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
2023-08-25 11:19:47	ga_ls9c_ard_3-2-1_110074_2023-08-25_final
2023-08-27 09:28:58	ga_ls9c_ard_3-2-1_092075_2023-08-26_final
2023-08-28 11:51:07	ga_ls9c_ard_3-2-1_115075_2023-08-28_final
2023-08-29 09:21:01	ga_ls9c_ard_3-2-1_090086_2023-08-28_final
2023-09-08 09:52:12	ga_ls9c_ard_3-2-1_096071_2023-09-08_final
2023-09-21 09:22:33	ga_ls9c_ard_3-2-1_091074_2023-09-20_final
2023-09-22 10:04:36	ga_ls9c_ard_3-2-1_098071_2023-09-22_final
2023-09-22 10:07:00	ga_ls9c_ard_3-2-1_098077_2023-09-22_final
2023-09-29 10:15:32	ga_ls9c_ard_3-2-1_099083_2023-09-29_final
2023-09-29 11:51:37	ga_ls9c_ard_3-2-1_115076_2023-09-29_final
2023-10-04 10:28:10	ga_ls9c_ard_3-2-1_102068_2023-10-04_final
2023-10-05 11:13:50	ga_ls9c_ard_3-2-1_109074_2023-10-05_final
2023-10-06 10:21:49	ga_ls9c_ard_3-2-1_100083_2023-10-06_final
2023-10-07 11:01:29	ga_ls9c_ard_3-2-1_107074_2023-10-07_final
2023-10-07 11:05:05	ga_ls9c_ard_3-2-1_107083_2023-10-07_final
2023-10-08 10:03:29	ga_ls9c_ard_3-2-1_098068_2023-10-08_final
2023-10-09 09:13:03	ga_ls9c_ard_3-2-1_089081_2023-10-08_final
2023-10-09 10:48:45	ga_ls9c_ard_3-2-1_105073_2023-10-09_final
2023-10-14 11:06:34	ga_ls9c_ard_3-2-1_108071_2023-10-14_final
2023-10-16 10:54:13	ga_ls9c_ard_3-2-1_106071_2023-10-16_final
2023-10-16 10:56:13	ga_ls9c_ard_3-2-1_106076_2023-10-16_final
2023-10-24 11:47:16	ga_ls9c_ard_3-2-1_114080_2023-10-24_final
2023-10-25 10:46:50	ga_ls9c_ard_3-2-1_105068_2023-10-25_final
2023-10-30 09:29:38	ga_ls9c_ard_3-2-1_092076_2023-10-29_final
2023-10-30 09:32:26	ga_ls9c_ard_3-2-1_092083_2023-10-30_final
2023-10-30 11:08:07	ga_ls9c_ard_3-2-1_108075_2023-10-30_final
2023-10-31 10:11:41	ga_ls9c_ard_3-2-1_099073_2023-10-31_final
2023-11-01 09:18:03	ga_ls9c_ard_3-2-1_090078_2023-10-31_final
2023-11-01 09:22:26	ga_ls9c_ard_3-2-1_090089_2023-10-31_final
2023-11-01 10:55:20	ga_ls9c_ard_3-2-1_106074_2023-11-01_final
2023-11-04 09:52:07	ga_ls9c_ard_3-2-1_095086_2023-11-04_final
2023-11-08 10:59:56	ga_ls9c_ard_3-2-1_107070_2023-11-08_final
2023-11-09 10:04:19	ga_ls9c_ard_3-2-1_098070_2023-11-09_final
2023-11-09 10:07:07	ga_ls9c_ard_3-2-1_098077_2023-11-09_final
2023-11-09 11:45:36	ga_ls9c_ard_3-2-1_114076_2023-11-09_final
2023-11-10 10:47:35	ga_ls9c_ard_3-2-1_105070_2023-11-10_final
2023-11-10 10:49:59	ga_ls9c_ard_3-2-1_105076_2023-11-10_final
2023-11-15 11:07:43	ga_ls9c_ard_3-2-1_108074_2023-11-15_final
2023-11-17 09:22:05	ga_ls9c_ard_3-2-1_090088_2023-11-16_final
2023-11-18 09:58:10	ga_ls9c_ard_3-2-1_097070_2023-11-18_final
2023-11-18 10:04:10	ga_ls9c_ard_3-2-1_097085_2023-11-18_final
2023-11-24 11:01:39	ga_ls9c_ard_3-2-1_107074_2023-11-24_final
2023-11-25 11:45:44	ga_ls9c_ard_3-2-1_114076_2023-11-25_final
2023-11-26 09:15:13	ga_ls9c_ard_3-2-1_089086_2023-11-25_final
2023-11-28 10:34:34	ga_ls9c_ard_3-2-1_103068_2023-11-28_final
2023-11-30 10:27:47	ga_ls9c_ard_3-2-1_101082_2023-11-30_final
2023-12-02 10:14:37	ga_ls9c_ard_3-2-1_099080_2023-12-02_final
2023-12-09 10:19:08	ga_ls9c_ard_3-2-1_100076_2023-12-09_final
2023-12-12 10:50:05	ga_ls9c_ard_3-2-1_105076_2023-12-12_final
2023-12-13 09:58:28	ga_ls9c_ard_3-2-1_096086_2023-12-13_final
2023-12-14 10:34:57	ga_ls9c_ard_3-2-1_103069_2023-12-14_final
2023-12-22 11:25:14	ga_ls9c_ard_3-2-1_111071_2023-12-22_final
2023-12-26 11:00:07	ga_ls9c_ard_3-2-1_107070_2023-12-26_final
2023-12-28 09:12:27	ga_ls9c_ard_3-2-1_089079_2023-12-27_final
2023-12-28 10:50:32	ga_ls9c_ard_3-2-1_105077_2023-12-28_final
2023-12-29 09:53:42	ga_ls9c_ard_3-2-1_096074_2023-12-29_final
2023-12-30 10:34:34	ga_ls9c_ard_3-2-1_103068_2023-12-30_final
2023-12-31 09:40:31	ga_ls9c_ard_3-2-1_094072_2023-12-31_final
2023-12-31 09:42:07	ga_ls9c_ard_3-2-1_094076_2023-12-31_final
2023-12-31 11:20:36	ga_ls9c_ard_3-2-1_110075_2023-12-31_final
2024-01-02 09:34:08	ga_ls9c_ard_3-2-1_092087_2024-01-02_final
2024-01-07 09:47:26	ga_ls9c_ard_3-2-1_095074_2024-01-07_final
2024-01-07 11:23:55	ga_ls9c_ard_3-2-1_111068_2024-01-07_final
2024-01-09 11:14:47	ga_ls9c_ard_3-2-1_109076_2024-01-09_final
2024-01-11 09:26:44	ga_ls9c_ard_3-2-1_091084_2024-01-10_final
2024-01-12 10:10:24	ga_ls9c_ard_3-2-1_098085_2024-01-12_final
2024-01-21 11:41:29	ga_ls9c_ard_3-2-1_113081_2024-01-21_final
2024-01-23 09:52:13	ga_ls9c_ard_3-2-1_095086_2024-01-23_final
2024-01-25 09:38:39	ga_ls9c_ard_3-2-1_093083_2024-01-25_final
2024-01-27 11:05:36	ga_ls9c_ard_3-2-1_107084_2024-01-27_final
2024-01-28 10:03:12	ga_ls9c_ard_3-2-1_098067_2024-01-28_final
2024-01-29 09:13:35	ga_ls9c_ard_3-2-1_089082_2024-01-28_final
2024-01-29 10:49:40	ga_ls9c_ard_3-2-1_105075_2024-01-29_final
2024-02-01 11:19:00	ga_ls9c_ard_3-2-1_110071_2024-02-01_final
2024-02-04 10:16:13	ga_ls9c_ard_3-2-1_099084_2024-02-04_final
2024-02-05 09:18:36	ga_ls9c_ard_3-2-1_090079_2024-02-04_final
2024-02-05 10:56:18	ga_ls9c_ard_3-2-1_106076_2024-02-05_final
2024-02-10 11:14:02	ga_ls9c_ard_3-2-1_109074_2024-02-10_final
2024-02-11 10:21:59	ga_ls9c_ard_3-2-1_100083_2024-02-11_final
2024-02-12 11:04:27	ga_ls9c_ard_3-2-1_107081_2024-02-12_final
2024-02-15 09:58:25	ga_ls9c_ard_3-2-1_096086_2024-02-15_final
2024-02-24 09:46:53	ga_ls9c_ard_3-2-1_095073_2024-02-24_final
2024-02-26 09:33:45	ga_ls9c_ard_3-2-1_093071_2024-02-26_final
2024-02-27 10:21:49	ga_ls9c_ard_3-2-1_100083_2024-02-27_final
2024-02-29 10:09:29	ga_ls9c_ard_3-2-1_098083_2024-02-29_final
2024-03-01 09:13:04	ga_ls9c_ard_3-2-1_089081_2024-02-29_final
2024-03-02 11:36:01	ga_ls9c_ard_3-2-1_112083_2024-03-02_final
2024-03-05 10:24:28	ga_ls9c_ard_3-2-1_101074_2024-03-05_final
2024-03-07 11:52:59	ga_ls9c_ard_3-2-1_115079_2024-03-07_final
2024-03-14 11:58:44	ga_ls9c_ard_3-2-1_116078_2024-03-14_final
2024-03-16 11:44:47	ga_ls9c_ard_3-2-1_114074_2024-03-16_final
2024-03-19 10:34:48	ga_ls9c_ard_3-2-1_103069_2024-03-19_final
2024-03-20 09:46:21	ga_ls9c_ard_3-2-1_094087_2024-03-20_final
2024-03-22 09:33:59	ga_ls9c_ard_3-2-1_092087_2024-03-22_final
2024-03-24 09:20:24	ga_ls9c_ard_3-2-1_090084_2024-03-23_final
2024-03-24 09:21:12	ga_ls9c_ard_3-2-1_090086_2024-03-23_final
2024-03-26 10:41:42	ga_ls9c_ard_3-2-1_104071_2024-03-26_final
2024-03-30 10:17:43	ga_ls9c_ard_3-2-1_100073_2024-03-30_final
2024-04-08 10:14:18	ga_ls9c_ard_3-2-1_099080_2024-04-08_final
2024-04-09 09:20:16	ga_ls9c_ard_3-2-1_090084_2024-04-08_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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