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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

53 results

Time (local)	Label
2021-12-16 11:26:22	ga_ls9c_ard_3-2-1_111074_2021-12-16_final.stac-item
2022-01-22 10:08:48	ga_ls9c_ard_3-2-1_098081_2022-01-22_final.stac-item
2022-01-26 11:20:35	ga_ls9c_ard_3-2-1_110075_2022-01-26_final.stac-item
2022-02-22 10:59:53	ga_ls9c_ard_3-2-1_107070_2022-02-22_final.stac-item
2022-03-27 11:46:58	ga_ls9c_ard_3-2-1_114080_2022-03-27_final.stac-item
2022-04-04 09:17:26	ga_ls9c_ard_3-2-1_090077_2022-04-03_final.stac-item
2022-05-11 09:37:41	ga_ls9c_ard_3-2-1_093082_2022-05-11_final.stac-item
2022-05-25 09:45:31	ga_ls9c_ard_3-2-1_095071_2022-05-25_final.stac-item
2022-05-25 11:28:47	ga_ls9c_ard_3-2-1_111082_2022-05-25_final.stac-item
2022-05-27 09:39:08	ga_ls9c_ard_3-2-1_093086_2022-05-27_final.stac-item
2022-06-14 09:26:05	ga_ls9c_ard_3-2-1_091084_2022-06-13_final.stac-item
2022-06-19 11:22:48	ga_ls9c_ard_3-2-1_110082_2022-06-19_final.stac-item
2022-07-02 10:47:17	ga_ls9c_ard_3-2-1_105070_2022-07-02_final.stac-item
2022-07-15 11:58:23	ga_ls9c_ard_3-2-1_116078_2022-07-15_final.stac-item
2022-07-28 09:52:24	ga_ls9c_ard_3-2-1_095087_2022-07-28_final.stac-item
2022-10-02 09:34:24	ga_ls9c_ard_3-2-1_093072_2022-10-02_final.stac-item
2022-10-03 10:21:39	ga_ls9c_ard_3-2-1_100082_2022-10-03_final.stac-item
2022-11-12 11:11:36	ga_ls9c_ard_3-2-1_108083_2022-11-12_final.stac-item
2022-11-18 10:29:20	ga_ls9c_ard_3-2-1_102070_2022-11-18_final.stac-item
2022-12-25 10:47:01	ga_ls9c_ard_3-2-1_105068_2022-12-25_final.stac-item
2023-01-04 09:46:52	ga_ls9c_ard_3-2-1_095072_2023-01-04_final.stac-item
2023-01-15 09:35:02	ga_ls9c_ard_3-2-1_092089_2023-01-15_final.stac-item
2023-01-27 09:52:59	ga_ls9c_ard_3-2-1_096072_2023-01-27_final.stac-item
2023-02-02 10:54:52	ga_ls9c_ard_3-2-1_106072_2023-02-02_final.stac-item
2023-03-06 12:31:29	ga_ls9c_ard_3-2-1_122067_2023-03-06_final.stac-item
2023-04-06 10:09:05	ga_ls9c_ard_3-2-1_099067_2023-04-06_final.stac-item
2023-04-21 11:07:00	ga_ls9c_ard_3-2-1_108073_2023-04-21_final.stac-item
2023-05-03 11:31:33	ga_ls9c_ard_3-2-1_112073_2023-05-03_final.stac-item
2023-05-09 09:20:44	ga_ls9c_ard_3-2-1_090086_2023-05-08_final.stac-item
2023-05-12 09:51:38	ga_ls9c_ard_3-2-1_095086_2023-05-12_final.stac-item
2023-07-02 10:21:11	ga_ls9c_ard_3-2-1_100083_2023-07-02_final.stac-item
2023-07-05 10:50:55	ga_ls9c_ard_3-2-1_105080_2023-07-05_final.stac-item
2023-07-21 09:15:18	ga_ls9c_ard_3-2-1_089088_2023-07-20_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
2023-09-07 10:46:37	ga_ls9c_ard_3-2-1_105068_2023-09-07_final.stac-item
2023-09-19 11:14:12	ga_ls9c_ard_3-2-1_109075_2023-09-19_final.stac-item
2023-10-06 10:19:49	ga_ls9c_ard_3-2-1_100078_2023-10-06_final.stac-item
2023-12-01 09:35:21	ga_ls9c_ard_3-2-1_092090_2023-12-01_final.stac-item
2024-01-13 09:14:47	ga_ls9c_ard_3-2-1_089085_2024-01-12_final.stac-item
2024-01-22 10:46:15	ga_ls9c_ard_3-2-1_104082_2024-01-22_final.stac-item
2024-02-06 10:01:52	ga_ls9c_ard_3-2-1_097079_2024-02-06_final.stac-item
2024-02-24 11:25:46	ga_ls9c_ard_3-2-1_111073_2024-02-24_final.stac-item
2024-02-26 09:34:33	ga_ls9c_ard_3-2-1_093073_2024-02-26_final.stac-item
2024-02-26 11:14:38	ga_ls9c_ard_3-2-1_109076_2024-02-26_final.stac-item
2024-02-28 09:23:49	ga_ls9c_ard_3-2-1_091077_2024-02-27_final.stac-item
2024-03-03 10:36:01	ga_ls9c_ard_3-2-1_103072_2024-03-03_final.stac-item
2024-03-08 10:56:34	ga_ls9c_ard_3-2-1_106077_2024-03-08_final.stac-item
2024-03-10 10:45:24	ga_ls9c_ard_3-2-1_104080_2024-03-10_final.stac-item
2024-03-12 10:33:49	ga_ls9c_ard_3-2-1_102082_2024-03-12_final.stac-item
2024-03-14 08:42:34	ga_ls9c_ard_3-2-1_084082_2024-03-13_final.stac-item
2024-04-04 10:35:51	ga_ls9c_ard_3-2-1_103072_2024-04-04_final.stac-item
2024-05-10 10:10:20	ga_ls9c_ard_3-2-1_099071_2024-05-10_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