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
2021-10-31 11:14:47	ga_ls9c_ard_3-2-1_109081_2021-10-31_final
2021-11-03 09:57:45	ga_ls9c_ard_3-2-1_096082_2021-11-03_final
2021-11-05 11:17:16	ga_ls9c_ard_3-2-1_109081_2021-11-05_final
2021-11-08 10:00:13	ga_ls9c_ard_3-2-1_097082_2021-11-08_final
2021-11-10 11:19:45	ga_ls9c_ard_3-2-1_110081_2021-11-10_final
2021-11-11 10:21:26	ga_ls9c_ard_3-2-1_100082_2021-11-11_final
2021-11-12 11:01:24	ga_ls9c_ard_3-2-1_106082_2021-11-12_final
2021-11-18 11:43:49	ga_ls9c_ard_3-2-1_113082_2021-11-18_final
2021-11-19 10:45:07	ga_ls9c_ard_3-2-1_104082_2021-11-19_final
2021-11-23 10:07:36	ga_ls9c_ard_3-2-1_098082_2021-11-23_final
2021-12-04 09:26:05	ga_ls9c_ard_3-2-1_091082_2021-12-03_final
2021-12-06 10:52:35	ga_ls9c_ard_3-2-1_105082_2021-12-06_final
2021-12-15 10:46:18	ga_ls9c_ard_3-2-1_104082_2021-12-15_final
2021-12-22 10:52:29	ga_ls9c_ard_3-2-1_105082_2021-12-22_final
2022-01-10 11:22:57	ga_ls9c_ard_3-2-1_110081_2022-01-10_final
2022-01-19 11:16:46	ga_ls9c_ard_3-2-1_109081_2022-01-19_final
2022-02-07 10:09:11	ga_ls9c_ard_3-2-1_098082_2022-02-07_final
2022-03-08 11:16:33	ga_ls9c_ard_3-2-1_109081_2022-03-08_final
2022-03-31 11:22:39	ga_ls9c_ard_3-2-1_110081_2022-03-31_final
2022-05-29 09:25:11	ga_ls9c_ard_3-2-1_091082_2022-05-28_final
2022-06-08 11:41:11	ga_ls9c_ard_3-2-1_113082_2022-06-08_final
2022-06-09 10:45:33	ga_ls9c_ard_3-2-1_104082_2022-06-09_final
2022-06-12 09:37:37	ga_ls9c_ard_3-2-1_093082_2022-06-12_final
2022-06-13 10:20:53	ga_ls9c_ard_3-2-1_100082_2022-06-13_final
2022-06-14 09:25:17	ga_ls9c_ard_3-2-1_091082_2022-06-13_final
2022-06-24 11:41:30	ga_ls9c_ard_3-2-1_113082_2022-06-24_final
2022-06-25 10:45:54	ga_ls9c_ard_3-2-1_104082_2022-06-25_final
2022-06-28 09:37:55	ga_ls9c_ard_3-2-1_093082_2022-06-28_final
2022-06-30 09:25:33	ga_ls9c_ard_3-2-1_091082_2022-06-29_final
2022-07-05 11:22:33	ga_ls9c_ard_3-2-1_110081_2022-07-05_final
2022-07-07 09:31:42	ga_ls9c_ard_3-2-1_092082_2022-07-07_final
2022-07-10 11:41:28	ga_ls9c_ard_3-2-1_113082_2022-07-10_final
2022-07-16 09:25:29	ga_ls9c_ard_3-2-1_091082_2022-07-15_final
2022-08-04 09:56:40	ga_ls9c_ard_3-2-1_096082_2022-08-04_final
2022-08-04 11:35:33	ga_ls9c_ard_3-2-1_112082_2022-08-04_final
2022-08-11 10:02:55	ga_ls9c_ard_3-2-1_097082_2022-08-11_final
2022-08-12 10:46:11	ga_ls9c_ard_3-2-1_104082_2022-08-12_final
2022-08-13 09:50:35	ga_ls9c_ard_3-2-1_095082_2022-08-13_final
2022-08-15 09:38:14	ga_ls9c_ard_3-2-1_093082_2022-08-15_final
2022-08-20 09:56:48	ga_ls9c_ard_3-2-1_096082_2022-08-20_final
2022-08-20 11:35:41	ga_ls9c_ard_3-2-1_112082_2022-08-20_final
2022-08-22 11:22:55	ga_ls9c_ard_3-2-1_110081_2022-08-22_final
2022-09-09 09:32:04	ga_ls9c_ard_3-2-1_092082_2022-09-09_final
2022-09-12 11:41:54	ga_ls9c_ard_3-2-1_113082_2022-09-12_final
2022-09-14 09:50:40	ga_ls9c_ard_3-2-1_095082_2022-09-14_final
2022-09-16 09:38:20	ga_ls9c_ard_3-2-1_093082_2022-09-16_final
2022-09-16 11:16:49	ga_ls9c_ard_3-2-1_109081_2022-09-16_final
2022-09-19 10:09:15	ga_ls9c_ard_3-2-1_098082_2022-09-19_final
2022-09-23 11:23:03	ga_ls9c_ard_3-2-1_110081_2022-09-23_final
2022-09-24 10:27:49	ga_ls9c_ard_3-2-1_101082_2022-09-24_final
2022-09-25 09:32:12	ga_ls9c_ard_3-2-1_092082_2022-09-25_final
2022-10-02 09:38:24	ga_ls9c_ard_3-2-1_093082_2022-10-02_final
2022-10-14 11:42:04	ga_ls9c_ard_3-2-1_113082_2022-10-14_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
2022-10-18 11:16:58	ga_ls9c_ard_3-2-1_109081_2022-10-18_final
2022-10-29 10:58:49	ga_ls9c_ard_3-2-1_106082_2022-10-29_final
2022-10-30 11:42:04	ga_ls9c_ard_3-2-1_113082_2022-10-30_final
2022-11-05 09:26:05	ga_ls9c_ard_3-2-1_091082_2022-11-04_final
2022-11-06 10:09:21	ga_ls9c_ard_3-2-1_098082_2022-11-06_final
2022-11-07 10:52:38	ga_ls9c_ard_3-2-1_105082_2022-11-07_final
2022-11-08 09:57:01	ga_ls9c_ard_3-2-1_096082_2022-11-08_final
2022-11-19 09:38:30	ga_ls9c_ard_3-2-1_093082_2022-11-19_final
2022-11-24 09:57:02	ga_ls9c_ard_3-2-1_096082_2022-11-24_final
2022-11-26 11:23:09	ga_ls9c_ard_3-2-1_110081_2022-11-26_final
2022-12-01 11:42:03	ga_ls9c_ard_3-2-1_113082_2022-12-01_final
2022-12-06 10:21:44	ga_ls9c_ard_3-2-1_100082_2022-12-06_final
2022-12-08 10:09:23	ga_ls9c_ard_3-2-1_098082_2022-12-08_final
2022-12-09 10:52:39	ga_ls9c_ard_3-2-1_105082_2022-12-09_final
2023-01-07 10:21:45	ga_ls9c_ard_3-2-1_100082_2023-01-07_final
2023-01-11 09:57:00	ga_ls9c_ard_3-2-1_096082_2023-01-11_final
2023-02-03 11:42:07	ga_ls9c_ard_3-2-1_113082_2023-02-03_final
2023-02-23 11:16:48	ga_ls9c_ard_3-2-1_109081_2023-02-23_final
2023-03-02 11:22:57	ga_ls9c_ard_3-2-1_110081_2023-03-02_final
2023-03-11 11:16:39	ga_ls9c_ard_3-2-1_109081_2023-03-11_final
2023-03-18 11:22:50	ga_ls9c_ard_3-2-1_110081_2023-03-18_final
2023-03-27 11:16:32	ga_ls9c_ard_3-2-1_109081_2023-03-27_final
2023-05-05 11:22:21	ga_ls9c_ard_3-2-1_110081_2023-05-05_final
2023-06-06 11:22:08	ga_ls9c_ard_3-2-1_110081_2023-06-06_final
2023-06-16 10:20:37	ga_ls9c_ard_3-2-1_100082_2023-06-16_final
2023-06-20 09:55:54	ga_ls9c_ard_3-2-1_096082_2023-06-20_final
2023-06-21 10:39:10	ga_ls9c_ard_3-2-1_103082_2023-06-21_final
2023-06-22 09:43:32	ga_ls9c_ard_3-2-1_094082_2023-06-22_final
2023-06-23 10:26:48	ga_ls9c_ard_3-2-1_101082_2023-06-23_final
2023-06-24 09:31:10	ga_ls9c_ard_3-2-1_092082_2023-06-24_final
2023-06-24 11:10:03	ga_ls9c_ard_3-2-1_108082_2023-06-24_final
2023-06-29 09:49:49	ga_ls9c_ard_3-2-1_095082_2023-06-29_final
2023-07-01 11:15:59	ga_ls9c_ard_3-2-1_109081_2023-07-01_final
2023-07-17 11:16:07	ga_ls9c_ard_3-2-1_109081_2023-07-17_final
2023-07-29 11:41:18	ga_ls9c_ard_3-2-1_113082_2023-07-29_final
2023-08-02 11:16:14	ga_ls9c_ard_3-2-1_109081_2023-08-02_final
2023-09-10 11:22:45	ga_ls9c_ard_3-2-1_110081_2023-09-10_final
2023-09-15 11:41:43	ga_ls9c_ard_3-2-1_113082_2023-09-15_final
2023-09-19 11:16:36	ga_ls9c_ard_3-2-1_109081_2023-09-19_final
2023-09-26 11:22:43	ga_ls9c_ard_3-2-1_110081_2023-09-26_final
2023-10-01 11:41:41	ga_ls9c_ard_3-2-1_113082_2023-10-01_final
2023-10-05 11:16:38	ga_ls9c_ard_3-2-1_109081_2023-10-05_final
2023-10-12 11:22:54	ga_ls9c_ard_3-2-1_110081_2023-10-12_final
2023-10-17 11:41:53	ga_ls9c_ard_3-2-1_113082_2023-10-17_final
2023-10-21 11:16:46	ga_ls9c_ard_3-2-1_109081_2023-10-21_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

All years