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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

55 results

Time (local)	Label
2021-12-12 10:16:14	ga_ls9c_ard_3-2-1_099084_2021-12-12_final.stac-item
2021-12-28 10:16:12	ga_ls9c_ard_3-2-1_099084_2021-12-28_final.stac-item
2022-01-13 10:16:09	ga_ls9c_ard_3-2-1_099084_2022-01-13_final.stac-item
2022-01-29 10:16:11	ga_ls9c_ard_3-2-1_099084_2022-01-29_final.stac-item
2022-02-14 10:16:07	ga_ls9c_ard_3-2-1_099084_2022-02-14_final.stac-item
2022-03-02 10:15:56	ga_ls9c_ard_3-2-1_099084_2022-03-02_final.stac-item
2022-04-03 10:15:51	ga_ls9c_ard_3-2-1_099084_2022-04-03_final.stac-item
2022-04-19 10:15:42	ga_ls9c_ard_3-2-1_099084_2022-04-19_final.stac-item
2022-05-05 10:15:37	ga_ls9c_ard_3-2-1_099084_2022-05-05_final.stac-item
2022-05-21 10:15:25	ga_ls9c_ard_3-2-1_099084_2022-05-21_final.stac-item
2022-06-06 10:15:27	ga_ls9c_ard_3-2-1_099084_2022-06-06_final.stac-item
2022-06-22 10:15:43	ga_ls9c_ard_3-2-1_099084_2022-06-22_final.stac-item
2022-07-08 10:15:45	ga_ls9c_ard_3-2-1_099084_2022-07-08_final.stac-item
2022-07-24 10:15:52	ga_ls9c_ard_3-2-1_099084_2022-07-24_final.stac-item
2022-08-09 10:16:04	ga_ls9c_ard_3-2-1_099084_2022-08-09_final.stac-item
2022-08-25 10:16:09	ga_ls9c_ard_3-2-1_099084_2022-08-25_final.stac-item
2022-09-10 10:16:09	ga_ls9c_ard_3-2-1_099084_2022-09-10_final.stac-item
2022-09-26 10:16:16	ga_ls9c_ard_3-2-1_099084_2022-09-26_final.stac-item
2022-10-12 10:16:19	ga_ls9c_ard_3-2-1_099084_2022-10-12_final.stac-item
2022-10-28 10:16:22	ga_ls9c_ard_3-2-1_099084_2022-10-28_final.stac-item
2022-11-13 10:16:23	ga_ls9c_ard_3-2-1_099084_2022-11-13_final.stac-item
2022-11-29 10:16:20	ga_ls9c_ard_3-2-1_099084_2022-11-29_final.stac-item
2022-12-15 10:16:22	ga_ls9c_ard_3-2-1_099084_2022-12-15_final.stac-item
2022-12-31 10:16:21	ga_ls9c_ard_3-2-1_099084_2022-12-31_final.stac-item
2023-01-16 10:16:17	ga_ls9c_ard_3-2-1_099084_2023-01-16_final.stac-item
2023-02-01 10:16:23	ga_ls9c_ard_3-2-1_099084_2023-02-01_final.stac-item
2023-02-17 10:16:20	ga_ls9c_ard_3-2-1_099084_2023-02-17_final.stac-item
2023-03-05 10:16:08	ga_ls9c_ard_3-2-1_099084_2023-03-05_final.stac-item
2023-03-21 10:16:02	ga_ls9c_ard_3-2-1_099084_2023-03-21_final.stac-item
2023-04-06 10:15:51	ga_ls9c_ard_3-2-1_099084_2023-04-06_final.stac-item
2023-04-22 10:15:45	ga_ls9c_ard_3-2-1_099084_2023-04-22_final.stac-item
2023-05-08 10:15:34	ga_ls9c_ard_3-2-1_099084_2023-05-08_final.stac-item
2023-05-24 10:15:24	ga_ls9c_ard_3-2-1_099084_2023-05-24_final.stac-item
2023-06-09 10:15:19	ga_ls9c_ard_3-2-1_099084_2023-06-09_final.stac-item
2023-06-25 10:15:14	ga_ls9c_ard_3-2-1_099084_2023-06-25_final.stac-item
2023-07-11 10:15:30	ga_ls9c_ard_3-2-1_099084_2023-07-11_final.stac-item
2023-07-27 10:15:32	ga_ls9c_ard_3-2-1_099084_2023-07-27_final.stac-item
2023-08-12 10:15:41	ga_ls9c_ard_3-2-1_099084_2023-08-12_final.stac-item
2023-08-28 10:15:50	ga_ls9c_ard_3-2-1_099084_2023-08-28_final.stac-item
2023-09-13 10:15:59	ga_ls9c_ard_3-2-1_099084_2023-09-13_final.stac-item
2023-09-29 10:15:56	ga_ls9c_ard_3-2-1_099084_2023-09-29_final.stac-item
2023-10-15 10:16:08	ga_ls9c_ard_3-2-1_099084_2023-10-15_final.stac-item
2023-10-31 10:16:05	ga_ls9c_ard_3-2-1_099084_2023-10-31_final.stac-item
2023-11-16 10:16:05	ga_ls9c_ard_3-2-1_099084_2023-11-16_final.stac-item
2023-12-02 10:16:13	ga_ls9c_ard_3-2-1_099084_2023-12-02_final.stac-item
2023-12-18 10:16:15	ga_ls9c_ard_3-2-1_099084_2023-12-18_final.stac-item
2024-01-03 10:16:11	ga_ls9c_ard_3-2-1_099084_2024-01-03_final.stac-item
2024-01-19 10:16:11	ga_ls9c_ard_3-2-1_099084_2024-01-19_final.stac-item
2024-02-04 10:16:13	ga_ls9c_ard_3-2-1_099084_2024-02-04_final.stac-item
2024-02-20 10:16:03	ga_ls9c_ard_3-2-1_099084_2024-02-20_final.stac-item
2024-03-23 10:16:02	ga_ls9c_ard_3-2-1_099084_2024-03-23_final.stac-item
2024-04-08 10:15:53	ga_ls9c_ard_3-2-1_099084_2024-04-08_final.stac-item
2024-04-24 10:15:32	ga_ls9c_ard_3-2-1_099084_2024-04-24_final.stac-item
2024-05-10 10:15:31	ga_ls9c_ard_3-2-1_099084_2024-05-10_final.stac-item
2024-05-26 10:15:19	ga_ls9c_ard_3-2-1_099084_2024-05-26_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