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
2021-11-03 09:57:21	ga_ls9c_ard_3-2-1_096081_2021-11-03_final
2021-11-12 10:57:25	ga_ls9c_ard_3-2-1_106072_2021-11-12_final
2021-11-17 09:22:52	ga_ls9c_ard_3-2-1_091076_2021-11-16_final
2021-11-22 11:01:56	ga_ls9c_ard_3-2-1_107071_2021-11-22_final
2021-11-25 09:49:15	ga_ls9c_ard_3-2-1_095083_2021-11-25_final
2021-12-04 11:00:35	ga_ls9c_ard_3-2-1_107071_2021-12-04_final
2021-12-07 09:56:33	ga_ls9c_ard_3-2-1_096081_2021-12-07_final
2021-12-09 11:20:40	ga_ls9c_ard_3-2-1_110075_2021-12-09_final
2021-12-11 09:34:59	ga_ls9c_ard_3-2-1_092089_2021-12-11_final
2021-12-12 11:51:08	ga_ls9c_ard_3-2-1_115074_2021-12-12_final
2021-12-16 09:47:29	ga_ls9c_ard_3-2-1_095074_2021-12-16_final
2021-12-16 09:51:04	ga_ls9c_ard_3-2-1_095083_2021-12-16_final
2021-12-20 11:00:27	ga_ls9c_ard_3-2-1_107071_2021-12-20_final
2021-12-24 10:36:32	ga_ls9c_ard_3-2-1_103073_2021-12-24_final
2021-12-25 11:20:36	ga_ls9c_ard_3-2-1_110075_2021-12-25_final
2022-01-28 09:34:55	ga_ls9c_ard_3-2-1_092089_2022-01-28_final
2022-06-26 09:47:05	ga_ls9c_ard_3-2-1_095074_2022-06-26_final
2022-06-27 10:28:45	ga_ls9c_ard_3-2-1_102070_2022-06-27_final
2022-06-28 09:37:07	ga_ls9c_ard_3-2-1_093080_2022-06-28_final
2022-06-30 11:00:03	ga_ls9c_ard_3-2-1_107071_2022-06-30_final
2022-07-03 09:56:03	ga_ls9c_ard_3-2-1_096081_2022-07-03_final
2022-07-04 10:36:06	ga_ls9c_ard_3-2-1_103073_2022-07-04_final
2022-07-06 10:25:44	ga_ls9c_ard_3-2-1_101078_2022-07-06_final
2022-07-10 09:59:47	ga_ls9c_ard_3-2-1_097075_2022-07-10_final
2022-07-11 10:42:15	ga_ls9c_ard_3-2-1_104073_2022-07-11_final
2022-07-12 09:47:01	ga_ls9c_ard_3-2-1_095074_2022-07-12_final
2022-07-18 10:47:16	ga_ls9c_ard_3-2-1_105070_2022-07-18_final
2022-07-19 09:56:03	ga_ls9c_ard_3-2-1_096081_2022-07-19_final
2022-07-20 10:36:08	ga_ls9c_ard_3-2-1_103073_2022-07-20_final
2022-07-23 09:34:35	ga_ls9c_ard_3-2-1_092089_2022-07-23_final
2022-07-25 09:16:40	ga_ls9c_ard_3-2-1_090075_2022-07-24_final
2022-07-28 09:47:13	ga_ls9c_ard_3-2-1_095074_2022-07-28_final
2022-07-30 09:37:16	ga_ls9c_ard_3-2-1_093080_2022-07-30_final
2022-08-01 11:00:14	ga_ls9c_ard_3-2-1_107071_2022-08-01_final
2022-08-03 10:47:30	ga_ls9c_ard_3-2-1_105070_2022-08-03_final
2022-08-04 09:56:16	ga_ls9c_ard_3-2-1_096081_2022-08-04_final
2022-08-09 10:15:16	ga_ls9c_ard_3-2-1_099082_2022-08-09_final
2022-08-10 09:16:51	ga_ls9c_ard_3-2-1_090075_2022-08-09_final
2022-08-12 10:42:36	ga_ls9c_ard_3-2-1_104073_2022-08-12_final
2022-08-14 10:28:39	ga_ls9c_ard_3-2-1_102069_2022-08-14_final
2022-08-15 09:37:26	ga_ls9c_ard_3-2-1_093080_2022-08-15_final
2022-08-19 10:47:37	ga_ls9c_ard_3-2-1_105070_2022-08-19_final
2022-08-20 11:32:29	ga_ls9c_ard_3-2-1_112074_2022-08-20_final
2022-08-24 09:34:53	ga_ls9c_ard_3-2-1_092089_2022-08-24_final
2022-08-26 09:16:56	ga_ls9c_ard_3-2-1_090075_2022-08-25_final
2022-08-26 10:54:37	ga_ls9c_ard_3-2-1_106072_2022-08-26_final
2022-08-28 10:42:40	ga_ls9c_ard_3-2-1_104073_2022-08-28_final
2022-08-29 09:47:26	ga_ls9c_ard_3-2-1_095074_2022-08-29_final
2022-09-04 10:47:38	ga_ls9c_ard_3-2-1_105070_2022-09-04_final
2022-09-05 11:32:30	ga_ls9c_ard_3-2-1_112074_2022-09-05_final
2022-09-05 11:33:41	ga_ls9c_ard_3-2-1_112077_2022-09-05_final
2022-09-06 10:35:16	ga_ls9c_ard_3-2-1_103070_2022-09-06_final
2022-09-07 09:40:03	ga_ls9c_ard_3-2-1_094071_2022-09-07_final
2022-09-07 09:40:27	ga_ls9c_ard_3-2-1_094072_2022-09-07_final
2022-09-07 11:20:32	ga_ls9c_ard_3-2-1_110075_2022-09-07_final
2022-09-07 11:20:55	ga_ls9c_ard_3-2-1_110076_2022-09-07_final
2022-09-07 11:21:19	ga_ls9c_ard_3-2-1_110077_2022-09-07_final
2022-09-08 10:24:06	ga_ls9c_ard_3-2-1_101073_2022-09-08_final
2022-09-08 10:24:30	ga_ls9c_ard_3-2-1_101074_2022-09-08_final
2022-09-08 10:24:54	ga_ls9c_ard_3-2-1_101075_2022-09-08_final
2022-09-08 10:25:18	ga_ls9c_ard_3-2-1_101076_2022-09-08_final
2022-09-08 10:25:42	ga_ls9c_ard_3-2-1_101077_2022-09-08_final
2022-09-09 09:31:40	ga_ls9c_ard_3-2-1_092081_2022-09-09_final
2022-09-09 09:34:04	ga_ls9c_ard_3-2-1_092087_2022-09-09_final
2022-09-09 09:34:28	ga_ls9c_ard_3-2-1_092088_2022-09-09_final
2022-09-10 10:09:46	ga_ls9c_ard_3-2-1_099068_2022-09-10_final
2022-09-10 10:10:10	ga_ls9c_ard_3-2-1_099069_2022-09-10_final
2022-09-10 10:10:34	ga_ls9c_ard_3-2-1_099070_2022-09-10_final
2022-09-10 10:10:57	ga_ls9c_ard_3-2-1_099071_2022-09-10_final
2022-09-10 10:11:21	ga_ls9c_ard_3-2-1_099072_2022-09-10_final
2022-09-10 10:15:21	ga_ls9c_ard_3-2-1_099082_2022-09-10_final
2022-09-10 10:15:45	ga_ls9c_ard_3-2-1_099083_2022-09-10_final
2022-09-10 10:16:09	ga_ls9c_ard_3-2-1_099084_2022-09-10_final
2022-09-10 10:16:33	ga_ls9c_ard_3-2-1_099085_2022-09-10_final
2022-09-11 09:16:57	ga_ls9c_ard_3-2-1_090075_2022-09-10_final
2022-09-11 09:17:21	ga_ls9c_ard_3-2-1_090076_2022-09-10_final
2022-09-11 10:53:50	ga_ls9c_ard_3-2-1_106070_2022-09-11_final
2022-09-11 10:54:14	ga_ls9c_ard_3-2-1_106071_2022-09-11_final
2022-09-11 10:54:38	ga_ls9c_ard_3-2-1_106072_2022-09-11_final
2022-09-11 10:55:02	ga_ls9c_ard_3-2-1_106073_2022-09-11_final
2022-09-11 10:55:26	ga_ls9c_ard_3-2-1_106074_2022-09-11_final
2022-09-11 10:58:37	ga_ls9c_ard_3-2-1_106082_2022-09-11_final
2022-09-11 10:59:01	ga_ls9c_ard_3-2-1_106083_2022-09-11_final
2022-09-12 11:42:18	ga_ls9c_ard_3-2-1_113083_2022-09-12_final
2022-09-14 09:47:29	ga_ls9c_ard_3-2-1_095074_2022-09-14_final
2022-09-14 09:48:41	ga_ls9c_ard_3-2-1_095077_2022-09-14_final
2022-09-14 11:27:10	ga_ls9c_ard_3-2-1_111076_2022-09-14_final
2022-09-15 10:28:45	ga_ls9c_ard_3-2-1_102069_2022-09-15_final
2022-09-15 10:33:33	ga_ls9c_ard_3-2-1_102081_2022-09-15_final
2022-09-15 10:33:57	ga_ls9c_ard_3-2-1_102082_2022-09-15_final
2022-09-16 09:37:32	ga_ls9c_ard_3-2-1_093080_2022-09-16_final
2022-09-18 09:23:12	ga_ls9c_ard_3-2-1_091075_2022-09-17_final
2022-09-21 11:32:36	ga_ls9c_ard_3-2-1_112074_2022-09-21_final
2022-09-23 09:43:46	ga_ls9c_ard_3-2-1_094080_2022-09-23_final
2023-06-07 10:23:19	ga_ls9c_ard_3-2-1_101073_2023-06-07_final
2023-06-07 10:23:43	ga_ls9c_ard_3-2-1_101074_2023-06-07_final
2023-06-07 10:24:31	ga_ls9c_ard_3-2-1_101076_2023-06-07_final
2023-06-07 10:25:19	ga_ls9c_ard_3-2-1_101078_2023-06-07_final
2023-06-07 10:25:43	ga_ls9c_ard_3-2-1_101079_2023-06-07_final
2023-06-08 09:29:17	ga_ls9c_ard_3-2-1_092077_2023-06-07_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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