3-2-1_107082_2023-03-13_final
2023-03-20 09:31:59	ga_ls9c_ard_3-2-1_092082_2023-03-20_final
2023-03-20 11:10:52	ga_ls9c_ard_3-2-1_108082_2023-03-20_final
2023-03-21 10:15:14	ga_ls9c_ard_3-2-1_099082_2023-03-21_final
2023-03-23 10:02:51	ga_ls9c_ard_3-2-1_097082_2023-03-23_final
2023-03-23 11:41:44	ga_ls9c_ard_3-2-1_113082_2023-03-23_final
2023-03-24 09:07:12	ga_ls9c_ard_3-2-1_088082_2023-03-23_final
2023-03-24 10:46:05	ga_ls9c_ard_3-2-1_104082_2023-03-24_final
2023-04-18 10:39:41	ga_ls9c_ard_3-2-1_103082_2023-04-18_final
2023-04-19 09:44:04	ga_ls9c_ard_3-2-1_094082_2023-04-19_final
2023-04-19 11:22:57	ga_ls9c_ard_3-2-1_110082_2023-04-19_final
2023-04-20 08:48:27	ga_ls9c_ard_3-2-1_085082_2023-04-19_final
2023-04-20 10:27:20	ga_ls9c_ard_3-2-1_101082_2023-04-20_final
2023-04-21 09:31:42	ga_ls9c_ard_3-2-1_092082_2023-04-21_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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