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
2021-11-10 11:15:22	ga_ls9c_ard_3-2-1_110070_2021-11-10_final.stac-item
2021-12-06 10:47:24	ga_ls9c_ard_3-2-1_105069_2021-12-06_final.stac-item
2021-12-11 11:05:53	ga_ls9c_ard_3-2-1_108069_2021-12-11_final.stac-item
2021-12-13 10:53:30	ga_ls9c_ard_3-2-1_106069_2021-12-13_final.stac-item
2021-12-16 11:24:46	ga_ls9c_ard_3-2-1_111070_2021-12-16_final.stac-item
2021-12-22 10:47:18	ga_ls9c_ard_3-2-1_105069_2021-12-22_final.stac-item
2021-12-24 10:34:56	ga_ls9c_ard_3-2-1_103069_2021-12-24_final.stac-item
2021-12-27 11:05:50	ga_ls9c_ard_3-2-1_108069_2021-12-27_final.stac-item
2022-01-01 11:24:46	ga_ls9c_ard_3-2-1_111070_2022-01-01_final.stac-item
2022-01-09 10:34:54	ga_ls9c_ard_3-2-1_103069_2022-01-09_final.stac-item
2022-01-10 11:18:33	ga_ls9c_ard_3-2-1_110070_2022-01-10_final.stac-item
2022-01-12 11:05:47	ga_ls9c_ard_3-2-1_108069_2022-01-12_final.stac-item
2022-01-14 10:53:25	ga_ls9c_ard_3-2-1_106069_2022-01-14_final.stac-item
2022-01-16 10:41:04	ga_ls9c_ard_3-2-1_104069_2022-01-16_final.stac-item
2022-01-23 10:47:17	ga_ls9c_ard_3-2-1_105069_2022-01-23_final.stac-item
2022-01-25 10:34:55	ga_ls9c_ard_3-2-1_103069_2022-01-25_final.stac-item
2022-01-28 11:05:49	ga_ls9c_ard_3-2-1_108069_2022-01-28_final.stac-item
2022-02-02 11:24:46	ga_ls9c_ard_3-2-1_111070_2022-02-02_final.stac-item
2022-02-10 10:34:53	ga_ls9c_ard_3-2-1_103069_2022-02-10_final.stac-item
2022-02-13 11:05:46	ga_ls9c_ard_3-2-1_108069_2022-02-13_final.stac-item
2022-02-17 10:41:01	ga_ls9c_ard_3-2-1_104069_2022-02-17_final.stac-item
2022-03-01 11:05:35	ga_ls9c_ard_3-2-1_108069_2022-03-01_final.stac-item
2022-03-21 10:40:49	ga_ls9c_ard_3-2-1_104069_2022-03-21_final.stac-item
2022-04-02 11:05:30	ga_ls9c_ard_3-2-1_108069_2022-04-02_final.stac-item
2022-04-04 10:53:08	ga_ls9c_ard_3-2-1_106069_2022-04-04_final.stac-item
2022-04-13 10:46:53	ga_ls9c_ard_3-2-1_105069_2022-04-13_final.stac-item
2022-04-15 10:34:30	ga_ls9c_ard_3-2-1_103069_2022-04-15_final.stac-item
2022-04-20 10:52:58	ga_ls9c_ard_3-2-1_106069_2022-04-20_final.stac-item
2022-04-22 10:40:35	ga_ls9c_ard_3-2-1_104069_2022-04-22_final.stac-item
2022-05-04 11:05:16	ga_ls9c_ard_3-2-1_108069_2022-05-04_final.stac-item
2022-05-06 10:52:53	ga_ls9c_ard_3-2-1_106069_2022-05-06_final.stac-item
2022-05-20 11:05:03	ga_ls9c_ard_3-2-1_108069_2022-05-20_final.stac-item
2022-05-24 10:40:20	ga_ls9c_ard_3-2-1_104069_2022-05-24_final.stac-item
2022-05-31 10:46:32	ga_ls9c_ard_3-2-1_105069_2022-05-31_final.stac-item
2022-06-09 10:40:22	ga_ls9c_ard_3-2-1_104069_2022-06-09_final.stac-item
2022-06-10 11:24:02	ga_ls9c_ard_3-2-1_111070_2022-06-10_final.stac-item
2022-06-16 10:46:38	ga_ls9c_ard_3-2-1_105069_2022-06-16_final.stac-item
2022-06-18 10:34:18	ga_ls9c_ard_3-2-1_103069_2022-06-18_final.stac-item
2022-06-23 10:53:01	ga_ls9c_ard_3-2-1_106069_2022-06-23_final.stac-item
2022-06-26 11:24:22	ga_ls9c_ard_3-2-1_111070_2022-06-26_final.stac-item
2022-07-09 10:53:02	ga_ls9c_ard_3-2-1_106069_2022-07-09_final.stac-item
2022-07-12 11:24:18	ga_ls9c_ard_3-2-1_111070_2022-07-12_final.stac-item
2022-07-23 11:05:29	ga_ls9c_ard_3-2-1_108069_2022-07-23_final.stac-item
2022-07-25 10:53:10	ga_ls9c_ard_3-2-1_106069_2022-07-25_final.stac-item
2022-07-27 10:40:50	ga_ls9c_ard_3-2-1_104069_2022-07-27_final.stac-item
2022-07-28 11:24:30	ga_ls9c_ard_3-2-1_111070_2022-07-28_final.stac-item
2022-08-06 11:18:26	ga_ls9c_ard_3-2-1_110070_2022-08-06_final.stac-item
2022-08-13 11:24:40	ga_ls9c_ard_3-2-1_111070_2022-08-13_final.stac-item
2022-08-22 11:18:32	ga_ls9c_ard_3-2-1_110070_2022-08-22_final.stac-item
2022-08-24 11:05:47	ga_ls9c_ard_3-2-1_108069_2022-08-24_final.stac-item
2022-08-29 11:24:44	ga_ls9c_ard_3-2-1_111070_2022-08-29_final.stac-item
2022-09-04 10:47:14	ga_ls9c_ard_3-2-1_105069_2022-09-04_final.stac-item
2022-09-22 10:34:59	ga_ls9c_ard_3-2-1_103069_2022-09-22_final.stac-item
2022-09-25 11:05:54	ga_ls9c_ard_3-2-1_108069_2022-09-25_final.stac-item
2022-10-06 10:47:21	ga_ls9c_ard_3-2-1_105069_2022-10-06_final.stac-item
2022-10-09 11:18:41	ga_ls9c_ard_3-2-1_110070_2022-10-09_final.stac-item
2022-10-11 11:05:57	ga_ls9c_ard_3-2-1_108069_2022-10-11_final.stac-item
2022-11-28 11:05:59	ga_ls9c_ard_3-2-1_108069_2022-11-28_final.stac-item
2022-11-30 10:53:36	ga_ls9c_ard_3-2-1_106069_2022-11-30_final.stac-item
2022-12-14 11:06:00	ga_ls9c_ard_3-2-1_108069_2022-12-14_final.stac-item
2022-12-16 10:53:38	ga_ls9c_ard_3-2-1_106069_2022-12-16_final.stac-item
2022-12-30 11:05:59	ga_ls9c_ard_3-2-1_108069_2022-12-30_final.stac-item
2023-01-17 10:53:32	ga_ls9c_ard_3-2-1_106069_2023-01-17_final.stac-item
2023-02-09 10:59:53	ga_ls9c_ard_3-2-1_107069_2023-02-09_interim.stac-item
2023-02-16 11:06:00	ga_ls9c_ard_3-2-1_108069_2023-02-16_final.stac-item
2023-02-18 10:53:36	ga_ls9c_ard_3-2-1_106069_2023-02-18_final.stac-item
2023-02-25 10:59:38	ga_ls9c_ard_3-2-1_107069_2023-02-25_final.stac-item
2023-03-06 10:53:24	ga_ls9c_ard_3-2-1_106069_2023-03-06_final.stac-item
2023-03-13 10:59:31	ga_ls9c_ard_3-2-1_107069_2023-03-13_final.stac-item
2023-03-22 10:53:17	ga_ls9c_ard_3-2-1_106069_2023-03-22_final.stac-item
2023-03-29 10:59:20	ga_ls9c_ard_3-2-1_107069_2023-03-29_final.stac-item
2023-04-23 10:53:01	ga_ls9c_ard_3-2-1_106069_2023-04-23_final.stac-item
2023-05-25 10:52:40	ga_ls9c_ard_3-2-1_106069_2023-05-25_final.stac-item
2023-06-22 11:17:38	ga_ls9c_ard_3-2-1_110070_2023-06-22_final.stac-item
2023-06-24 11:04:52	ga_ls9c_ard_3-2-1_108069_2023-06-24_final.stac-item
2023-06-29 11:23:55	ga_ls9c_ard_3-2-1_111070_2023-06-29_final.stac-item
2023-07-03 10:58:52	ga_ls9c_ard_3-2-1_107069_2023-07-03_final.stac-item
2023-07-08 11:17:52	ga_ls9c_ard_3-2-1_110070_2023-07-08_final.stac-item
2023-07-15 11:24:06	ga_ls9c_ard_3-2-1_111070_2023-07-15_final.stac-item
2023-07-19 10:58:58	ga_ls9c_ard_3-2-1_107069_2023-07-19_final.stac-item
2023-07-31 11:24:10	ga_ls9c_ard_3-2-1_111070_2023-07-31_final.stac-item
2023-08-16 11:24:15	ga_ls9c_ard_3-2-1_111070_2023-08-16_final.stac-item
2023-08-20 10:59:10	ga_ls9c_ard_3-2-1_107069_2023-08-20_final.stac-item
2023-09-01 11:24:26	ga_ls9c_ard_3-2-1_111070_2023-09-01_final.stac-item
2023-09-17 11:24:34	ga_ls9c_ard_3-2-1_111070_2023-09-17_final.stac-item
2023-09-21 10:59:26	ga_ls9c_ard_3-2-1_107069_2023-09-21_final.stac-item
2023-09-28 11:05:32	ga_ls9c_ard_3-2-1_108069_2023-09-28_final.stac-item
2023-10-07 10:59:30	ga_ls9c_ard_3-2-1_107069_2023-10-07_final.stac-item
2023-10-23 10:59:37	ga_ls9c_ard_3-2-1_107069_2023-10-23_final.stac-item
2023-11-04 11:24:37	ga_ls9c_ard_3-2-1_111070_2023-11-04_final.stac-item
2023-11-08 10:59:33	ga_ls9c_ard_3-2-1_107069_2023-11-08_final.stac-item
2023-11-15 11:05:43	ga_ls9c_ard_3-2-1_108069_2023-11-15_final.stac-item
2023-11-17 10:53:23	ga_ls9c_ard_3-2-1_106069_2023-11-17_final.stac-item
2023-11-24 10:59:40	ga_ls9c_ard_3-2-1_107069_2023-11-24_final.stac-item
2023-12-10 10:59:37	ga_ls9c_ard_3-2-1_107069_2023-12-10_final.stac-item
2023-12-26 10:59:43	ga_ls9c_ard_3-2-1_107069_2023-12-26_final.stac-item
2024-02-08 11:24:48	ga_ls9c_ard_3-2-1_111070_2024-02-08_final.stac-item
2024-02-24 11:24:34	ga_ls9c_ard_3-2-1_111070_2024-02-24_final.stac-item
2024-02-28 10:59:30	ga_ls9c_ard_3-2-1_107069_2024-02-28_final.stac-item
2024-04-09 10:53:10	ga_ls9c_ard_3-2-1_106069_2024-04-09_final.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