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
2021-12-19 11:58:52	ga_ls9c_ard_3-2-1_116078_2021-12-19_final.stac-item
2021-12-28 11:53:29	ga_ls9c_ard_3-2-1_115080_2021-12-28_final.stac-item
2022-01-13 11:53:26	ga_ls9c_ard_3-2-1_115080_2022-01-13_final.stac-item
2022-01-20 11:58:27	ga_ls9c_ard_3-2-1_116077_2022-01-20_final.stac-item
2022-01-20 11:58:51	ga_ls9c_ard_3-2-1_116078_2022-01-20_final.stac-item
2022-02-05 11:58:27	ga_ls9c_ard_3-2-1_116077_2022-02-05_final.stac-item
2022-02-05 11:58:51	ga_ls9c_ard_3-2-1_116078_2022-02-05_final.stac-item
2022-02-21 11:58:43	ga_ls9c_ard_3-2-1_116078_2022-02-21_final.stac-item
2022-03-09 11:58:13	ga_ls9c_ard_3-2-1_116077_2022-03-09_final.stac-item
2022-03-09 11:58:37	ga_ls9c_ard_3-2-1_116078_2022-03-09_final.stac-item
2022-03-25 11:58:32	ga_ls9c_ard_3-2-1_116078_2022-03-25_final.stac-item
2022-04-10 11:58:05	ga_ls9c_ard_3-2-1_116077_2022-04-10_final.stac-item
2022-04-10 11:58:29	ga_ls9c_ard_3-2-1_116078_2022-04-10_final.stac-item
2022-04-26 11:58:20	ga_ls9c_ard_3-2-1_116078_2022-04-26_final.stac-item
2022-05-05 11:52:55	ga_ls9c_ard_3-2-1_115080_2022-05-05_final.stac-item
2022-05-12 11:57:49	ga_ls9c_ard_3-2-1_116077_2022-05-12_final.stac-item
2022-05-12 11:58:13	ga_ls9c_ard_3-2-1_116078_2022-05-12_final.stac-item
2022-05-21 11:52:43	ga_ls9c_ard_3-2-1_115080_2022-05-21_final.stac-item
2022-05-28 11:58:06	ga_ls9c_ard_3-2-1_116078_2022-05-28_final.stac-item
2022-06-13 11:57:47	ga_ls9c_ard_3-2-1_116077_2022-06-13_final.stac-item
2022-06-13 11:58:10	ga_ls9c_ard_3-2-1_116078_2022-06-13_final.stac-item
2022-06-29 11:58:28	ga_ls9c_ard_3-2-1_116078_2022-06-29_final.stac-item
2022-07-15 11:57:59	ga_ls9c_ard_3-2-1_116077_2022-07-15_final.stac-item
2022-07-15 11:58:23	ga_ls9c_ard_3-2-1_116078_2022-07-15_final.stac-item
2022-07-24 11:53:09	ga_ls9c_ard_3-2-1_115080_2022-07-24_final.stac-item
2022-07-31 11:58:14	ga_ls9c_ard_3-2-1_116077_2022-07-31_final.stac-item
2022-07-31 11:58:38	ga_ls9c_ard_3-2-1_116078_2022-07-31_final.stac-item
2022-08-25 11:53:26	ga_ls9c_ard_3-2-1_115080_2022-08-25_final.stac-item
2022-09-01 11:58:49	ga_ls9c_ard_3-2-1_116078_2022-09-01_final.stac-item
2022-09-10 11:53:26	ga_ls9c_ard_3-2-1_115080_2022-09-10_final.stac-item
2022-09-26 11:53:33	ga_ls9c_ard_3-2-1_115080_2022-09-26_final.stac-item
2022-10-03 11:58:32	ga_ls9c_ard_3-2-1_116077_2022-10-03_final.stac-item
2022-10-03 11:58:56	ga_ls9c_ard_3-2-1_116078_2022-10-03_final.stac-item
2022-10-19 11:58:38	ga_ls9c_ard_3-2-1_116077_2022-10-19_final.stac-item
2022-10-19 11:59:02	ga_ls9c_ard_3-2-1_116078_2022-10-19_final.stac-item
2022-10-28 11:53:39	ga_ls9c_ard_3-2-1_115080_2022-10-28_final.stac-item
2022-11-04 11:58:59	ga_ls9c_ard_3-2-1_116078_2022-11-04_final.stac-item
2022-11-20 11:59:03	ga_ls9c_ard_3-2-1_116078_2022-11-20_final.stac-item
2022-11-29 11:53:37	ga_ls9c_ard_3-2-1_115080_2022-11-29_final.stac-item
2022-12-06 11:58:37	ga_ls9c_ard_3-2-1_116077_2022-12-06_final.stac-item
2022-12-06 11:59:01	ga_ls9c_ard_3-2-1_116078_2022-12-06_final.stac-item
2022-12-15 11:53:39	ga_ls9c_ard_3-2-1_115080_2022-12-15_final.stac-item
2022-12-22 11:58:59	ga_ls9c_ard_3-2-1_116078_2022-12-22_final.stac-item
2022-12-31 11:53:39	ga_ls9c_ard_3-2-1_115080_2022-12-31_final.stac-item
2023-01-07 11:58:38	ga_ls9c_ard_3-2-1_116077_2023-01-07_final.stac-item
2023-01-07 11:59:02	ga_ls9c_ard_3-2-1_116078_2023-01-07_final.stac-item
2023-01-16 11:53:34	ga_ls9c_ard_3-2-1_115080_2023-01-16_final.stac-item
2023-01-23 11:58:31	ga_ls9c_ard_3-2-1_116077_2023-01-23_final.stac-item
2023-01-23 11:58:55	ga_ls9c_ard_3-2-1_116078_2023-01-23_final.stac-item
2023-02-01 11:53:40	ga_ls9c_ard_3-2-1_115080_2023-02-01_final.stac-item
2023-02-08 11:59:06	ga_ls9c_ard_3-2-1_116078_2023-02-08_final.stac-item
2023-02-17 11:53:38	ga_ls9c_ard_3-2-1_115080_2023-02-17_final.stac-item
2023-03-21 11:53:19	ga_ls9c_ard_3-2-1_115080_2023-03-21_final.stac-item
2023-04-06 11:53:09	ga_ls9c_ard_3-2-1_115080_2023-04-06_final.stac-item
2023-04-13 11:58:27	ga_ls9c_ard_3-2-1_116078_2023-04-13_final.stac-item
2023-04-29 11:57:56	ga_ls9c_ard_3-2-1_116077_2023-04-29_final.stac-item
2023-04-29 11:58:20	ga_ls9c_ard_3-2-1_116078_2023-04-29_final.stac-item
2023-05-15 11:58:12	ga_ls9c_ard_3-2-1_116078_2023-05-15_final.stac-item
2023-05-24 11:52:41	ga_ls9c_ard_3-2-1_115080_2023-05-24_final.stac-item
2023-05-31 11:57:39	ga_ls9c_ard_3-2-1_116077_2023-05-31_final.stac-item
2023-05-31 11:58:03	ga_ls9c_ard_3-2-1_116078_2023-05-31_final.stac-item
2023-06-09 11:52:37	ga_ls9c_ard_3-2-1_115080_2023-06-09_final.stac-item
2023-06-16 11:57:54	ga_ls9c_ard_3-2-1_116078_2023-06-16_final.stac-item
2023-06-25 11:52:31	ga_ls9c_ard_3-2-1_115080_2023-06-25_final.stac-item
2023-07-02 11:58:04	ga_ls9c_ard_3-2-1_116078_2023-07-02_final.stac-item
2023-07-11 11:52:47	ga_ls9c_ard_3-2-1_115080_2023-07-11_final.stac-item
2023-07-18 11:57:47	ga_ls9c_ard_3-2-1_116077_2023-07-18_final.stac-item
2023-07-27 11:52:49	ga_ls9c_ard_3-2-1_115080_2023-07-27_final.stac-item
2023-08-03 11:57:55	ga_ls9c_ard_3-2-1_116077_2023-08-03_final.stac-item
2023-08-12 11:52:58	ga_ls9c_ard_3-2-1_115080_2023-08-12_final.stac-item
2023-08-19 11:57:58	ga_ls9c_ard_3-2-1_116077_2023-08-19_final.stac-item
2023-08-28 11:53:07	ga_ls9c_ard_3-2-1_115080_2023-08-28_final.stac-item
2023-09-04 11:58:09	ga_ls9c_ard_3-2-1_116077_2023-09-04_final.stac-item
2023-09-13 11:53:16	ga_ls9c_ard_3-2-1_115080_2023-09-13_final.stac-item
2023-09-20 11:58:16	ga_ls9c_ard_3-2-1_116077_2023-09-20_final.stac-item
2023-09-29 11:53:13	ga_ls9c_ard_3-2-1_115080_2023-09-29_final.stac-item
2023-10-06 11:58:18	ga_ls9c_ard_3-2-1_116077_2023-10-06_final.stac-item
2023-10-15 11:53:26	ga_ls9c_ard_3-2-1_115080_2023-10-15_final.stac-item
2023-10-31 11:53:22	ga_ls9c_ard_3-2-1_115080_2023-10-31_final.stac-item
2023-11-07 11:58:21	ga_ls9c_ard_3-2-1_116077_2023-11-07_final.stac-item
2023-11-16 11:53:22	ga_ls9c_ard_3-2-1_115080_2023-11-16_final.stac-item
2023-11-23 11:58:28	ga_ls9c_ard_3-2-1_116077_2023-11-23_final.stac-item
2023-12-02 11:53:30	ga_ls9c_ard_3-2-1_115080_2023-12-02_final.stac-item
2023-12-09 11:58:25	ga_ls9c_ard_3-2-1_116077_2023-12-09_final.stac-item
2023-12-18 11:53:32	ga_ls9c_ard_3-2-1_115080_2023-12-18_final.stac-item
2023-12-25 11:58:32	ga_ls9c_ard_3-2-1_116077_2023-12-25_final.stac-item
2024-01-03 11:53:28	ga_ls9c_ard_3-2-1_115080_2024-01-03_final.stac-item
2024-01-10 11:58:27	ga_ls9c_ard_3-2-1_116077_2024-01-10_final.stac-item
2024-01-19 11:53:28	ga_ls9c_ard_3-2-1_115080_2024-01-19_final.stac-item
2024-01-26 11:58:25	ga_ls9c_ard_3-2-1_116077_2024-01-26_final.stac-item
2024-02-04 11:53:31	ga_ls9c_ard_3-2-1_115080_2024-02-04_final.stac-item
2024-02-20 11:53:20	ga_ls9c_ard_3-2-1_115080_2024-02-20_final.stac-item
2024-02-27 11:58:19	ga_ls9c_ard_3-2-1_116077_2024-02-27_final.stac-item
2024-03-07 11:53:23	ga_ls9c_ard_3-2-1_115080_2024-03-07_final.stac-item
2024-03-23 11:53:19	ga_ls9c_ard_3-2-1_115080_2024-03-23_final.stac-item
2024-03-30 11:58:12	ga_ls9c_ard_3-2-1_116077_2024-03-30_final.stac-item
2024-04-08 11:53:11	ga_ls9c_ard_3-2-1_115080_2024-04-08_final.stac-item
2024-04-15 11:58:04	ga_ls9c_ard_3-2-1_116077_2024-04-15_final.stac-item
2024-04-24 11:52:49	ga_ls9c_ard_3-2-1_115080_2024-04-24_final.stac-item
2024-05-01 11:57:47	ga_ls9c_ard_3-2-1_116077_2024-05-01_nrt.stac-item

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

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years