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

57 results

Time (local)	Label
2021-11-03 09:54:34	ga_ls9c_ard_3-2-1_096074_2021-11-03_final.stac-item
2021-12-07 09:53:46	ga_ls9c_ard_3-2-1_096074_2021-12-07_final.stac-item
2021-12-23 09:53:40	ga_ls9c_ard_3-2-1_096074_2021-12-23_final.stac-item
2022-01-08 09:53:38	ga_ls9c_ard_3-2-1_096074_2022-01-08_final.stac-item
2022-01-24 09:53:39	ga_ls9c_ard_3-2-1_096074_2022-01-24_final.stac-item
2022-02-09 09:53:38	ga_ls9c_ard_3-2-1_096074_2022-02-09_final.stac-item
2022-02-25 09:53:28	ga_ls9c_ard_3-2-1_096074_2022-02-25_final.stac-item
2022-03-29 09:53:19	ga_ls9c_ard_3-2-1_096074_2022-03-29_final.stac-item
2022-04-14 09:53:14	ga_ls9c_ard_3-2-1_096074_2022-04-14_final.stac-item
2022-04-30 09:53:08	ga_ls9c_ard_3-2-1_096074_2022-04-30_final.stac-item
2022-05-16 09:52:58	ga_ls9c_ard_3-2-1_096074_2022-05-16_final.stac-item
2022-06-01 09:52:54	ga_ls9c_ard_3-2-1_096074_2022-06-01_final.stac-item
2022-06-17 09:53:01	ga_ls9c_ard_3-2-1_096074_2022-06-17_final.stac-item
2022-07-03 09:53:15	ga_ls9c_ard_3-2-1_096074_2022-07-03_final.stac-item
2022-07-19 09:53:15	ga_ls9c_ard_3-2-1_096074_2022-07-19_final.stac-item
2022-08-04 09:53:29	ga_ls9c_ard_3-2-1_096074_2022-08-04_final.stac-item
2022-08-20 09:53:36	ga_ls9c_ard_3-2-1_096074_2022-08-20_final.stac-item
2022-09-05 09:53:37	ga_ls9c_ard_3-2-1_096074_2022-09-05_final.stac-item
2022-09-21 09:53:43	ga_ls9c_ard_3-2-1_096074_2022-09-21_final.stac-item
2022-10-07 09:53:44	ga_ls9c_ard_3-2-1_096074_2022-10-07_final.stac-item
2022-10-23 09:53:50	ga_ls9c_ard_3-2-1_096074_2022-10-23_final.stac-item
2022-11-08 09:53:49	ga_ls9c_ard_3-2-1_096074_2022-11-08_final.stac-item
2022-11-24 09:53:50	ga_ls9c_ard_3-2-1_096074_2022-11-24_final.stac-item
2022-12-10 09:53:50	ga_ls9c_ard_3-2-1_096074_2022-12-10_final.stac-item
2022-12-26 09:53:47	ga_ls9c_ard_3-2-1_096074_2022-12-26_final.stac-item
2023-01-11 09:53:49	ga_ls9c_ard_3-2-1_096074_2023-01-11_final.stac-item
2023-01-27 09:53:47	ga_ls9c_ard_3-2-1_096074_2023-01-27_final.stac-item
2023-02-12 09:53:53	ga_ls9c_ard_3-2-1_096074_2023-02-12_final.stac-item
2023-03-16 09:53:32	ga_ls9c_ard_3-2-1_096074_2023-03-16_final.stac-item
2023-04-01 09:53:20	ga_ls9c_ard_3-2-1_096074_2023-04-01_final.stac-item
2023-04-17 09:53:14	ga_ls9c_ard_3-2-1_096074_2023-04-17_final.stac-item
2023-05-03 09:53:04	ga_ls9c_ard_3-2-1_096074_2023-05-03_final.stac-item
2023-05-19 09:52:57	ga_ls9c_ard_3-2-1_096074_2023-05-19_final.stac-item
2023-06-04 09:52:50	ga_ls9c_ard_3-2-1_096074_2023-06-04_final.stac-item
2023-06-20 09:52:42	ga_ls9c_ard_3-2-1_096074_2023-06-20_final.stac-item
2023-07-06 09:52:55	ga_ls9c_ard_3-2-1_096074_2023-07-06_final.stac-item
2023-07-22 09:52:58	ga_ls9c_ard_3-2-1_096074_2023-07-22_final.stac-item
2023-08-07 09:53:08	ga_ls9c_ard_3-2-1_096074_2023-08-07_final.stac-item
2023-08-23 09:53:14	ga_ls9c_ard_3-2-1_096074_2023-08-23_final.stac-item
2023-09-08 09:53:24	ga_ls9c_ard_3-2-1_096074_2023-09-08_final.stac-item
2023-09-24 09:53:25	ga_ls9c_ard_3-2-1_096074_2023-09-24_final.stac-item
2023-10-10 09:53:32	ga_ls9c_ard_3-2-1_096074_2023-10-10_final.stac-item
2023-10-26 09:53:36	ga_ls9c_ard_3-2-1_096074_2023-10-26_final.stac-item
2023-11-11 09:53:34	ga_ls9c_ard_3-2-1_096074_2023-11-11_final.stac-item
2023-11-27 09:53:42	ga_ls9c_ard_3-2-1_096074_2023-11-27_final.stac-item
2023-12-13 09:53:40	ga_ls9c_ard_3-2-1_096074_2023-12-13_final.stac-item
2023-12-29 09:53:42	ga_ls9c_ard_3-2-1_096074_2023-12-29_final.stac-item
2024-01-14 09:53:40	ga_ls9c_ard_3-2-1_096074_2024-01-14_final.stac-item
2024-01-30 09:53:40	ga_ls9c_ard_3-2-1_096074_2024-01-30_final.stac-item
2024-02-15 09:53:38	ga_ls9c_ard_3-2-1_096074_2024-02-15_final.stac-item
2024-03-02 09:53:33	ga_ls9c_ard_3-2-1_096074_2024-03-02_final.stac-item
2024-03-18 09:53:32	ga_ls9c_ard_3-2-1_096074_2024-03-18_final.stac-item
2024-04-03 09:53:23	ga_ls9c_ard_3-2-1_096074_2024-04-03_final.stac-item
2024-04-19 09:53:11	ga_ls9c_ard_3-2-1_096074_2024-04-19_final.stac-item
2024-05-05 09:52:59	ga_ls9c_ard_3-2-1_096074_2024-05-05_final.stac-item
2024-05-21 09:52:51	ga_ls9c_ard_3-2-1_096074_2024-05-21_final.stac-item
2024-06-06 09:52:44	ga_ls9c_ard_3-2-1_096074_2024-06-06_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