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

58 results

Time (local)	Label
2021-11-04 10:37:19	ga_ls9c_ard_3-2-1_103081_2021-11-04_final.stac-item
2021-11-09 10:39:47	ga_ls9c_ard_3-2-1_103081_2021-11-09_final.stac-item
2021-11-14 10:42:15	ga_ls9c_ard_3-2-1_103081_2021-11-14_final.stac-item
2021-12-08 10:39:48	ga_ls9c_ard_3-2-1_103081_2021-12-08_final.stac-item
2021-12-24 10:39:44	ga_ls9c_ard_3-2-1_103081_2021-12-24_final.stac-item
2022-01-09 10:39:41	ga_ls9c_ard_3-2-1_103081_2022-01-09_final.stac-item
2022-01-25 10:39:43	ga_ls9c_ard_3-2-1_103081_2022-01-25_final.stac-item
2022-02-10 10:39:41	ga_ls9c_ard_3-2-1_103081_2022-02-10_final.stac-item
2022-02-26 10:39:30	ga_ls9c_ard_3-2-1_103081_2022-02-26_final.stac-item
2022-03-30 10:39:23	ga_ls9c_ard_3-2-1_103081_2022-03-30_final.stac-item
2022-04-15 10:39:17	ga_ls9c_ard_3-2-1_103081_2022-04-15_final.stac-item
2022-05-01 10:39:11	ga_ls9c_ard_3-2-1_103081_2022-05-01_final.stac-item
2022-05-17 10:39:00	ga_ls9c_ard_3-2-1_103081_2022-05-17_final.stac-item
2022-06-02 10:38:58	ga_ls9c_ard_3-2-1_103081_2022-06-02_final.stac-item
2022-06-18 10:39:06	ga_ls9c_ard_3-2-1_103081_2022-06-18_final.stac-item
2022-07-04 10:39:18	ga_ls9c_ard_3-2-1_103081_2022-07-04_final.stac-item
2022-07-20 10:39:20	ga_ls9c_ard_3-2-1_103081_2022-07-20_final.stac-item
2022-08-05 10:39:33	ga_ls9c_ard_3-2-1_103081_2022-08-05_final.stac-item
2022-08-21 10:39:40	ga_ls9c_ard_3-2-1_103081_2022-08-21_final.stac-item
2022-09-06 10:39:40	ga_ls9c_ard_3-2-1_103081_2022-09-06_final.stac-item
2022-09-22 10:39:47	ga_ls9c_ard_3-2-1_103081_2022-09-22_final.stac-item
2022-10-08 10:39:48	ga_ls9c_ard_3-2-1_103081_2022-10-08_final.stac-item
2022-10-24 10:39:54	ga_ls9c_ard_3-2-1_103081_2022-10-24_final.stac-item
2022-11-09 10:39:53	ga_ls9c_ard_3-2-1_103081_2022-11-09_final.stac-item
2022-11-25 10:39:53	ga_ls9c_ard_3-2-1_103081_2022-11-25_final.stac-item
2022-12-11 10:39:53	ga_ls9c_ard_3-2-1_103081_2022-12-11_final.stac-item
2022-12-27 10:39:51	ga_ls9c_ard_3-2-1_103081_2022-12-27_final.stac-item
2023-01-12 10:39:51	ga_ls9c_ard_3-2-1_103081_2023-01-12_final.stac-item
2023-01-28 10:39:51	ga_ls9c_ard_3-2-1_103081_2023-01-28_final.stac-item
2023-02-13 10:39:55	ga_ls9c_ard_3-2-1_103081_2023-02-13_final.stac-item
2023-03-01 10:39:42	ga_ls9c_ard_3-2-1_103081_2023-03-01_final.stac-item
2023-03-17 10:39:35	ga_ls9c_ard_3-2-1_103081_2023-03-17_final.stac-item
2023-04-02 10:39:24	ga_ls9c_ard_3-2-1_103081_2023-04-02_final.stac-item
2023-04-18 10:39:17	ga_ls9c_ard_3-2-1_103081_2023-04-18_final.stac-item
2023-05-04 10:39:05	ga_ls9c_ard_3-2-1_103081_2023-05-04_final.stac-item
2023-05-20 10:38:59	ga_ls9c_ard_3-2-1_103081_2023-05-20_final.stac-item
2023-06-05 10:38:53	ga_ls9c_ard_3-2-1_103081_2023-06-05_final.stac-item
2023-06-21 10:38:46	ga_ls9c_ard_3-2-1_103081_2023-06-21_final.stac-item
2023-07-07 10:38:59	ga_ls9c_ard_3-2-1_103081_2023-07-07_final.stac-item
2023-07-23 10:39:01	ga_ls9c_ard_3-2-1_103081_2023-07-23_final.stac-item
2023-08-08 10:39:12	ga_ls9c_ard_3-2-1_103081_2023-08-08_final.stac-item
2023-08-24 10:39:18	ga_ls9c_ard_3-2-1_103081_2023-08-24_final.stac-item
2023-09-09 10:39:28	ga_ls9c_ard_3-2-1_103081_2023-09-09_final.stac-item
2023-09-25 10:39:28	ga_ls9c_ard_3-2-1_103081_2023-09-25_final.stac-item
2023-10-11 10:39:37	ga_ls9c_ard_3-2-1_103081_2023-10-11_final.stac-item
2023-10-27 10:39:39	ga_ls9c_ard_3-2-1_103081_2023-10-27_final.stac-item
2023-11-12 10:39:37	ga_ls9c_ard_3-2-1_103081_2023-11-12_final.stac-item
2023-11-28 10:39:45	ga_ls9c_ard_3-2-1_103081_2023-11-28_final.stac-item
2023-12-14 10:39:44	ga_ls9c_ard_3-2-1_103081_2023-12-14_final.stac-item
2023-12-30 10:39:45	ga_ls9c_ard_3-2-1_103081_2023-12-30_final.stac-item
2024-01-15 10:39:43	ga_ls9c_ard_3-2-1_103081_2024-01-15_final.stac-item
2024-01-31 10:39:43	ga_ls9c_ard_3-2-1_103081_2024-01-31_final.stac-item
2024-02-16 10:39:40	ga_ls9c_ard_3-2-1_103081_2024-02-16_final.stac-item
2024-03-03 10:39:37	ga_ls9c_ard_3-2-1_103081_2024-03-03_final.stac-item
2024-03-19 10:39:35	ga_ls9c_ard_3-2-1_103081_2024-03-19_final.stac-item
2024-04-04 10:39:26	ga_ls9c_ard_3-2-1_103081_2024-04-04_final.stac-item
2024-04-20 10:39:12	ga_ls9c_ard_3-2-1_103081_2024-04-20_final.stac-item
2024-05-06 10:39:02	ga_ls9c_ard_3-2-1_103081_2024-05-06_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