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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

56 results

Time (local)	Label
2021-11-20 09:42:25	ga_ls9c_ard_3-2-1_094072_2021-11-20_final.stac-item
2021-11-20 11:23:05	ga_ls9c_ard_3-2-1_110077_2021-11-20_final.stac-item
2021-12-06 09:12:54	ga_ls9c_ard_3-2-1_089080_2021-12-05_final.stac-item
2022-01-07 09:13:59	ga_ls9c_ard_3-2-1_089083_2022-01-06_final.stac-item
2022-02-09 11:32:31	ga_ls9c_ard_3-2-1_112074_2022-02-09_final.stac-item
2022-03-10 09:24:06	ga_ls9c_ard_3-2-1_091078_2022-03-09_final.stac-item
2022-04-04 09:21:50	ga_ls9c_ard_3-2-1_090088_2022-04-03_final.stac-item
2022-04-09 11:14:02	ga_ls9c_ard_3-2-1_109075_2022-04-09_final.stac-item
2022-04-23 11:24:14	ga_ls9c_ard_3-2-1_111070_2022-04-23_final.stac-item
2022-05-14 11:46:38	ga_ls9c_ard_3-2-1_114080_2022-05-14_final.stac-item
2022-05-19 10:27:00	ga_ls9c_ard_3-2-1_101082_2022-05-19_final.stac-item
2022-05-25 09:48:18	ga_ls9c_ard_3-2-1_095078_2022-05-25_final.stac-item
2022-06-12 11:14:06	ga_ls9c_ard_3-2-1_109076_2022-06-12_final.stac-item
2022-06-13 10:18:53	ga_ls9c_ard_3-2-1_100077_2022-06-13_final.stac-item
2022-06-15 11:45:27	ga_ls9c_ard_3-2-1_114077_2022-06-15_final.stac-item
2022-06-20 10:27:12	ga_ls9c_ard_3-2-1_101082_2022-06-20_final.stac-item
2022-07-12 09:51:48	ga_ls9c_ard_3-2-1_095086_2022-07-12_final.stac-item
2022-08-08 09:35:11	ga_ls9c_ard_3-2-1_092090_2022-08-08_final.stac-item
2022-08-19 09:11:32	ga_ls9c_ard_3-2-1_089077_2022-08-18_final.stac-item
2022-09-23 11:20:39	ga_ls9c_ard_3-2-1_110075_2022-09-23_final.stac-item
2022-10-04 11:04:55	ga_ls9c_ard_3-2-1_107082_2022-10-04_final.stac-item
2022-10-11 09:31:03	ga_ls9c_ard_3-2-1_092079_2022-10-11_final.stac-item
2022-10-19 10:19:45	ga_ls9c_ard_3-2-1_100077_2022-10-19_final.stac-item
2022-11-04 10:17:18	ga_ls9c_ard_3-2-1_100071_2022-11-04_final.stac-item
2022-11-12 11:11:36	ga_ls9c_ard_3-2-1_108083_2022-11-12_final.stac-item
2022-11-16 10:43:42	ga_ls9c_ard_3-2-1_104075_2022-11-16_final.stac-item
2022-11-23 09:12:35	ga_ls9c_ard_3-2-1_089079_2022-11-22_final.stac-item
2022-12-23 11:00:34	ga_ls9c_ard_3-2-1_107071_2022-12-23_final.stac-item
2023-01-22 09:37:09	ga_ls9c_ard_3-2-1_093079_2023-01-22_final.stac-item
2023-03-05 10:10:57	ga_ls9c_ard_3-2-1_099071_2023-03-05_final.stac-item
2023-03-09 11:25:02	ga_ls9c_ard_3-2-1_111071_2023-03-09_final.stac-item
2023-04-28 11:13:30	ga_ls9c_ard_3-2-1_109074_2023-04-28_final.stac-item
2023-05-24 11:52:17	ga_ls9c_ard_3-2-1_115079_2023-05-24_final.stac-item
2023-07-08 11:19:28	ga_ls9c_ard_3-2-1_110074_2023-07-08_final.stac-item
2023-08-02 11:14:38	ga_ls9c_ard_3-2-1_109077_2023-08-02_final.stac-item
2023-08-14 10:01:44	ga_ls9c_ard_3-2-1_097080_2023-08-14_final.stac-item
2023-10-09 09:12:15	ga_ls9c_ard_3-2-1_089079_2023-10-08_final.stac-item
2023-11-04 11:23:49	ga_ls9c_ard_3-2-1_111068_2023-11-04_final.stac-item
2023-11-04 11:24:13	ga_ls9c_ard_3-2-1_111069_2023-11-04_final.stac-item
2023-11-06 09:37:00	ga_ls9c_ard_3-2-1_093079_2023-11-06_final.stac-item
2023-11-22 11:14:00	ga_ls9c_ard_3-2-1_109074_2023-11-22_final.stac-item
2023-11-23 10:19:35	ga_ls9c_ard_3-2-1_100077_2023-11-23_final.stac-item
2023-12-06 09:51:26	ga_ls9c_ard_3-2-1_095084_2023-12-06_final.stac-item
2023-12-22 08:11:03	ga_ls9c_ard_3-2-1_079080_2023-12-21_final.stac-item
2023-12-28 10:52:31	ga_ls9c_ard_3-2-1_105082_2023-12-28_final.stac-item
2024-01-24 10:29:04	ga_ls9c_ard_3-2-1_102070_2024-01-24_final.stac-item
2024-01-26 10:19:32	ga_ls9c_ard_3-2-1_100077_2024-01-26_final.stac-item
2024-01-27 11:00:49	ga_ls9c_ard_3-2-1_107072_2024-01-27_final.stac-item
2024-01-27 11:01:13	ga_ls9c_ard_3-2-1_107073_2024-01-27_final.stac-item
2024-02-11 11:57:41	ga_ls9c_ard_3-2-1_116075_2024-02-11_final.stac-item
2024-02-11 11:58:05	ga_ls9c_ard_3-2-1_116076_2024-02-11_final.stac-item
2024-02-27 10:19:25	ga_ls9c_ard_3-2-1_100077_2024-02-27_final.stac-item
2024-03-11 11:27:27	ga_ls9c_ard_3-2-1_111077_2024-03-11_final.stac-item
2024-03-22 09:30:23	ga_ls9c_ard_3-2-1_092078_2024-03-22_final.stac-item
2024-03-23 10:11:39	ga_ls9c_ard_3-2-1_099073_2024-03-23_final.stac-item
2024-05-09 11:05:09	ga_ls9c_ard_3-2-1_108069_2024-05-09_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