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
2021-12-06 10:49:24	ga_ls9c_ard_3-2-1_105074_2021-12-06_final.stac-item
2021-12-22 10:49:17	ga_ls9c_ard_3-2-1_105074_2021-12-22_final.stac-item
2022-01-07 10:49:16	ga_ls9c_ard_3-2-1_105074_2022-01-07_final.stac-item
2022-01-23 10:49:16	ga_ls9c_ard_3-2-1_105074_2022-01-23_final.stac-item
2022-02-08 10:49:15	ga_ls9c_ard_3-2-1_105074_2022-02-08_final.stac-item
2022-02-24 10:49:06	ga_ls9c_ard_3-2-1_105074_2022-02-24_final.stac-item
2022-03-12 10:49:02	ga_ls9c_ard_3-2-1_105074_2022-03-12_final.stac-item
2022-03-28 10:48:57	ga_ls9c_ard_3-2-1_105074_2022-03-28_final.stac-item
2022-04-13 10:48:52	ga_ls9c_ard_3-2-1_105074_2022-04-13_final.stac-item
2022-04-29 10:48:45	ga_ls9c_ard_3-2-1_105074_2022-04-29_final.stac-item
2022-05-15 10:48:36	ga_ls9c_ard_3-2-1_105074_2022-05-15_final.stac-item
2022-05-31 10:48:32	ga_ls9c_ard_3-2-1_105074_2022-05-31_final.stac-item
2022-06-16 10:48:38	ga_ls9c_ard_3-2-1_105074_2022-06-16_final.stac-item
2022-07-02 10:48:52	ga_ls9c_ard_3-2-1_105074_2022-07-02_final.stac-item
2022-07-18 10:48:52	ga_ls9c_ard_3-2-1_105074_2022-07-18_final.stac-item
2022-08-03 10:49:05	ga_ls9c_ard_3-2-1_105074_2022-08-03_final.stac-item
2022-08-19 10:49:13	ga_ls9c_ard_3-2-1_105074_2022-08-19_final.stac-item
2022-09-04 10:49:14	ga_ls9c_ard_3-2-1_105074_2022-09-04_final.stac-item
2022-09-20 10:49:20	ga_ls9c_ard_3-2-1_105074_2022-09-20_final.stac-item
2022-10-06 10:49:21	ga_ls9c_ard_3-2-1_105074_2022-10-06_final.stac-item
2022-10-22 10:49:28	ga_ls9c_ard_3-2-1_105074_2022-10-22_final.stac-item
2022-11-07 10:49:26	ga_ls9c_ard_3-2-1_105074_2022-11-07_final.stac-item
2022-11-23 10:49:28	ga_ls9c_ard_3-2-1_105074_2022-11-23_final.stac-item
2022-12-09 10:49:27	ga_ls9c_ard_3-2-1_105074_2022-12-09_final.stac-item
2022-12-25 10:49:24	ga_ls9c_ard_3-2-1_105074_2022-12-25_final.stac-item
2023-01-10 10:49:26	ga_ls9c_ard_3-2-1_105074_2023-01-10_final.stac-item
2023-01-26 10:49:23	ga_ls9c_ard_3-2-1_105074_2023-01-26_final.stac-item
2023-02-11 10:49:30	ga_ls9c_ard_3-2-1_105074_2023-02-11_final.stac-item
2023-02-27 10:49:16	ga_ls9c_ard_3-2-1_105074_2023-02-27_final.stac-item
2023-03-15 10:49:09	ga_ls9c_ard_3-2-1_105074_2023-03-15_final.stac-item
2023-03-31 10:48:57	ga_ls9c_ard_3-2-1_105074_2023-03-31_final.stac-item
2023-04-16 10:48:51	ga_ls9c_ard_3-2-1_105074_2023-04-16_final.stac-item
2023-05-02 10:48:42	ga_ls9c_ard_3-2-1_105074_2023-05-02_final.stac-item
2023-05-18 10:48:35	ga_ls9c_ard_3-2-1_105074_2023-05-18_final.stac-item
2023-06-03 10:48:28	ga_ls9c_ard_3-2-1_105074_2023-06-03_final.stac-item
2023-06-19 10:48:20	ga_ls9c_ard_3-2-1_105074_2023-06-19_final.stac-item
2023-07-05 10:48:32	ga_ls9c_ard_3-2-1_105074_2023-07-05_final.stac-item
2023-07-21 10:48:36	ga_ls9c_ard_3-2-1_105074_2023-07-21_final.stac-item
2023-08-06 10:48:45	ga_ls9c_ard_3-2-1_105074_2023-08-06_final.stac-item
2023-08-22 10:48:50	ga_ls9c_ard_3-2-1_105074_2023-08-22_final.stac-item
2023-09-07 10:49:01	ga_ls9c_ard_3-2-1_105074_2023-09-07_final.stac-item
2023-09-23 10:49:03	ga_ls9c_ard_3-2-1_105074_2023-09-23_final.stac-item
2023-10-09 10:49:09	ga_ls9c_ard_3-2-1_105074_2023-10-09_final.stac-item
2023-10-25 10:49:14	ga_ls9c_ard_3-2-1_105074_2023-10-25_final.stac-item
2023-11-10 10:49:11	ga_ls9c_ard_3-2-1_105074_2023-11-10_final.stac-item
2023-11-26 10:49:19	ga_ls9c_ard_3-2-1_105074_2023-11-26_final.stac-item
2023-12-12 10:49:17	ga_ls9c_ard_3-2-1_105074_2023-12-12_final.stac-item
2023-12-28 10:49:20	ga_ls9c_ard_3-2-1_105074_2023-12-28_final.stac-item
2024-01-13 10:49:17	ga_ls9c_ard_3-2-1_105074_2024-01-13_final.stac-item
2024-01-29 10:49:16	ga_ls9c_ard_3-2-1_105074_2024-01-29_final.stac-item
2024-02-14 10:49:16	ga_ls9c_ard_3-2-1_105074_2024-02-14_final.stac-item
2024-03-01 10:49:10	ga_ls9c_ard_3-2-1_105074_2024-03-01_final.stac-item
2024-03-17 10:49:10	ga_ls9c_ard_3-2-1_105074_2024-03-17_final.stac-item
2024-04-02 10:49:01	ga_ls9c_ard_3-2-1_105074_2024-04-02_final.stac-item
2024-04-18 10:48:50	ga_ls9c_ard_3-2-1_105074_2024-04-18_final.stac-item
2024-05-04 10:48:36	ga_ls9c_ard_3-2-1_105074_2024-05-04_final.stac-item
2024-05-20 10:48:28	ga_ls9c_ard_3-2-1_105074_2024-05-20_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