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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

53 results

Time (local)	Label
2021-11-12 10:56:13	ga_ls9c_ard_3-2-1_106069_2021-11-12_final.stac-item
2022-01-13 10:10:57	ga_ls9c_ard_3-2-1_099071_2022-01-13_final.stac-item
2022-01-17 09:47:03	ga_ls9c_ard_3-2-1_095073_2022-01-17_final.stac-item
2022-02-08 09:11:34	ga_ls9c_ard_3-2-1_089077_2022-02-07_final.stac-item
2022-04-06 09:06:16	ga_ls9c_ard_3-2-1_088080_2022-04-05_final.stac-item
2022-04-20 09:16:52	ga_ls9c_ard_3-2-1_090076_2022-04-19_final.stac-item
2022-05-03 10:25:36	ga_ls9c_ard_3-2-1_101078_2022-05-03_final.stac-item
2022-06-02 10:38:10	ga_ls9c_ard_3-2-1_103079_2022-06-02_final.stac-item
2022-07-07 09:33:42	ga_ls9c_ard_3-2-1_092087_2022-07-07_final.stac-item
2022-07-09 10:55:25	ga_ls9c_ard_3-2-1_106075_2022-07-09_final.stac-item
2022-07-18 09:13:10	ga_ls9c_ard_3-2-1_089082_2022-07-17_final.stac-item
2022-07-27 09:07:32	ga_ls9c_ard_3-2-1_088083_2022-07-26_final.stac-item
2022-08-07 10:25:37	ga_ls9c_ard_3-2-1_101077_2022-08-07_final.stac-item
2022-08-17 09:28:16	ga_ls9c_ard_3-2-1_091088_2022-08-16_final.stac-item
2022-09-07 09:40:03	ga_ls9c_ard_3-2-1_094071_2022-09-07_final.stac-item
2022-09-16 11:14:01	ga_ls9c_ard_3-2-1_109074_2022-09-16_final.stac-item
2022-10-02 11:12:05	ga_ls9c_ard_3-2-1_109069_2022-10-02_final.stac-item
2022-11-23 09:12:35	ga_ls9c_ard_3-2-1_089079_2022-11-22_final.stac-item
2022-11-26 11:19:33	ga_ls9c_ard_3-2-1_110072_2022-11-26_final.stac-item
2022-11-28 09:28:18	ga_ls9c_ard_3-2-1_092072_2022-11-27_final.stac-item
2022-12-17 09:58:00	ga_ls9c_ard_3-2-1_097069_2022-12-17_final.stac-item
2022-12-22 10:18:06	ga_ls9c_ard_3-2-1_100073_2022-12-22_final.stac-item
2023-02-01 10:10:24	ga_ls9c_ard_3-2-1_099069_2023-02-01_final.stac-item
2023-02-10 10:03:28	ga_ls9c_ard_3-2-1_098067_2023-02-10_final.stac-item
2023-02-21 11:24:02	ga_ls9c_ard_3-2-1_111068_2023-02-21_final.stac-item
2023-03-05 10:09:21	ga_ls9c_ard_3-2-1_099067_2023-03-05_final.stac-item
2023-03-16 11:32:25	ga_ls9c_ard_3-2-1_112074_2023-03-16_final.stac-item
2023-03-25 09:46:27	ga_ls9c_ard_3-2-1_095072_2023-03-25_final.stac-item
2023-04-01 11:31:25	ga_ls9c_ard_3-2-1_112072_2023-04-01_final.stac-item
2023-04-17 09:58:01	ga_ls9c_ard_3-2-1_096086_2023-04-17_final.stac-item
2023-04-26 11:24:41	ga_ls9c_ard_3-2-1_111071_2023-04-26_final.stac-item
2023-05-17 10:09:19	ga_ls9c_ard_3-2-1_098084_2023-05-17_final.stac-item
2023-05-24 10:09:01	ga_ls9c_ard_3-2-1_099068_2023-05-24_final.stac-item
2023-06-06 09:45:39	ga_ls9c_ard_3-2-1_094087_2023-06-06_final.stac-item
2023-06-22 09:39:09	ga_ls9c_ard_3-2-1_094071_2023-06-22_final.stac-item
2023-09-09 10:39:28	ga_ls9c_ard_3-2-1_103081_2023-09-09_final.stac-item
2023-10-09 09:11:27	ga_ls9c_ard_3-2-1_089077_2023-10-08_final.stac-item
2023-10-12 11:18:06	ga_ls9c_ard_3-2-1_110069_2023-10-12_final.stac-item
2023-10-25 09:10:45	ga_ls9c_ard_3-2-1_089075_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
2023-11-20 11:26:20	ga_ls9c_ard_3-2-1_111074_2023-11-20_final.stac-item
2023-12-02 10:11:01	ga_ls9c_ard_3-2-1_099071_2023-12-02_final.stac-item
2023-12-02 10:14:13	ga_ls9c_ard_3-2-1_099079_2023-12-02_final.stac-item
2023-12-28 09:16:26	ga_ls9c_ard_3-2-1_089089_2023-12-27_final.stac-item
2024-01-07 09:52:13	ga_ls9c_ard_3-2-1_095086_2024-01-07_final.stac-item
2024-01-27 09:23:31	ga_ls9c_ard_3-2-1_091076_2024-01-26_final.stac-item
2024-02-06 09:57:05	ga_ls9c_ard_3-2-1_097067_2024-02-06_final.stac-item
2024-02-12 09:27:57	ga_ls9c_ard_3-2-1_091087_2024-02-11_final.stac-item
2024-02-13 10:05:13	ga_ls9c_ard_3-2-1_098072_2024-02-13_final.stac-item
2024-03-08 10:52:58	ga_ls9c_ard_3-2-1_106068_2024-03-08_final.stac-item
2024-03-10 09:07:19	ga_ls9c_ard_3-2-1_088082_2024-03-09_final.stac-item
2024-04-08 10:09:54	ga_ls9c_ard_3-2-1_099069_2024-04-08_final.stac-item
2024-05-03 10:02:57	ga_ls9c_ard_3-2-1_098068_2024-05-03_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