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
2021-11-02 10:53:16	ga_ls9c_ard_3-2-1_106074_2021-11-02_final.stac-item
2021-11-02 10:54:03	ga_ls9c_ard_3-2-1_106076_2021-11-02_final.stac-item
2021-11-07 10:55:45	ga_ls9c_ard_3-2-1_106074_2021-11-07_final.stac-item
2021-11-07 10:56:32	ga_ls9c_ard_3-2-1_106076_2021-11-07_final.stac-item
2021-11-12 10:56:37	ga_ls9c_ard_3-2-1_106070_2021-11-12_final.stac-item
2021-11-12 10:58:13	ga_ls9c_ard_3-2-1_106074_2021-11-12_final.stac-item
2021-11-22 11:01:32	ga_ls9c_ard_3-2-1_107070_2021-11-22_final.stac-item
2021-12-13 10:56:18	ga_ls9c_ard_3-2-1_106076_2021-12-13_final.stac-item
2022-01-21 11:00:02	ga_ls9c_ard_3-2-1_107070_2022-01-21_final.stac-item
2022-01-23 10:50:04	ga_ls9c_ard_3-2-1_105076_2022-01-23_final.stac-item
2022-01-30 10:55:28	ga_ls9c_ard_3-2-1_106074_2022-01-30_final.stac-item
2022-02-06 11:00:02	ga_ls9c_ard_3-2-1_107070_2022-02-06_final.stac-item
2022-02-15 10:55:23	ga_ls9c_ard_3-2-1_106074_2022-02-15_final.stac-item
2022-02-15 10:56:11	ga_ls9c_ard_3-2-1_106076_2022-02-15_final.stac-item
2022-02-24 10:49:54	ga_ls9c_ard_3-2-1_105076_2022-02-24_final.stac-item
2022-03-03 10:55:12	ga_ls9c_ard_3-2-1_106074_2022-03-03_final.stac-item
2022-03-03 10:56:00	ga_ls9c_ard_3-2-1_106076_2022-03-03_final.stac-item
2022-04-04 10:55:55	ga_ls9c_ard_3-2-1_106076_2022-04-04_final.stac-item
2022-04-11 10:59:40	ga_ls9c_ard_3-2-1_107070_2022-04-11_final.stac-item
2022-04-29 10:49:33	ga_ls9c_ard_3-2-1_105076_2022-04-29_final.stac-item
2022-05-06 10:55:41	ga_ls9c_ard_3-2-1_106076_2022-05-06_final.stac-item
2022-05-13 10:59:23	ga_ls9c_ard_3-2-1_107070_2022-05-13_final.stac-item
2022-05-22 10:54:42	ga_ls9c_ard_3-2-1_106074_2022-05-22_final.stac-item
2022-06-14 10:59:22	ga_ls9c_ard_3-2-1_107070_2022-06-14_final.stac-item
2022-06-23 10:55:01	ga_ls9c_ard_3-2-1_106074_2022-06-23_final.stac-item
2022-06-23 10:55:49	ga_ls9c_ard_3-2-1_106076_2022-06-23_final.stac-item
2022-06-30 10:59:39	ga_ls9c_ard_3-2-1_107070_2022-06-30_final.stac-item
2022-07-09 10:55:01	ga_ls9c_ard_3-2-1_106074_2022-07-09_final.stac-item
2022-07-16 10:59:35	ga_ls9c_ard_3-2-1_107070_2022-07-16_final.stac-item
2022-07-18 10:49:39	ga_ls9c_ard_3-2-1_105076_2022-07-18_final.stac-item
2022-07-25 10:55:09	ga_ls9c_ard_3-2-1_106074_2022-07-25_final.stac-item
2022-08-03 10:49:53	ga_ls9c_ard_3-2-1_105076_2022-08-03_final.stac-item
2022-08-26 10:55:25	ga_ls9c_ard_3-2-1_106074_2022-08-26_final.stac-item
2022-08-26 10:56:13	ga_ls9c_ard_3-2-1_106076_2022-08-26_final.stac-item
2022-09-11 10:55:26	ga_ls9c_ard_3-2-1_106074_2022-09-11_final.stac-item
2022-09-11 10:56:14	ga_ls9c_ard_3-2-1_106076_2022-09-11_final.stac-item
2022-09-27 10:55:32	ga_ls9c_ard_3-2-1_106074_2022-09-27_final.stac-item
2022-10-13 10:55:36	ga_ls9c_ard_3-2-1_106074_2022-10-13_final.stac-item
2022-10-13 10:56:24	ga_ls9c_ard_3-2-1_106076_2022-10-13_final.stac-item
2022-10-20 11:00:13	ga_ls9c_ard_3-2-1_107070_2022-10-20_final.stac-item
2022-10-22 10:50:15	ga_ls9c_ard_3-2-1_105076_2022-10-22_final.stac-item
2022-11-05 11:00:11	ga_ls9c_ard_3-2-1_107070_2022-11-05_final.stac-item
2022-11-07 10:50:14	ga_ls9c_ard_3-2-1_105076_2022-11-07_final.stac-item
2022-11-14 10:55:39	ga_ls9c_ard_3-2-1_106074_2022-11-14_final.stac-item
2022-11-21 11:00:14	ga_ls9c_ard_3-2-1_107070_2022-11-21_final.stac-item
2022-11-30 10:56:24	ga_ls9c_ard_3-2-1_106076_2022-11-30_final.stac-item
2022-12-07 11:00:12	ga_ls9c_ard_3-2-1_107070_2022-12-07_final.stac-item
2022-12-16 10:55:38	ga_ls9c_ard_3-2-1_106074_2022-12-16_final.stac-item
2022-12-16 10:56:26	ga_ls9c_ard_3-2-1_106076_2022-12-16_final.stac-item
2022-12-23 11:00:10	ga_ls9c_ard_3-2-1_107070_2022-12-23_final.stac-item
2023-01-01 10:55:38	ga_ls9c_ard_3-2-1_106074_2023-01-01_final.stac-item
2023-01-08 11:00:13	ga_ls9c_ard_3-2-1_107070_2023-01-08_final.stac-item
2023-01-10 10:50:14	ga_ls9c_ard_3-2-1_105076_2023-01-10_final.stac-item
2023-01-17 10:55:32	ga_ls9c_ard_3-2-1_106074_2023-01-17_final.stac-item
2023-01-24 11:00:07	ga_ls9c_ard_3-2-1_107070_2023-01-24_final.stac-item
2023-02-09 10:59:29	ga_ls9c_ard_3-2-1_107068_2023-02-09_interim.stac-item
2023-02-09 11:00:17	ga_ls9c_ard_3-2-1_107070_2023-02-09_final.stac-item
2023-02-25 10:59:14	ga_ls9c_ard_3-2-1_107068_2023-02-25_interim.stac-item
2023-02-25 11:00:02	ga_ls9c_ard_3-2-1_107070_2023-02-25_final.stac-item
2023-03-06 10:55:23	ga_ls9c_ard_3-2-1_106074_2023-03-06_final.stac-item
2023-03-13 10:59:55	ga_ls9c_ard_3-2-1_107070_2023-03-13_final.stac-item
2023-03-29 10:58:56	ga_ls9c_ard_3-2-1_107068_2023-03-29_final.stac-item
2023-03-29 10:59:44	ga_ls9c_ard_3-2-1_107070_2023-03-29_final.stac-item
2023-04-07 10:55:07	ga_ls9c_ard_3-2-1_106074_2023-04-07_final.stac-item
2023-04-14 10:59:37	ga_ls9c_ard_3-2-1_107070_2023-04-14_final.stac-item
2023-04-23 10:55:01	ga_ls9c_ard_3-2-1_106074_2023-04-23_final.stac-item
2023-04-30 10:59:30	ga_ls9c_ard_3-2-1_107070_2023-04-30_final.stac-item
2023-05-16 10:59:22	ga_ls9c_ard_3-2-1_107070_2023-05-16_final.stac-item
2023-05-25 10:54:39	ga_ls9c_ard_3-2-1_106074_2023-05-25_final.stac-item
2023-06-10 10:54:35	ga_ls9c_ard_3-2-1_106074_2023-06-10_final.stac-item
2023-06-26 10:54:30	ga_ls9c_ard_3-2-1_106074_2023-06-26_final.stac-item
2023-07-03 10:59:16	ga_ls9c_ard_3-2-1_107070_2023-07-03_final.stac-item
2023-07-12 10:54:46	ga_ls9c_ard_3-2-1_106074_2023-07-12_final.stac-item
2023-07-28 10:54:49	ga_ls9c_ard_3-2-1_106074_2023-07-28_final.stac-item
2023-08-04 10:59:30	ga_ls9c_ard_3-2-1_107070_2023-08-04_final.stac-item
2023-08-13 10:54:57	ga_ls9c_ard_3-2-1_106074_2023-08-13_final.stac-item
2023-08-20 10:59:34	ga_ls9c_ard_3-2-1_107070_2023-08-20_final.stac-item
2023-08-29 10:55:06	ga_ls9c_ard_3-2-1_106074_2023-08-29_final.stac-item
2023-09-14 10:55:15	ga_ls9c_ard_3-2-1_106074_2023-09-14_final.stac-item
2023-09-30 10:55:13	ga_ls9c_ard_3-2-1_106074_2023-09-30_final.stac-item
2023-10-07 10:59:53	ga_ls9c_ard_3-2-1_107070_2023-10-07_final.stac-item
2023-10-16 10:55:25	ga_ls9c_ard_3-2-1_106074_2023-10-16_final.stac-item
2023-11-01 10:55:20	ga_ls9c_ard_3-2-1_106074_2023-11-01_final.stac-item
2023-11-08 10:59:56	ga_ls9c_ard_3-2-1_107070_2023-11-08_final.stac-item
2023-11-17 10:55:22	ga_ls9c_ard_3-2-1_106074_2023-11-17_final.stac-item
2023-11-24 11:00:04	ga_ls9c_ard_3-2-1_107070_2023-11-24_final.stac-item
2023-12-03 10:55:28	ga_ls9c_ard_3-2-1_106074_2023-12-03_final.stac-item
2023-12-19 10:55:31	ga_ls9c_ard_3-2-1_106074_2023-12-19_final.stac-item
2023-12-26 11:00:07	ga_ls9c_ard_3-2-1_107070_2023-12-26_final.stac-item
2024-01-04 10:55:26	ga_ls9c_ard_3-2-1_106074_2024-01-04_final.stac-item
2024-01-20 10:55:26	ga_ls9c_ard_3-2-1_106074_2024-01-20_final.stac-item
2024-01-27 11:00:01	ga_ls9c_ard_3-2-1_107070_2024-01-27_final.stac-item
2024-02-05 10:55:30	ga_ls9c_ard_3-2-1_106074_2024-02-05_final.stac-item
2024-02-12 11:00:03	ga_ls9c_ard_3-2-1_107070_2024-02-12_final.stac-item
2024-02-21 10:55:18	ga_ls9c_ard_3-2-1_106074_2024-02-21_final.stac-item
2024-02-28 10:59:54	ga_ls9c_ard_3-2-1_107070_2024-02-28_final.stac-item
2024-03-15 10:59:56	ga_ls9c_ard_3-2-1_107070_2024-03-15_final.stac-item
2024-04-16 10:59:38	ga_ls9c_ard_3-2-1_107070_2024-04-16_final.stac-item
2024-05-02 10:59:22	ga_ls9c_ard_3-2-1_107070_2024-05-02_final.stac-item
2024-05-18 10:59:14	ga_ls9c_ard_3-2-1_107070_2024-05-18_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