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
2021-12-13 09:21:24	ga_ls9c_ard_3-2-1_090086_2021-12-12_final
2021-12-22 09:15:12	ga_ls9c_ard_3-2-1_089086_2021-12-21_final
2022-01-30 09:21:22	ga_ls9c_ard_3-2-1_090086_2022-01-29_final
2022-02-22 09:27:24	ga_ls9c_ard_3-2-1_091086_2022-02-21_final
2022-02-24 09:15:00	ga_ls9c_ard_3-2-1_089086_2022-02-23_final
2022-03-03 09:20:42	ga_ls9c_ard_3-2-1_090085_2022-03-02_final
2022-03-08 09:39:40	ga_ls9c_ard_3-2-1_093086_2022-03-08_final
2022-04-20 09:20:28	ga_ls9c_ard_3-2-1_090085_2022-04-19_final
2022-04-30 09:57:31	ga_ls9c_ard_3-2-1_096085_2022-04-30_final
2022-05-02 09:45:09	ga_ls9c_ard_3-2-1_094085_2022-05-02_final
2022-05-02 11:24:02	ga_ls9c_ard_3-2-1_110085_2022-05-02_final
2022-05-04 09:32:46	ga_ls9c_ard_3-2-1_092085_2022-05-04_final
2022-05-07 10:03:39	ga_ls9c_ard_3-2-1_097085_2022-05-07_final
2022-05-09 09:51:16	ga_ls9c_ard_3-2-1_095085_2022-05-09_final
2022-05-22 09:20:12	ga_ls9c_ard_3-2-1_090085_2022-05-21_final
2022-05-25 09:51:06	ga_ls9c_ard_3-2-1_095085_2022-05-25_final
2022-05-27 09:39:08	ga_ls9c_ard_3-2-1_093086_2022-05-27_final
2022-05-29 09:26:23	ga_ls9c_ard_3-2-1_091085_2022-05-28_final
2022-06-05 09:32:35	ga_ls9c_ard_3-2-1_092085_2022-06-05_final
2022-06-12 09:39:12	ga_ls9c_ard_3-2-1_093086_2022-06-12_final
2022-06-21 09:32:49	ga_ls9c_ard_3-2-1_092085_2022-06-21_final
2022-08-31 09:39:28	ga_ls9c_ard_3-2-1_093085_2022-08-31_final
2022-08-31 09:39:52	ga_ls9c_ard_3-2-1_093086_2022-08-31_final
2022-09-18 09:27:11	ga_ls9c_ard_3-2-1_091085_2022-09-17_final
2022-10-27 09:33:30	ga_ls9c_ard_3-2-1_092085_2022-10-27_final
2022-12-03 09:52:00	ga_ls9c_ard_3-2-1_095085_2022-12-03_final
2023-01-09 10:10:35	ga_ls9c_ard_3-2-1_098085_2023-01-09_final
2023-01-15 09:33:26	ga_ls9c_ard_3-2-1_092085_2023-01-15_final
2023-01-27 09:58:10	ga_ls9c_ard_3-2-1_096085_2023-01-27_final
2023-01-29 11:24:44	ga_ls9c_ard_3-2-1_110085_2023-01-29_final
2023-02-07 09:39:44	ga_ls9c_ard_3-2-1_093085_2023-02-07_final
2023-02-09 09:27:23	ga_ls9c_ard_3-2-1_091085_2023-02-08_final
2023-02-10 10:10:38	ga_ls9c_ard_3-2-1_098085_2023-02-10_final
2023-02-14 09:45:53	ga_ls9c_ard_3-2-1_094085_2023-02-14_final
2023-02-16 09:33:30	ga_ls9c_ard_3-2-1_092085_2023-02-16_final
2023-02-18 09:21:06	ga_ls9c_ard_3-2-1_090085_2023-02-17_final
2023-02-23 09:39:31	ga_ls9c_ard_3-2-1_093085_2023-02-23_final
2023-03-02 09:45:40	ga_ls9c_ard_3-2-1_094085_2023-03-02_final
2023-03-04 09:33:17	ga_ls9c_ard_3-2-1_092085_2023-03-04_final
2023-03-07 10:04:08	ga_ls9c_ard_3-2-1_097085_2023-03-07_final
2023-03-09 09:51:44	ga_ls9c_ard_3-2-1_095085_2023-03-09_final
2023-03-11 09:39:22	ga_ls9c_ard_3-2-1_093085_2023-03-11_final
2023-03-16 09:57:55	ga_ls9c_ard_3-2-1_096085_2023-03-16_final
2023-03-18 11:24:26	ga_ls9c_ard_3-2-1_110085_2023-03-18_final
2023-03-20 09:33:10	ga_ls9c_ard_3-2-1_092085_2023-03-20_final
2023-03-21 10:16:26	ga_ls9c_ard_3-2-1_099085_2023-03-21_final
2023-03-23 10:04:02	ga_ls9c_ard_3-2-1_097085_2023-03-23_final
2023-03-25 09:51:39	ga_ls9c_ard_3-2-1_095085_2023-03-25_final
2023-03-29 09:26:50	ga_ls9c_ard_3-2-1_091085_2023-03-28_final
2023-03-30 10:10:05	ga_ls9c_ard_3-2-1_098085_2023-03-30_final
2023-04-01 09:57:44	ga_ls9c_ard_3-2-1_096085_2023-04-01_final
2023-04-03 11:24:15	ga_ls9c_ard_3-2-1_110085_2023-04-03_final
2023-04-05 09:33:00	ga_ls9c_ard_3-2-1_092085_2023-04-05_final
2023-04-06 10:16:15	ga_ls9c_ard_3-2-1_099085_2023-04-06_final
2023-04-07 09:20:38	ga_ls9c_ard_3-2-1_090085_2023-04-06_final
2023-04-08 10:03:53	ga_ls9c_ard_3-2-1_097085_2023-04-08_final
2023-04-10 09:51:30	ga_ls9c_ard_3-2-1_095085_2023-04-10_final
2023-04-12 09:39:07	ga_ls9c_ard_3-2-1_093085_2023-04-12_final
2023-04-14 09:26:43	ga_ls9c_ard_3-2-1_091085_2023-04-13_final
2023-04-15 10:09:58	ga_ls9c_ard_3-2-1_098085_2023-04-15_final
2023-04-17 09:57:37	ga_ls9c_ard_3-2-1_096085_2023-04-17_final
2023-04-19 09:45:16	ga_ls9c_ard_3-2-1_094085_2023-04-19_final
2023-04-19 11:24:09	ga_ls9c_ard_3-2-1_110085_2023-04-19_final
2023-04-21 09:32:54	ga_ls9c_ard_3-2-1_092085_2023-04-21_final
2023-04-22 10:16:09	ga_ls9c_ard_3-2-1_099085_2023-04-22_final
2023-04-24 10:03:47	ga_ls9c_ard_3-2-1_097085_2023-04-24_final
2023-04-26 09:51:24	ga_ls9c_ard_3-2-1_095085_2023-04-26_final
2023-04-28 09:39:00	ga_ls9c_ard_3-2-1_093085_2023-04-28_final
2023-04-30 09:26:37	ga_ls9c_ard_3-2-1_091085_2023-04-29_final
2023-05-01 10:09:51	ga_ls9c_ard_3-2-1_098085_2023-05-01_final
2023-05-03 09:57:27	ga_ls9c_ard_3-2-1_096085_2023-05-03_final
2023-05-05 09:45:03	ga_ls9c_ard_3-2-1_094085_2023-05-05_final
2023-05-05 11:23:56	ga_ls9c_ard_3-2-1_110085_2023-05-05_final
2023-05-07 09:32:42	ga_ls9c_ard_3-2-1_092085_2023-05-07_final
2023-05-08 10:15:58	ga_ls9c_ard_3-2-1_099085_2023-05-08_final
2023-05-09 09:20:20	ga_ls9c_ard_3-2-1_090085_2023-05-08_final
2023-05-10 10:03:36	ga_ls9c_ard_3-2-1_097085_2023-05-10_final
2023-05-12 09:51:14	ga_ls9c_ard_3-2-1_095085_2023-05-12_final
2023-05-14 09:38:51	ga_ls9c_ard_3-2-1_093085_2023-05-14_final
2023-05-16 09:26:28	ga_ls9c_ard_3-2-1_091085_2023-05-15_final
2023-05-17 10:09:43	ga_ls9c_ard_3-2-1_098085_2023-05-17_final
2023-05-19 09:57:20	ga_ls9c_ard_3-2-1_096085_2023-05-19_final
2023-05-21 09:44:57	ga_ls9c_ard_3-2-1_094085_2023-05-21_final
2023-05-21 11:23:50	ga_ls9c_ard_3-2-1_110085_2023-05-21_final
2023-05-23 09:32:33	ga_ls9c_ard_3-2-1_092085_2023-05-23_final
2023-05-24 10:15:48	ga_ls9c_ard_3-2-1_099085_2023-05-24_final
2023-05-25 09:20:10	ga_ls9c_ard_3-2-1_090085_2023-05-24_final
2023-05-26 10:03:26	ga_ls9c_ard_3-2-1_097085_2023-05-26_final
2023-05-28 09:51:04	ga_ls9c_ard_3-2-1_095085_2023-05-28_final
2023-05-30 09:38:42	ga_ls9c_ard_3-2-1_093085_2023-05-30_final
2023-06-01 09:26:20	ga_ls9c_ard_3-2-1_091085_2023-05-31_final
2023-06-03 09:13:58	ga_ls9c_ard_3-2-1_089085_2023-06-02_final
2023-06-06 09:44:51	ga_ls9c_ard_3-2-1_094085_2023-06-06_final
2023-06-08 09:32:28	ga_ls9c_ard_3-2-1_092085_2023-06-08_final
2023-06-10 09:20:05	ga_ls9c_ard_3-2-1_090085_2023-06-09_final
2023-06-15 09:38:33	ga_ls9c_ard_3-2-1_093085_2023-06-15_final
2023-06-17 09:26:11	ga_ls9c_ard_3-2-1_091085_2023-06-16_final
2023-06-24 09:32:22	ga_ls9c_ard_3-2-1_092085_2023-06-24_final
2024-04-30 09:38:51	ga_ls9c_ard_3-2-1_093085_2024-04-30_final
2024-05-09 09:32:39	ga_ls9c_ard_3-2-1_092085_2024-05-09_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