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
2021-11-20 09:42:49	ga_ls9c_ard_3-2-1_094073_2021-11-20_final
2021-11-25 09:45:16	ga_ls9c_ard_3-2-1_095073_2021-11-25_final
2021-12-16 09:47:05	ga_ls9c_ard_3-2-1_095073_2021-12-16_final
2021-12-25 09:40:55	ga_ls9c_ard_3-2-1_094073_2021-12-25_final
2022-01-01 09:47:05	ga_ls9c_ard_3-2-1_095073_2022-01-01_final
2022-01-10 09:41:16	ga_ls9c_ard_3-2-1_094074_2022-01-10_final
2022-01-17 09:47:03	ga_ls9c_ard_3-2-1_095073_2022-01-17_final
2022-01-26 09:40:54	ga_ls9c_ard_3-2-1_094073_2022-01-26_final
2022-01-26 09:41:18	ga_ls9c_ard_3-2-1_094074_2022-01-26_final
2022-02-11 09:41:15	ga_ls9c_ard_3-2-1_094074_2022-02-11_final
2022-03-06 09:47:14	ga_ls9c_ard_3-2-1_095074_2022-03-06_final
2022-03-31 09:40:34	ga_ls9c_ard_3-2-1_094073_2022-03-31_final
2022-03-31 09:40:58	ga_ls9c_ard_3-2-1_094074_2022-03-31_final
2022-04-23 09:46:57	ga_ls9c_ard_3-2-1_095074_2022-04-23_final
2022-05-25 09:46:42	ga_ls9c_ard_3-2-1_095074_2022-05-25_final
2022-06-10 09:46:21	ga_ls9c_ard_3-2-1_095073_2022-06-10_final
2022-06-19 09:40:19	ga_ls9c_ard_3-2-1_094073_2022-06-19_final
2022-06-19 09:40:43	ga_ls9c_ard_3-2-1_094074_2022-06-19_final
2022-06-26 09:46:41	ga_ls9c_ard_3-2-1_095073_2022-06-26_final
2022-06-26 09:47:05	ga_ls9c_ard_3-2-1_095074_2022-06-26_final
2022-07-12 09:46:37	ga_ls9c_ard_3-2-1_095073_2022-07-12_final
2022-07-12 09:47:01	ga_ls9c_ard_3-2-1_095074_2022-07-12_final
2022-07-21 09:40:56	ga_ls9c_ard_3-2-1_094074_2022-07-21_final
2022-07-28 09:46:49	ga_ls9c_ard_3-2-1_095073_2022-07-28_final
2022-07-28 09:47:13	ga_ls9c_ard_3-2-1_095074_2022-07-28_final
2022-08-06 09:41:08	ga_ls9c_ard_3-2-1_094074_2022-08-06_final
2022-08-13 09:46:59	ga_ls9c_ard_3-2-1_095073_2022-08-13_final
2022-08-22 09:40:51	ga_ls9c_ard_3-2-1_094073_2022-08-22_final
2022-08-22 09:41:15	ga_ls9c_ard_3-2-1_094074_2022-08-22_final
2022-08-29 09:47:02	ga_ls9c_ard_3-2-1_095073_2022-08-29_final
2022-08-29 09:47:26	ga_ls9c_ard_3-2-1_095074_2022-08-29_final
2022-09-07 09:40:51	ga_ls9c_ard_3-2-1_094073_2022-09-07_final
2022-09-07 09:41:15	ga_ls9c_ard_3-2-1_094074_2022-09-07_final
2022-09-14 09:47:29	ga_ls9c_ard_3-2-1_095074_2022-09-14_final
2022-09-23 09:40:58	ga_ls9c_ard_3-2-1_094073_2022-09-23_final
2022-09-30 09:47:10	ga_ls9c_ard_3-2-1_095073_2022-09-30_final
2022-10-09 09:41:00	ga_ls9c_ard_3-2-1_094073_2022-10-09_final
2022-10-09 09:41:24	ga_ls9c_ard_3-2-1_094074_2022-10-09_final
2022-10-16 09:47:15	ga_ls9c_ard_3-2-1_095073_2022-10-16_final
2022-10-25 09:41:05	ga_ls9c_ard_3-2-1_094073_2022-10-25_final
2022-10-25 09:41:29	ga_ls9c_ard_3-2-1_094074_2022-10-25_final
2022-11-17 09:47:17	ga_ls9c_ard_3-2-1_095073_2022-11-17_final
2022-12-12 09:41:04	ga_ls9c_ard_3-2-1_094073_2022-12-12_final
2023-01-04 09:47:15	ga_ls9c_ard_3-2-1_095073_2023-01-04_final
2023-01-20 09:47:29	ga_ls9c_ard_3-2-1_095074_2023-01-20_final
2023-01-29 09:41:03	ga_ls9c_ard_3-2-1_094073_2023-01-29_final
2023-02-05 09:47:18	ga_ls9c_ard_3-2-1_095073_2023-02-05_final
2023-02-14 09:41:30	ga_ls9c_ard_3-2-1_094074_2023-02-14_final
2023-03-02 09:41:16	ga_ls9c_ard_3-2-1_094074_2023-03-02_final
2023-03-09 09:47:21	ga_ls9c_ard_3-2-1_095074_2023-03-09_final
2023-03-25 09:46:51	ga_ls9c_ard_3-2-1_095073_2023-03-25_final
2023-04-03 09:40:59	ga_ls9c_ard_3-2-1_094074_2023-04-03_final
2023-04-10 09:46:43	ga_ls9c_ard_3-2-1_095073_2023-04-10_final
2023-04-19 09:40:29	ga_ls9c_ard_3-2-1_094073_2023-04-19_final
2023-04-26 09:46:36	ga_ls9c_ard_3-2-1_095073_2023-04-26_final
2023-05-21 09:40:09	ga_ls9c_ard_3-2-1_094073_2023-05-21_final
2023-05-28 09:46:17	ga_ls9c_ard_3-2-1_095073_2023-05-28_final
2023-06-06 09:40:04	ga_ls9c_ard_3-2-1_094073_2023-06-06_final
2023-06-13 09:46:09	ga_ls9c_ard_3-2-1_095073_2023-06-13_final
2023-06-22 09:39:57	ga_ls9c_ard_3-2-1_094073_2023-06-22_final
2023-06-29 09:46:13	ga_ls9c_ard_3-2-1_095073_2023-06-29_final
2023-07-08 09:40:11	ga_ls9c_ard_3-2-1_094073_2023-07-08_final
2023-07-15 09:46:24	ga_ls9c_ard_3-2-1_095073_2023-07-15_final
2023-07-24 09:40:12	ga_ls9c_ard_3-2-1_094073_2023-07-24_final
2023-07-31 09:46:29	ga_ls9c_ard_3-2-1_095073_2023-07-31_final
2023-08-09 09:40:23	ga_ls9c_ard_3-2-1_094073_2023-08-09_final
2023-08-16 09:46:34	ga_ls9c_ard_3-2-1_095073_2023-08-16_final
2023-08-25 09:40:30	ga_ls9c_ard_3-2-1_094073_2023-08-25_final
2023-09-01 09:46:45	ga_ls9c_ard_3-2-1_095073_2023-09-01_final
2023-09-10 09:40:40	ga_ls9c_ard_3-2-1_094073_2023-09-10_final
2023-09-17 09:46:53	ga_ls9c_ard_3-2-1_095073_2023-09-17_final
2023-09-26 09:40:38	ga_ls9c_ard_3-2-1_094073_2023-09-26_final
2023-10-03 09:46:53	ga_ls9c_ard_3-2-1_095073_2023-10-03_final
2023-10-12 09:40:49	ga_ls9c_ard_3-2-1_094073_2023-10-12_final
2023-10-19 09:47:03	ga_ls9c_ard_3-2-1_095073_2023-10-19_final
2023-10-28 09:40:50	ga_ls9c_ard_3-2-1_094073_2023-10-28_final
2023-11-04 09:46:56	ga_ls9c_ard_3-2-1_095073_2023-11-04_final
2023-11-20 09:47:03	ga_ls9c_ard_3-2-1_095073_2023-11-20_final
2023-11-29 09:40:56	ga_ls9c_ard_3-2-1_094073_2023-11-29_final
2023-12-06 09:47:03	ga_ls9c_ard_3-2-1_095073_2023-12-06_final
2023-12-15 09:40:56	ga_ls9c_ard_3-2-1_094073_2023-12-15_final
2023-12-22 09:47:09	ga_ls9c_ard_3-2-1_095073_2023-12-22_final
2023-12-31 09:40:55	ga_ls9c_ard_3-2-1_094073_2023-12-31_final
2024-01-07 09:47:02	ga_ls9c_ard_3-2-1_095073_2024-01-07_final
2024-01-16 09:40:54	ga_ls9c_ard_3-2-1_094073_2024-01-16_final
2024-01-23 09:47:01	ga_ls9c_ard_3-2-1_095073_2024-01-23_final
2024-02-01 09:40:55	ga_ls9c_ard_3-2-1_094073_2024-02-01_final
2024-02-08 09:47:07	ga_ls9c_ard_3-2-1_095073_2024-02-08_final
2024-02-17 09:40:50	ga_ls9c_ard_3-2-1_094073_2024-02-17_final
2024-02-24 09:46:53	ga_ls9c_ard_3-2-1_095073_2024-02-24_final
2024-03-04 09:40:48	ga_ls9c_ard_3-2-1_094073_2024-03-04_final
2024-03-11 09:46:59	ga_ls9c_ard_3-2-1_095073_2024-03-11_final
2024-03-20 09:40:46	ga_ls9c_ard_3-2-1_094073_2024-03-20_final
2024-03-27 09:46:51	ga_ls9c_ard_3-2-1_095073_2024-03-27_final
2024-04-05 09:40:37	ga_ls9c_ard_3-2-1_094073_2024-04-05_final
2024-04-12 09:46:44	ga_ls9c_ard_3-2-1_095073_2024-04-12_final
2024-04-28 09:46:26	ga_ls9c_ard_3-2-1_095073_2024-04-28_final
2024-05-07 09:40:14	ga_ls9c_ard_3-2-1_094073_2024-05-07_final
2024-05-14 09:46:21	ga_ls9c_ard_3-2-1_095073_2024-05-14_final
2024-05-23 09:40:04	ga_ls9c_ard_3-2-1_094073_2024-05-23_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

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