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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

37 results

Time (local)	Label
2021-12-15 10:40:43	ga_ls9c_ard_3-2-1_104068_2021-12-15_final.stac-item
2021-12-16 11:24:46	ga_ls9c_ard_3-2-1_111070_2021-12-16_final.stac-item
2022-01-02 10:33:32	ga_ls9c_ard_3-2-1_102081_2022-01-02_final.stac-item
2022-01-03 11:12:00	ga_ls9c_ard_3-2-1_109069_2022-01-03_final.stac-item
2022-02-11 11:20:32	ga_ls9c_ard_3-2-1_110075_2022-02-11_final.stac-item
2022-03-03 09:21:06	ga_ls9c_ard_3-2-1_090086_2022-03-02_final.stac-item
2022-04-26 10:21:51	ga_ls9c_ard_3-2-1_100084_2022-04-26_final.stac-item
2022-05-04 11:09:15	ga_ls9c_ard_3-2-1_108079_2022-05-04_final.stac-item
2022-05-05 10:10:50	ga_ls9c_ard_3-2-1_099072_2022-05-05_final.stac-item
2022-05-10 10:27:44	ga_ls9c_ard_3-2-1_102068_2022-05-10_final.stac-item
2022-05-16 09:57:21	ga_ls9c_ard_3-2-1_096085_2022-05-16_final.stac-item
2022-06-14 09:21:17	ga_ls9c_ard_3-2-1_091072_2022-06-13_final.stac-item
2022-06-19 11:18:00	ga_ls9c_ard_3-2-1_110070_2022-06-19_final.stac-item
2022-06-21 09:33:13	ga_ls9c_ard_3-2-1_092086_2022-06-21_final.stac-item
2022-07-16 11:04:46	ga_ls9c_ard_3-2-1_107083_2022-07-16_final.stac-item
2022-07-21 11:18:13	ga_ls9c_ard_3-2-1_110070_2022-07-21_final.stac-item
2022-08-26 10:55:49	ga_ls9c_ard_3-2-1_106075_2022-08-26_final.stac-item
2022-10-07 09:57:43	ga_ls9c_ard_3-2-1_096084_2022-10-07_final.stac-item
2022-10-12 10:09:09	ga_ls9c_ard_3-2-1_099066_2022-10-12_final.stac-item
2022-10-27 09:28:19	ga_ls9c_ard_3-2-1_092072_2022-10-26_final.stac-item
2023-01-06 09:35:42	ga_ls9c_ard_3-2-1_093075_2023-01-06_final.stac-item
2023-02-21 09:46:44	ga_ls9c_ard_3-2-1_095072_2023-02-21_final.stac-item
2023-03-03 10:25:43	ga_ls9c_ard_3-2-1_101077_2023-03-03_final.stac-item
2023-03-09 09:52:32	ga_ls9c_ard_3-2-1_095087_2023-03-09_final.stac-item
2023-06-19 10:51:31	ga_ls9c_ard_3-2-1_105082_2023-06-19_final.stac-item
2023-09-07 09:16:07	ga_ls9c_ard_3-2-1_089089_2023-09-06_final.stac-item
2023-10-05 11:14:14	ga_ls9c_ard_3-2-1_109075_2023-10-05_final.stac-item
2023-10-06 10:19:49	ga_ls9c_ard_3-2-1_100078_2023-10-06_final.stac-item
2023-11-11 11:31:39	ga_ls9c_ard_3-2-1_112072_2023-11-11_final.stac-item
2023-12-06 09:47:03	ga_ls9c_ard_3-2-1_095073_2023-12-06_final.stac-item
2023-12-07 10:33:29	ga_ls9c_ard_3-2-1_102081_2023-12-07_final.stac-item
2023-12-25 11:58:32	ga_ls9c_ard_3-2-1_116077_2023-12-25_final.stac-item
2024-02-13 10:05:37	ga_ls9c_ard_3-2-1_098073_2024-02-13_final.stac-item
2024-02-21 09:17:37	ga_ls9c_ard_3-2-1_090077_2024-02-20_final.stac-item
2024-03-04 11:18:05	ga_ls9c_ard_3-2-1_110069_2024-03-04_final.stac-item
2024-04-15 10:19:35	ga_ls9c_ard_3-2-1_100078_2024-04-15_final.stac-item
2024-05-30 11:23:51	ga_ls9c_ard_3-2-1_111070_2024-05-30_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