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
2022-01-10 11:18:10	ga_ls9c_ard_3-2-1_110069_2022-01-10_final.stac-item
2022-01-13 10:10:33	ga_ls9c_ard_3-2-1_099070_2022-01-13_final.stac-item
2022-02-07 10:02:48	ga_ls9c_ard_3-2-1_098066_2022-02-07_final.stac-item
2022-03-02 10:13:32	ga_ls9c_ard_3-2-1_099078_2022-03-02_final.stac-item
2022-03-06 09:52:01	ga_ls9c_ard_3-2-1_095086_2022-03-06_final.stac-item
2022-03-27 11:44:34	ga_ls9c_ard_3-2-1_114074_2022-03-27_final.stac-item
2022-08-03 09:11:24	ga_ls9c_ard_3-2-1_089077_2022-08-02_final.stac-item
2022-08-04 11:35:33	ga_ls9c_ard_3-2-1_112082_2022-08-04_final.stac-item
2022-08-22 09:40:03	ga_ls9c_ard_3-2-1_094071_2022-08-22_final.stac-item
2022-09-25 11:06:18	ga_ls9c_ard_3-2-1_108070_2022-09-25_final.stac-item
2022-10-09 09:45:47	ga_ls9c_ard_3-2-1_094085_2022-10-09_final.stac-item
2022-10-12 11:52:49	ga_ls9c_ard_3-2-1_115078_2022-10-12_final.stac-item
2022-10-16 11:24:56	ga_ls9c_ard_3-2-1_111070_2022-10-16_final.stac-item
2022-11-09 10:39:53	ga_ls9c_ard_3-2-1_103081_2022-11-09_final.stac-item
2022-12-11 10:39:53	ga_ls9c_ard_3-2-1_103081_2022-12-11_final.stac-item
2022-12-20 10:28:29	ga_ls9c_ard_3-2-1_102068_2022-12-20_final.stac-item
2022-12-21 09:39:39	ga_ls9c_ard_3-2-1_093085_2022-12-21_final.stac-item
2022-12-24 10:04:56	ga_ls9c_ard_3-2-1_098071_2022-12-24_final.stac-item
2023-02-05 11:24:59	ga_ls9c_ard_3-2-1_111070_2023-02-05_final.stac-item
2023-02-26 10:06:01	ga_ls9c_ard_3-2-1_098074_2023-02-26_final.stac-item
2023-03-31 10:46:34	ga_ls9c_ard_3-2-1_105068_2023-03-31_final.stac-item
2023-04-01 09:57:20	ga_ls9c_ard_3-2-1_096084_2023-04-01_final.stac-item
2023-04-11 10:33:33	ga_ls9c_ard_3-2-1_102082_2023-04-11_final.stac-item
2023-04-24 10:01:23	ga_ls9c_ard_3-2-1_097079_2023-04-24_final.stac-item
2023-05-24 10:09:01	ga_ls9c_ard_3-2-1_099068_2023-05-24_final.stac-item
2023-06-18 11:46:45	ga_ls9c_ard_3-2-1_114081_2023-06-18_final.stac-item
2023-07-05 10:48:32	ga_ls9c_ard_3-2-1_105074_2023-07-05_final.stac-item
2023-10-19 11:24:44	ga_ls9c_ard_3-2-1_111070_2023-10-19_final.stac-item
2023-10-25 09:11:57	ga_ls9c_ard_3-2-1_089078_2023-10-24_final.stac-item
2023-10-25 10:49:14	ga_ls9c_ard_3-2-1_105074_2023-10-25_final.stac-item
2023-11-25 10:10:02	ga_ls9c_ard_3-2-1_098084_2023-11-25_final.stac-item
2023-11-26 09:12:49	ga_ls9c_ard_3-2-1_089080_2023-11-25_final.stac-item
2023-12-23 10:33:36	ga_ls9c_ard_3-2-1_102081_2023-12-23_final.stac-item
2023-12-26 09:24:01	ga_ls9c_ard_3-2-1_091077_2023-12-25_final.stac-item
2024-01-16 11:20:11	ga_ls9c_ard_3-2-1_110074_2024-01-16_final.stac-item
2024-01-20 09:16:57	ga_ls9c_ard_3-2-1_090075_2024-01-19_final.stac-item
2024-02-03 11:05:51	ga_ls9c_ard_3-2-1_108069_2024-02-03_final.stac-item
2024-02-12 11:00:27	ga_ls9c_ard_3-2-1_107071_2024-02-12_final.stac-item
2024-03-18 11:32:25	ga_ls9c_ard_3-2-1_112074_2024-03-18_final.stac-item
2024-04-18 10:52:01	ga_ls9c_ard_3-2-1_105082_2024-04-18_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