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
2021-10-31 11:15:11	ga_ls9c_ard_3-2-1_109082_2021-10-31_final.stac-item
2021-11-05 11:17:40	ga_ls9c_ard_3-2-1_109082_2021-11-05_final.stac-item
2021-11-20 11:22:41	ga_ls9c_ard_3-2-1_110076_2021-11-20_final.stac-item
2021-11-20 11:23:28	ga_ls9c_ard_3-2-1_110078_2021-11-20_final.stac-item
2021-12-16 11:27:09	ga_ls9c_ard_3-2-1_111076_2021-12-16_final.stac-item
2021-12-18 11:17:11	ga_ls9c_ard_3-2-1_109082_2021-12-18_final.stac-item
2021-12-18 11:17:59	ga_ls9c_ard_3-2-1_109084_2021-12-18_final.stac-item
2022-01-01 11:27:10	ga_ls9c_ard_3-2-1_111076_2022-01-01_final.stac-item
2022-01-03 11:17:12	ga_ls9c_ard_3-2-1_109082_2022-01-03_final.stac-item
2022-01-03 11:18:00	ga_ls9c_ard_3-2-1_109084_2022-01-03_final.stac-item
2022-01-10 11:21:45	ga_ls9c_ard_3-2-1_110078_2022-01-10_final.stac-item
2022-01-10 11:23:21	ga_ls9c_ard_3-2-1_110082_2022-01-10_final.stac-item
2022-01-19 11:17:10	ga_ls9c_ard_3-2-1_109082_2022-01-19_final.stac-item
2022-01-19 11:17:58	ga_ls9c_ard_3-2-1_109084_2022-01-19_final.stac-item
2022-02-04 11:17:11	ga_ls9c_ard_3-2-1_109082_2022-02-04_final.stac-item
2022-02-18 11:27:03	ga_ls9c_ard_3-2-1_111076_2022-02-18_final.stac-item
2022-02-18 11:27:51	ga_ls9c_ard_3-2-1_111078_2022-02-18_final.stac-item
2022-02-20 11:17:04	ga_ls9c_ard_3-2-1_109082_2022-02-20_final.stac-item
2022-02-20 11:17:52	ga_ls9c_ard_3-2-1_109084_2022-02-20_final.stac-item
2022-03-06 11:26:55	ga_ls9c_ard_3-2-1_111076_2022-03-06_final.stac-item
2022-03-08 11:16:57	ga_ls9c_ard_3-2-1_109082_2022-03-08_final.stac-item
2022-03-24 11:16:53	ga_ls9c_ard_3-2-1_109082_2022-03-24_final.stac-item
2022-03-24 11:17:41	ga_ls9c_ard_3-2-1_109084_2022-03-24_final.stac-item
2022-04-07 11:26:48	ga_ls9c_ard_3-2-1_111076_2022-04-07_final.stac-item
2022-04-09 11:16:50	ga_ls9c_ard_3-2-1_109082_2022-04-09_final.stac-item
2022-04-16 11:21:20	ga_ls9c_ard_3-2-1_110078_2022-04-16_final.stac-item
2022-04-16 11:22:56	ga_ls9c_ard_3-2-1_110082_2022-04-16_final.stac-item
2022-04-25 11:16:40	ga_ls9c_ard_3-2-1_109082_2022-04-25_final.stac-item
2022-05-09 11:26:33	ga_ls9c_ard_3-2-1_111076_2022-05-09_final.stac-item
2022-05-11 11:16:34	ga_ls9c_ard_3-2-1_109082_2022-05-11_final.stac-item
2022-05-11 11:17:22	ga_ls9c_ard_3-2-1_109084_2022-05-11_final.stac-item
2022-05-27 11:16:25	ga_ls9c_ard_3-2-1_109082_2022-05-27_final.stac-item
2022-06-10 11:26:26	ga_ls9c_ard_3-2-1_111076_2022-06-10_final.stac-item
2022-06-12 11:16:30	ga_ls9c_ard_3-2-1_109082_2022-06-12_final.stac-item
2022-06-12 11:17:18	ga_ls9c_ard_3-2-1_109084_2022-06-12_final.stac-item
2022-06-28 11:16:48	ga_ls9c_ard_3-2-1_109082_2022-06-28_final.stac-item
2022-07-14 11:16:43	ga_ls9c_ard_3-2-1_109082_2022-07-14_final.stac-item
2022-07-21 11:21:25	ga_ls9c_ard_3-2-1_110078_2022-07-21_final.stac-item
2022-07-30 11:16:57	ga_ls9c_ard_3-2-1_109082_2022-07-30_final.stac-item
2022-08-06 11:23:13	ga_ls9c_ard_3-2-1_110082_2022-08-06_final.stac-item
2022-08-15 11:17:07	ga_ls9c_ard_3-2-1_109082_2022-08-15_final.stac-item
2022-08-22 11:21:44	ga_ls9c_ard_3-2-1_110078_2022-08-22_final.stac-item
2022-08-31 11:17:09	ga_ls9c_ard_3-2-1_109082_2022-08-31_final.stac-item
2022-08-31 11:17:57	ga_ls9c_ard_3-2-1_109084_2022-08-31_final.stac-item
2022-09-14 11:27:10	ga_ls9c_ard_3-2-1_111076_2022-09-14_final.stac-item
2022-09-16 11:17:13	ga_ls9c_ard_3-2-1_109082_2022-09-16_final.stac-item
2022-09-23 11:23:27	ga_ls9c_ard_3-2-1_110082_2022-09-23_final.stac-item
2022-09-30 11:27:15	ga_ls9c_ard_3-2-1_111076_2022-09-30_final.stac-item
2022-10-02 11:17:17	ga_ls9c_ard_3-2-1_109082_2022-10-02_final.stac-item
2022-10-02 11:18:04	ga_ls9c_ard_3-2-1_109084_2022-10-02_final.stac-item
2022-10-25 11:23:33	ga_ls9c_ard_3-2-1_110082_2022-10-25_final.stac-item
2022-11-03 11:17:19	ga_ls9c_ard_3-2-1_109082_2022-11-03_final.stac-item
2022-11-03 11:18:07	ga_ls9c_ard_3-2-1_109084_2022-11-03_final.stac-item
2022-11-10 11:23:33	ga_ls9c_ard_3-2-1_110082_2022-11-10_final.stac-item
2022-11-19 11:17:23	ga_ls9c_ard_3-2-1_109082_2022-11-19_final.stac-item
2022-11-26 11:23:33	ga_ls9c_ard_3-2-1_110082_2022-11-26_final.stac-item
2022-12-05 11:17:21	ga_ls9c_ard_3-2-1_109082_2022-12-05_final.stac-item
2022-12-12 11:23:33	ga_ls9c_ard_3-2-1_110082_2022-12-12_final.stac-item
2022-12-21 11:17:20	ga_ls9c_ard_3-2-1_109082_2022-12-21_final.stac-item
2022-12-28 11:23:31	ga_ls9c_ard_3-2-1_110082_2022-12-28_final.stac-item
2023-01-06 11:17:22	ga_ls9c_ard_3-2-1_109082_2023-01-06_final.stac-item
2023-01-06 11:18:10	ga_ls9c_ard_3-2-1_109084_2023-01-06_final.stac-item
2023-01-13 11:23:31	ga_ls9c_ard_3-2-1_110082_2023-01-13_final.stac-item
2023-01-22 11:17:14	ga_ls9c_ard_3-2-1_109082_2023-01-22_final.stac-item
2023-01-22 11:18:02	ga_ls9c_ard_3-2-1_109084_2023-01-22_final.stac-item
2023-01-29 11:23:32	ga_ls9c_ard_3-2-1_110082_2023-01-29_final.stac-item
2023-02-07 11:17:26	ga_ls9c_ard_3-2-1_109082_2023-02-07_final.stac-item
2023-02-14 11:23:34	ga_ls9c_ard_3-2-1_110082_2023-02-14_final.stac-item
2023-02-23 11:17:12	ga_ls9c_ard_3-2-1_109082_2023-02-23_final.stac-item
2023-02-23 11:18:00	ga_ls9c_ard_3-2-1_109084_2023-02-23_final.stac-item
2023-03-02 11:23:21	ga_ls9c_ard_3-2-1_110082_2023-03-02_final.stac-item
2023-03-11 11:17:51	ga_ls9c_ard_3-2-1_109084_2023-03-11_final.stac-item
2023-03-18 11:23:14	ga_ls9c_ard_3-2-1_110082_2023-03-18_final.stac-item
2023-03-25 11:27:44	ga_ls9c_ard_3-2-1_111078_2023-03-25_final.stac-item
2023-04-03 11:23:03	ga_ls9c_ard_3-2-1_110082_2023-04-03_final.stac-item
2023-04-12 11:16:48	ga_ls9c_ard_3-2-1_109082_2023-04-12_final.stac-item
2023-04-12 11:17:36	ga_ls9c_ard_3-2-1_109084_2023-04-12_final.stac-item
2023-04-19 11:22:57	ga_ls9c_ard_3-2-1_110082_2023-04-19_final.stac-item
2023-04-28 11:16:41	ga_ls9c_ard_3-2-1_109082_2023-04-28_final.stac-item
2023-05-05 11:22:45	ga_ls9c_ard_3-2-1_110082_2023-05-05_final.stac-item
2023-05-14 11:16:32	ga_ls9c_ard_3-2-1_109082_2023-05-14_final.stac-item
2023-05-21 11:22:38	ga_ls9c_ard_3-2-1_110082_2023-05-21_final.stac-item
2023-05-30 11:16:24	ga_ls9c_ard_3-2-1_109082_2023-05-30_final.stac-item
2023-06-06 11:20:57	ga_ls9c_ard_3-2-1_110078_2023-06-06_final.stac-item
2023-06-06 11:22:32	ga_ls9c_ard_3-2-1_110082_2023-06-06_final.stac-item
2023-06-22 11:22:25	ga_ls9c_ard_3-2-1_110082_2023-06-22_final.stac-item
2023-07-01 11:16:23	ga_ls9c_ard_3-2-1_109082_2023-07-01_final.stac-item
2023-11-04 11:27:01	ga_ls9c_ard_3-2-1_111076_2023-11-04_final.stac-item
2023-11-20 11:27:07	ga_ls9c_ard_3-2-1_111076_2023-11-20_final.stac-item
2023-12-06 11:27:08	ga_ls9c_ard_3-2-1_111076_2023-12-06_final.stac-item
2023-12-22 11:27:14	ga_ls9c_ard_3-2-1_111076_2023-12-22_final.stac-item
2024-01-07 11:27:07	ga_ls9c_ard_3-2-1_111076_2024-01-07_final.stac-item
2024-01-23 11:27:06	ga_ls9c_ard_3-2-1_111076_2024-01-23_final.stac-item
2024-01-23 11:27:06	ga_ls9c_ard_3-2-1_111076_2024-01-23_interim.stac-item
2024-02-08 11:27:12	ga_ls9c_ard_3-2-1_111076_2024-02-08_final.stac-item
2024-02-24 11:26:58	ga_ls9c_ard_3-2-1_111076_2024-02-24_final.stac-item
2024-03-11 11:27:03	ga_ls9c_ard_3-2-1_111076_2024-03-11_final.stac-item
2024-03-27 11:26:56	ga_ls9c_ard_3-2-1_111076_2024-03-27_final.stac-item
2024-04-12 11:26:49	ga_ls9c_ard_3-2-1_111076_2024-04-12_final.stac-item
2024-04-28 11:26:30	ga_ls9c_ard_3-2-1_111076_2024-04-28_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years