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

40 results

Time (local)	Label
2021-12-12 10:09:51	ga_ls9c_ard_3-2-1_099068_2021-12-12_final.stac-item
2022-01-01 09:52:40	ga_ls9c_ard_3-2-1_095087_2022-01-01_final.stac-item
2022-01-05 09:22:45	ga_ls9c_ard_3-2-1_091074_2022-01-04_final.stac-item
2022-01-21 09:23:56	ga_ls9c_ard_3-2-1_091077_2022-01-20_final.stac-item
2022-02-27 11:19:10	ga_ls9c_ard_3-2-1_110072_2022-02-27_final.stac-item
2022-03-02 10:09:09	ga_ls9c_ard_3-2-1_099067_2022-03-02_final.stac-item
2022-04-11 09:22:22	ga_ls9c_ard_3-2-1_091074_2022-04-10_final.stac-item
2022-04-15 10:34:06	ga_ls9c_ard_3-2-1_103068_2022-04-15_final.stac-item
2022-04-19 10:13:19	ga_ls9c_ard_3-2-1_099078_2022-04-19_final.stac-item
2022-06-14 09:27:40	ga_ls9c_ard_3-2-1_091088_2022-06-13_final.stac-item
2022-06-23 10:55:25	ga_ls9c_ard_3-2-1_106075_2022-06-23_final.stac-item
2022-08-06 11:20:02	ga_ls9c_ard_3-2-1_110074_2022-08-06_final.stac-item
2022-08-15 09:34:38	ga_ls9c_ard_3-2-1_093073_2022-08-15_final.stac-item
2022-09-02 09:29:06	ga_ls9c_ard_3-2-1_091090_2022-09-01_final.stac-item
2022-09-23 11:18:15	ga_ls9c_ard_3-2-1_110069_2022-09-23_final.stac-item
2022-11-07 09:16:32	ga_ls9c_ard_3-2-1_089089_2022-11-06_final.stac-item
2022-11-23 10:49:28	ga_ls9c_ard_3-2-1_105074_2022-11-23_final.stac-item
2022-12-07 09:22:31	ga_ls9c_ard_3-2-1_091073_2022-12-06_nrt.stac-item
2022-12-20 10:28:29	ga_ls9c_ard_3-2-1_102068_2022-12-20_final.stac-item
2022-12-25 10:50:12	ga_ls9c_ard_3-2-1_105076_2022-12-25_final.stac-item
2023-01-10 09:10:57	ga_ls9c_ard_3-2-1_089075_2023-01-09_final.stac-item
2023-03-06 09:17:18	ga_ls9c_ard_3-2-1_090076_2023-03-05_final.stac-item
2023-03-08 09:07:42	ga_ls9c_ard_3-2-1_088083_2023-03-07_final.stac-item
2023-04-26 11:23:54	ga_ls9c_ard_3-2-1_111069_2023-04-26_final.stac-item
2023-05-16 09:22:05	ga_ls9c_ard_3-2-1_091074_2023-05-15_final.stac-item
2023-05-30 11:16:47	ga_ls9c_ard_3-2-1_109083_2023-05-30_final.stac-item
2023-08-09 09:39:35	ga_ls9c_ard_3-2-1_094071_2023-08-09_final.stac-item
2023-08-16 11:23:51	ga_ls9c_ard_3-2-1_111069_2023-08-16_final.stac-item
2023-09-04 10:19:16	ga_ls9c_ard_3-2-1_100077_2023-09-04_final.stac-item
2023-09-05 09:21:40	ga_ls9c_ard_3-2-1_091072_2023-09-04_final.stac-item
2023-09-13 10:13:35	ga_ls9c_ard_3-2-1_099078_2023-09-13_final.stac-item
2023-10-07 09:23:00	ga_ls9c_ard_3-2-1_091075_2023-10-06_final.stac-item
2023-11-10 09:10:42	ga_ls9c_ard_3-2-1_089075_2023-11-09_final.stac-item
2023-11-27 09:58:29	ga_ls9c_ard_3-2-1_096086_2023-11-27_final.stac-item
2023-12-08 11:14:21	ga_ls9c_ard_3-2-1_109075_2023-12-08_final.stac-item
2024-01-03 10:13:47	ga_ls9c_ard_3-2-1_099078_2024-01-03_final.stac-item
2024-02-15 11:31:43	ga_ls9c_ard_3-2-1_112072_2024-02-15_final.stac-item
2024-03-13 09:33:48	ga_ls9c_ard_3-2-1_093071_2024-03-13_final.stac-item
2024-04-09 10:55:57	ga_ls9c_ard_3-2-1_106076_2024-04-09_final.stac-item
2024-04-16 09:22:21	ga_ls9c_ard_3-2-1_091074_2024-04-15_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