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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

50 results

Time (local)	Label
2022-02-25 09:52:40	ga_ls9c_ard_3-2-1_096072_2022-02-25_final.stac-item
2022-04-02 11:08:17	ga_ls9c_ard_3-2-1_108076_2022-04-02_final.stac-item
2022-04-30 11:33:12	ga_ls9c_ard_3-2-1_112077_2022-04-30_final.stac-item
2022-07-03 11:33:20	ga_ls9c_ard_3-2-1_112077_2022-07-03_final.stac-item
2022-07-12 09:48:13	ga_ls9c_ard_3-2-1_095077_2022-07-12_final.stac-item
2022-07-19 11:33:20	ga_ls9c_ard_3-2-1_112077_2022-07-19_final.stac-item
2022-07-28 09:48:25	ga_ls9c_ard_3-2-1_095077_2022-07-28_final.stac-item
2022-08-13 09:48:35	ga_ls9c_ard_3-2-1_095077_2022-08-13_final.stac-item
2022-08-20 11:33:17	ga_ls9c_ard_3-2-1_112076_2022-08-20_final.stac-item
2022-08-24 11:09:22	ga_ls9c_ard_3-2-1_108078_2022-08-24_final.stac-item
2022-09-21 11:33:48	ga_ls9c_ard_3-2-1_112077_2022-09-21_final.stac-item
2022-09-27 09:20:15	ga_ls9c_ard_3-2-1_090083_2022-09-26_final.stac-item
2022-10-09 11:18:41	ga_ls9c_ard_3-2-1_110070_2022-10-09_final.stac-item
2022-10-13 09:20:19	ga_ls9c_ard_3-2-1_090083_2022-10-12_final.stac-item
2022-12-05 09:39:40	ga_ls9c_ard_3-2-1_093085_2022-12-05_final.stac-item
2022-12-12 11:21:33	ga_ls9c_ard_3-2-1_110077_2022-12-12_final.stac-item
2023-01-04 11:24:09	ga_ls9c_ard_3-2-1_111068_2023-01-04_final.stac-item
2023-02-08 10:19:25	ga_ls9c_ard_3-2-1_100076_2023-02-08_final.stac-item
2023-04-10 09:48:42	ga_ls9c_ard_3-2-1_095078_2023-04-10_final.stac-item
2023-05-03 11:33:08	ga_ls9c_ard_3-2-1_112077_2023-05-03_final.stac-item
2023-05-19 11:33:02	ga_ls9c_ard_3-2-1_112077_2023-05-19_final.stac-item
2023-05-19 11:33:50	ga_ls9c_ard_3-2-1_112079_2023-05-19_final.stac-item
2023-05-28 09:47:52	ga_ls9c_ard_3-2-1_095077_2023-05-28_final.stac-item
2023-05-28 09:48:16	ga_ls9c_ard_3-2-1_095078_2023-05-28_final.stac-item
2023-06-04 11:32:55	ga_ls9c_ard_3-2-1_112077_2023-06-04_final.stac-item
2023-06-08 09:31:16	ga_ls9c_ard_3-2-1_092082_2023-06-08_final.stac-item
2023-06-13 09:47:45	ga_ls9c_ard_3-2-1_095077_2023-06-13_final.stac-item
2023-06-20 11:33:35	ga_ls9c_ard_3-2-1_112079_2023-06-20_final.stac-item
2023-07-10 11:08:43	ga_ls9c_ard_3-2-1_108078_2023-07-10_final.stac-item
2023-07-15 09:48:00	ga_ls9c_ard_3-2-1_095077_2023-07-15_final.stac-item
2023-07-15 09:48:24	ga_ls9c_ard_3-2-1_095078_2023-07-15_final.stac-item
2023-07-22 11:33:03	ga_ls9c_ard_3-2-1_112077_2023-07-22_final.stac-item
2023-07-26 11:08:44	ga_ls9c_ard_3-2-1_108078_2023-07-26_final.stac-item
2023-07-31 09:48:05	ga_ls9c_ard_3-2-1_095077_2023-07-31_final.stac-item
2023-07-31 09:48:29	ga_ls9c_ard_3-2-1_095078_2023-07-31_final.stac-item
2023-08-11 11:08:55	ga_ls9c_ard_3-2-1_108078_2023-08-11_final.stac-item
2023-08-23 11:33:19	ga_ls9c_ard_3-2-1_112077_2023-08-23_final.stac-item
2023-08-27 11:09:03	ga_ls9c_ard_3-2-1_108078_2023-08-27_final.stac-item
2023-09-01 09:48:21	ga_ls9c_ard_3-2-1_095077_2023-09-01_final.stac-item
2023-09-01 09:48:45	ga_ls9c_ard_3-2-1_095078_2023-09-01_final.stac-item
2023-09-17 09:48:53	ga_ls9c_ard_3-2-1_095078_2023-09-17_final.stac-item
2023-09-24 11:33:30	ga_ls9c_ard_3-2-1_112077_2023-09-24_final.stac-item
2023-09-28 11:09:08	ga_ls9c_ard_3-2-1_108078_2023-09-28_final.stac-item
2023-11-30 10:26:59	ga_ls9c_ard_3-2-1_101080_2023-11-30_final.stac-item
2024-02-05 09:20:12	ga_ls9c_ard_3-2-1_090083_2024-02-04_final.stac-item
2024-02-19 11:09:18	ga_ls9c_ard_3-2-1_108078_2024-02-19_final.stac-item
2024-03-01 10:48:22	ga_ls9c_ard_3-2-1_105072_2024-03-01_final.stac-item
2024-03-10 10:43:48	ga_ls9c_ard_3-2-1_104076_2024-03-10_final.stac-item
2024-04-28 11:27:18	ga_ls9c_ard_3-2-1_111078_2024-04-28_final.stac-item
2024-05-05 11:33:52	ga_ls9c_ard_3-2-1_112079_2024-05-05_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