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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

40 results

Time (local)	Label
2021-12-08 10:36:13	ga_ls9c_ard_3-2-1_103072_2021-12-08_final.stac-item
2022-01-14 09:17:44	ga_ls9c_ard_3-2-1_090077_2022-01-13_final.stac-item
2022-01-26 09:42:06	ga_ls9c_ard_3-2-1_094076_2022-01-26_final.stac-item
2022-02-01 10:41:54	ga_ls9c_ard_3-2-1_104071_2022-02-01_final.stac-item
2022-03-30 10:38:59	ga_ls9c_ard_3-2-1_103080_2022-03-30_final.stac-item
2022-04-25 09:38:35	ga_ls9c_ard_3-2-1_093084_2022-04-25_final.stac-item
2022-05-30 10:02:28	ga_ls9c_ard_3-2-1_098067_2022-05-30_final.stac-item
2022-06-14 09:28:04	ga_ls9c_ard_3-2-1_091089_2022-06-13_final.stac-item
2022-06-28 11:13:36	ga_ls9c_ard_3-2-1_109074_2022-06-28_final.stac-item
2022-07-01 10:02:49	ga_ls9c_ard_3-2-1_098067_2022-07-01_final.stac-item
2022-07-16 11:04:46	ga_ls9c_ard_3-2-1_107083_2022-07-16_final.stac-item
2022-08-08 11:05:41	ga_ls9c_ard_3-2-1_108069_2022-08-08_final.stac-item
2022-09-23 09:43:46	ga_ls9c_ard_3-2-1_094080_2022-09-23_final.stac-item
2022-10-03 10:17:40	ga_ls9c_ard_3-2-1_100072_2022-10-03_final.stac-item
2022-11-06 10:09:45	ga_ls9c_ard_3-2-1_098083_2022-11-06_final.stac-item
2022-12-08 10:03:24	ga_ls9c_ard_3-2-1_098067_2022-12-08_final.stac-item
2022-12-08 10:05:47	ga_ls9c_ard_3-2-1_098073_2022-12-08_final.stac-item
2023-01-29 09:45:27	ga_ls9c_ard_3-2-1_094084_2023-01-29_final.stac-item
2023-01-31 11:06:00	ga_ls9c_ard_3-2-1_108069_2023-01-31_final.stac-item
2023-02-17 11:51:38	ga_ls9c_ard_3-2-1_115075_2023-02-17_final.stac-item
2023-02-27 09:13:59	ga_ls9c_ard_3-2-1_089083_2023-02-26_final.stac-item
2023-04-03 11:20:40	ga_ls9c_ard_3-2-1_110076_2023-04-03_final.stac-item
2023-04-25 10:45:50	ga_ls9c_ard_3-2-1_104082_2023-04-25_final.stac-item
2023-05-06 10:27:07	ga_ls9c_ard_3-2-1_101082_2023-05-06_final.stac-item
2023-07-04 10:07:39	ga_ls9c_ard_3-2-1_098080_2023-07-04_final.stac-item
2023-07-09 10:22:15	ga_ls9c_ard_3-2-1_101070_2023-07-09_final.stac-item
2023-07-24 11:19:53	ga_ls9c_ard_3-2-1_110075_2023-07-24_final.stac-item
2023-09-03 11:17:16	ga_ls9c_ard_3-2-1_109083_2023-09-03_final.stac-item
2023-09-14 09:16:46	ga_ls9c_ard_3-2-1_090075_2023-09-13_final.stac-item
2023-11-19 09:07:21	ga_ls9c_ard_3-2-1_088082_2023-11-18_final.stac-item
2024-01-09 09:35:54	ga_ls9c_ard_3-2-1_093076_2024-01-09_final.stac-item
2024-01-23 11:23:55	ga_ls9c_ard_3-2-1_111068_2024-01-23_final.stac-item
2024-01-27 09:23:07	ga_ls9c_ard_3-2-1_091075_2024-01-26_final.stac-item
2024-02-05 09:18:13	ga_ls9c_ard_3-2-1_090078_2024-02-04_final.stac-item
2024-02-13 10:10:00	ga_ls9c_ard_3-2-1_098084_2024-02-13_final.stac-item
2024-02-17 11:23:18	ga_ls9c_ard_3-2-1_110082_2024-02-17_final.stac-item
2024-02-26 09:34:57	ga_ls9c_ard_3-2-1_093074_2024-02-26_final.stac-item
2024-03-13 11:13:53	ga_ls9c_ard_3-2-1_109074_2024-03-13_final.stac-item
2024-03-20 09:39:58	ga_ls9c_ard_3-2-1_094071_2024-03-20_final.stac-item
2024-04-28 11:25:19	ga_ls9c_ard_3-2-1_111073_2024-04-28_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