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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

43 results

Time (local)	Label
2021-11-03 11:32:26	ga_ls9c_ard_3-2-1_112072_2021-11-03_final.stac-item
2021-11-17 09:25:16	ga_ls9c_ard_3-2-1_091082_2021-11-16_final.stac-item
2021-12-06 10:52:35	ga_ls9c_ard_3-2-1_105082_2021-12-06_final.stac-item
2022-01-19 09:40:41	ga_ls9c_ard_3-2-1_093088_2022-01-19_final.stac-item
2022-02-13 09:31:16	ga_ls9c_ard_3-2-1_092080_2022-02-13_final.stac-item
2022-02-21 11:58:43	ga_ls9c_ard_3-2-1_116078_2022-02-21_final.stac-item
2022-03-24 11:14:29	ga_ls9c_ard_3-2-1_109076_2022-03-24_final.stac-item
2022-04-04 09:21:50	ga_ls9c_ard_3-2-1_090088_2022-04-03_final.stac-item
2022-05-17 10:35:24	ga_ls9c_ard_3-2-1_103072_2022-05-17_final.stac-item
2022-05-28 10:19:12	ga_ls9c_ard_3-2-1_100078_2022-05-28_final.stac-item
2022-06-21 09:33:37	ga_ls9c_ard_3-2-1_092087_2022-06-21_final.stac-item
2022-07-14 11:13:55	ga_ls9c_ard_3-2-1_109075_2022-07-14_final.stac-item
2022-07-17 10:09:58	ga_ls9c_ard_3-2-1_098085_2022-07-17_final.stac-item
2022-08-27 10:02:11	ga_ls9c_ard_3-2-1_097080_2022-08-27_final.stac-item
2022-09-03 10:03:11	ga_ls9c_ard_3-2-1_098067_2022-09-03_final.stac-item
2022-09-07 11:22:55	ga_ls9c_ard_3-2-1_110081_2022-09-07_final.stac-item
2022-09-14 11:29:10	ga_ls9c_ard_3-2-1_111081_2022-09-14_final.stac-item
2022-11-02 10:29:41	ga_ls9c_ard_3-2-1_102071_2022-11-02_final.stac-item
2022-11-20 10:19:22	ga_ls9c_ard_3-2-1_100076_2022-11-20_final.stac-item
2023-01-26 10:47:48	ga_ls9c_ard_3-2-1_105070_2023-01-26_final.stac-item
2023-02-11 09:11:49	ga_ls9c_ard_3-2-1_089077_2023-02-10_final.stac-item
2023-02-20 09:07:30	ga_ls9c_ard_3-2-1_088082_2023-02-19_final.stac-item
2023-02-21 11:24:02	ga_ls9c_ard_3-2-1_111068_2023-02-21_final.stac-item
2023-03-31 09:12:04	ga_ls9c_ard_3-2-1_089079_2023-03-30_final.stac-item
2023-04-16 09:10:22	ga_ls9c_ard_3-2-1_089075_2023-04-15_final.stac-item
2023-06-29 11:24:18	ga_ls9c_ard_3-2-1_111071_2023-06-29_final.stac-item
2023-07-04 10:06:03	ga_ls9c_ard_3-2-1_098076_2023-07-04_final.stac-item
2023-08-02 11:14:38	ga_ls9c_ard_3-2-1_109077_2023-08-02_final.stac-item
2023-08-27 11:11:02	ga_ls9c_ard_3-2-1_108083_2023-08-27_final.stac-item
2023-09-21 09:22:57	ga_ls9c_ard_3-2-1_091075_2023-09-20_final.stac-item
2023-09-25 10:39:52	ga_ls9c_ard_3-2-1_103082_2023-09-25_final.stac-item
2023-10-20 10:30:19	ga_ls9c_ard_3-2-1_102073_2023-10-20_final.stac-item
2023-10-23 11:02:00	ga_ls9c_ard_3-2-1_107075_2023-10-23_final.stac-item
2023-11-07 11:58:45	ga_ls9c_ard_3-2-1_116078_2023-11-07_final.stac-item
2023-11-29 11:20:13	ga_ls9c_ard_3-2-1_110074_2023-11-29_final.stac-item
2023-12-02 10:13:25	ga_ls9c_ard_3-2-1_099077_2023-12-02_final.stac-item
2023-12-19 09:22:13	ga_ls9c_ard_3-2-1_090088_2023-12-18_final.stac-item
2024-01-13 09:12:48	ga_ls9c_ard_3-2-1_089080_2024-01-12_final.stac-item
2024-03-29 09:39:14	ga_ls9c_ard_3-2-1_093085_2024-03-29_final.stac-item
2024-04-02 09:11:20	ga_ls9c_ard_3-2-1_089077_2024-04-01_final.stac-item
2024-04-27 09:06:46	ga_ls9c_ard_3-2-1_088082_2024-04-26_final.stac-item
2024-04-28 11:24:55	ga_ls9c_ard_3-2-1_111072_2024-04-28_final.stac-item
2024-05-27 10:52:11	ga_ls9c_ard_3-2-1_106068_2024-05-27_nrt.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