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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

45 results

Time (local)	Label
2022-01-13 10:09:22	ga_ls9c_ard_3-2-1_099067_2022-01-13_final.stac-item
2022-01-23 10:47:17	ga_ls9c_ard_3-2-1_105069_2022-01-23_final.stac-item
2022-02-16 11:37:50	ga_ls9c_ard_3-2-1_113072_2022-02-16_final.stac-item
2022-03-02 11:53:13	ga_ls9c_ard_3-2-1_115080_2022-03-02_final.stac-item
2022-03-12 10:52:37	ga_ls9c_ard_3-2-1_105083_2022-03-12_final.stac-item
2022-04-04 10:55:31	ga_ls9c_ard_3-2-1_106075_2022-04-04_final.stac-item
2022-04-21 09:56:32	ga_ls9c_ard_3-2-1_097067_2022-04-21_final.stac-item
2022-06-15 10:03:22	ga_ls9c_ard_3-2-1_098069_2022-06-15_final.stac-item
2022-06-22 11:53:00	ga_ls9c_ard_3-2-1_115080_2022-06-22_final.stac-item
2022-07-07 09:33:18	ga_ls9c_ard_3-2-1_092086_2022-07-07_final.stac-item
2022-08-16 10:19:54	ga_ls9c_ard_3-2-1_100078_2022-08-16_final.stac-item
2022-08-27 09:57:48	ga_ls9c_ard_3-2-1_097069_2022-08-27_final.stac-item
2022-09-05 11:32:06	ga_ls9c_ard_3-2-1_112073_2022-09-05_final.stac-item
2022-11-03 09:34:03	ga_ls9c_ard_3-2-1_093071_2022-11-03_final.stac-item
2022-11-13 10:09:36	ga_ls9c_ard_3-2-1_099067_2022-11-13_final.stac-item
2022-11-13 10:16:47	ga_ls9c_ard_3-2-1_099085_2022-11-13_final.stac-item
2022-11-21 09:23:21	ga_ls9c_ard_3-2-1_091075_2022-11-20_final.stac-item
2022-12-06 10:19:44	ga_ls9c_ard_3-2-1_100077_2022-12-06_nrt.stac-item
2022-12-30 11:06:23	ga_ls9c_ard_3-2-1_108070_2022-12-30_final.stac-item
2023-01-13 11:18:43	ga_ls9c_ard_3-2-1_110070_2023-01-13_final.stac-item
2023-01-18 11:38:47	ga_ls9c_ard_3-2-1_113074_2023-01-18_final.stac-item
2023-02-19 09:59:57	ga_ls9c_ard_3-2-1_097074_2023-02-19_final.stac-item
2023-02-20 09:06:42	ga_ls9c_ard_3-2-1_088080_2023-02-19_final.stac-item
2023-02-25 09:22:45	ga_ls9c_ard_3-2-1_091074_2023-02-24_final.stac-item
2023-02-27 09:11:35	ga_ls9c_ard_3-2-1_089077_2023-02-26_final.stac-item
2023-03-07 11:37:50	ga_ls9c_ard_3-2-1_113072_2023-03-07_final.stac-item
2023-05-21 09:39:22	ga_ls9c_ard_3-2-1_094071_2023-05-21_final.stac-item
2023-05-28 11:24:22	ga_ls9c_ard_3-2-1_111071_2023-05-28_final.stac-item
2023-05-31 10:18:46	ga_ls9c_ard_3-2-1_100077_2023-05-31_final.stac-item
2023-06-24 09:33:58	ga_ls9c_ard_3-2-1_092089_2023-06-24_final.stac-item
2023-07-03 09:21:11	ga_ls9c_ard_3-2-1_091072_2023-07-02_final.stac-item
2023-07-18 11:58:11	ga_ls9c_ard_3-2-1_116078_2023-07-18_final.stac-item
2023-07-24 11:17:53	ga_ls9c_ard_3-2-1_110070_2023-07-24_final.stac-item
2023-08-28 10:09:50	ga_ls9c_ard_3-2-1_099069_2023-08-28_final.stac-item
2023-08-28 11:53:07	ga_ls9c_ard_3-2-1_115080_2023-08-28_final.stac-item
2023-09-15 09:56:51	ga_ls9c_ard_3-2-1_097067_2023-09-15_final.stac-item
2023-10-28 09:46:01	ga_ls9c_ard_3-2-1_094086_2023-10-28_final.stac-item
2023-10-31 10:15:41	ga_ls9c_ard_3-2-1_099083_2023-10-31_final.stac-item
2024-01-03 10:09:24	ga_ls9c_ard_3-2-1_099067_2024-01-03_final.stac-item
2024-02-04 11:53:31	ga_ls9c_ard_3-2-1_115080_2024-02-04_final.stac-item
2024-02-05 09:17:25	ga_ls9c_ard_3-2-1_090076_2024-02-04_final.stac-item
2024-02-07 09:06:39	ga_ls9c_ard_3-2-1_088080_2024-02-06_final.stac-item
2024-03-13 09:33:48	ga_ls9c_ard_3-2-1_093071_2024-03-13_final.stac-item
2024-03-23 11:53:19	ga_ls9c_ard_3-2-1_115080_2024-03-23_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years