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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

68 results

Time (local)	Label
2021-11-20 09:44:49	ga_ls9c_ard_3-2-1_094078_2021-11-20_final.stac-item
2021-12-26 10:26:58	ga_ls9c_ard_3-2-1_101080_2021-12-26_final.stac-item
2021-12-27 11:09:26	ga_ls9c_ard_3-2-1_108078_2021-12-27_final.stac-item
2022-01-01 09:49:05	ga_ls9c_ard_3-2-1_095078_2022-01-01_final.stac-item
2022-01-17 09:49:03	ga_ls9c_ard_3-2-1_095078_2022-01-17_final.stac-item
2022-02-11 11:21:44	ga_ls9c_ard_3-2-1_110078_2022-02-11_final.stac-item
2022-03-01 11:09:10	ga_ls9c_ard_3-2-1_108078_2022-03-01_final.stac-item
2022-03-31 09:42:34	ga_ls9c_ard_3-2-1_094078_2022-03-31_final.stac-item
2022-04-23 11:27:50	ga_ls9c_ard_3-2-1_111079_2022-04-23_final.stac-item
2022-05-02 11:21:38	ga_ls9c_ard_3-2-1_110079_2022-05-02_final.stac-item
2022-06-14 11:02:34	ga_ls9c_ard_3-2-1_107078_2022-06-14_final.stac-item
2022-06-23 10:58:37	ga_ls9c_ard_3-2-1_106083_2022-06-23_final.stac-item
2022-06-28 11:15:36	ga_ls9c_ard_3-2-1_109079_2022-06-28_final.stac-item
2022-07-12 11:27:30	ga_ls9c_ard_3-2-1_111078_2022-07-12_final.stac-item
2022-07-14 11:15:07	ga_ls9c_ard_3-2-1_109078_2022-07-14_final.stac-item
2022-08-13 11:28:16	ga_ls9c_ard_3-2-1_111079_2022-08-13_final.stac-item
2022-08-22 11:22:08	ga_ls9c_ard_3-2-1_110079_2022-08-22_final.stac-item
2022-08-29 09:48:38	ga_ls9c_ard_3-2-1_095077_2022-08-29_final.stac-item
2022-08-29 11:28:19	ga_ls9c_ard_3-2-1_111079_2022-08-29_final.stac-item
2022-09-30 09:49:09	ga_ls9c_ard_3-2-1_095078_2022-09-30_final.stac-item
2022-10-03 11:58:32	ga_ls9c_ard_3-2-1_116077_2022-10-03_final.stac-item
2022-10-27 11:09:35	ga_ls9c_ard_3-2-1_108078_2022-10-27_final.stac-item
2022-11-17 11:28:33	ga_ls9c_ard_3-2-1_111079_2022-11-17_final.stac-item
2022-11-28 11:09:34	ga_ls9c_ard_3-2-1_108078_2022-11-28_final.stac-item
2023-01-20 09:49:05	ga_ls9c_ard_3-2-1_095078_2023-01-20_final.stac-item
2023-01-20 11:27:34	ga_ls9c_ard_3-2-1_111077_2023-01-20_final.stac-item
2023-01-22 09:38:21	ga_ls9c_ard_3-2-1_093082_2023-01-22_final.stac-item
2023-02-04 10:46:07	ga_ls9c_ard_3-2-1_104081_2023-02-04_final.stac-item
2023-02-16 11:09:35	ga_ls9c_ard_3-2-1_108078_2023-02-16_final.stac-item
2023-02-21 09:49:08	ga_ls9c_ard_3-2-1_095078_2023-02-21_final.stac-item
2023-03-04 11:09:22	ga_ls9c_ard_3-2-1_108078_2023-03-04_final.stac-item
2023-03-20 11:09:16	ga_ls9c_ard_3-2-1_108078_2023-03-20_final.stac-item
2023-03-25 09:48:27	ga_ls9c_ard_3-2-1_095077_2023-03-25_final.stac-item
2023-03-25 11:27:20	ga_ls9c_ard_3-2-1_111077_2023-03-25_final.stac-item
2023-04-26 09:48:12	ga_ls9c_ard_3-2-1_095077_2023-04-26_final.stac-item
2023-04-26 11:27:53	ga_ls9c_ard_3-2-1_111079_2023-04-26_final.stac-item
2023-05-12 11:27:43	ga_ls9c_ard_3-2-1_111079_2023-05-12_final.stac-item
2023-05-23 11:08:14	ga_ls9c_ard_3-2-1_108077_2023-05-23_final.stac-item
2023-05-28 11:27:33	ga_ls9c_ard_3-2-1_111079_2023-05-28_final.stac-item
2023-06-13 09:47:45	ga_ls9c_ard_3-2-1_095077_2023-06-13_final.stac-item
2023-06-13 11:27:26	ga_ls9c_ard_3-2-1_111079_2023-06-13_final.stac-item
2023-07-01 09:37:30	ga_ls9c_ard_3-2-1_093082_2023-07-01_final.stac-item
2023-07-08 11:21:28	ga_ls9c_ard_3-2-1_110079_2023-07-08_final.stac-item
2023-07-10 11:08:19	ga_ls9c_ard_3-2-1_108077_2023-07-10_final.stac-item
2023-07-22 11:33:51	ga_ls9c_ard_3-2-1_112079_2023-07-22_final.stac-item
2023-08-03 11:57:07	ga_ls9c_ard_3-2-1_116075_2023-08-03_final.stac-item
2023-08-03 11:57:31	ga_ls9c_ard_3-2-1_116076_2023-08-03_final.stac-item
2023-08-04 11:03:53	ga_ls9c_ard_3-2-1_107081_2023-08-04_final.stac-item
2023-08-16 09:48:34	ga_ls9c_ard_3-2-1_095078_2023-08-16_final.stac-item
2023-08-18 11:15:29	ga_ls9c_ard_3-2-1_109079_2023-08-18_final.stac-item
2023-09-01 11:28:02	ga_ls9c_ard_3-2-1_111079_2023-09-01_final.stac-item
2023-09-03 11:15:40	ga_ls9c_ard_3-2-1_109079_2023-09-03_final.stac-item
2023-09-08 11:33:29	ga_ls9c_ard_3-2-1_112077_2023-09-08_final.stac-item
2023-09-08 11:34:17	ga_ls9c_ard_3-2-1_112079_2023-09-08_final.stac-item
2023-09-14 10:58:51	ga_ls9c_ard_3-2-1_106083_2023-09-14_final.stac-item
2023-09-24 11:33:30	ga_ls9c_ard_3-2-1_112077_2023-09-24_final.stac-item
2023-11-04 11:28:13	ga_ls9c_ard_3-2-1_111079_2023-11-04_final.stac-item
2023-11-15 11:09:18	ga_ls9c_ard_3-2-1_108078_2023-11-15_final.stac-item
2024-01-02 11:09:25	ga_ls9c_ard_3-2-1_108078_2024-01-02_final.stac-item
2024-01-23 08:10:56	ga_ls9c_ard_3-2-1_079080_2024-01-22_final.stac-item
2024-01-27 11:01:13	ga_ls9c_ard_3-2-1_107073_2024-01-27_final.stac-item
2024-02-05 09:20:12	ga_ls9c_ard_3-2-1_090083_2024-02-04_final.stac-item
2024-03-10 10:43:48	ga_ls9c_ard_3-2-1_104076_2024-03-10_final.stac-item
2024-03-11 09:48:58	ga_ls9c_ard_3-2-1_095078_2024-03-11_final.stac-item
2024-03-27 11:28:08	ga_ls9c_ard_3-2-1_111079_2024-03-27_final.stac-item
2024-04-11 10:45:34	ga_ls9c_ard_3-2-1_104081_2024-04-11_final.stac-item
2024-04-15 11:58:04	ga_ls9c_ard_3-2-1_116077_2024-04-15_final.stac-item
2024-04-28 09:48:01	ga_ls9c_ard_3-2-1_095077_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