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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
2021-11-12 10:56:13	ga_ls9c_ard_3-2-1_106069_2021-11-12_final.stac-item
2021-11-23 11:43:05	ga_ls9c_ard_3-2-1_114074_2021-11-23_final.stac-item
2021-12-12 10:10:15	ga_ls9c_ard_3-2-1_099069_2021-12-12_final.stac-item
2021-12-13 10:53:06	ga_ls9c_ard_3-2-1_106068_2021-12-13_final.stac-item
2021-12-15 10:46:18	ga_ls9c_ard_3-2-1_104082_2021-12-15_final.stac-item
2021-12-19 10:19:35	ga_ls9c_ard_3-2-1_100077_2021-12-19_final.stac-item
2022-02-14 10:09:44	ga_ls9c_ard_3-2-1_099068_2022-02-14_final.stac-item
2022-03-05 09:07:09	ga_ls9c_ard_3-2-1_088082_2022-03-04_final.stac-item
2022-05-08 09:06:49	ga_ls9c_ard_3-2-1_088082_2022-05-07_final.stac-item
2022-06-02 10:38:10	ga_ls9c_ard_3-2-1_103079_2022-06-02_final.stac-item
2022-06-03 11:19:26	ga_ls9c_ard_3-2-1_110074_2022-06-03_final.stac-item
2022-06-12 11:14:06	ga_ls9c_ard_3-2-1_109076_2022-06-12_final.stac-item
2022-06-21 09:28:25	ga_ls9c_ard_3-2-1_092074_2022-06-20_final.stac-item
2022-07-18 09:11:58	ga_ls9c_ard_3-2-1_089079_2022-07-17_final.stac-item
2022-07-18 09:13:10	ga_ls9c_ard_3-2-1_089082_2022-07-17_final.stac-item
2022-08-04 11:31:34	ga_ls9c_ard_3-2-1_112072_2022-08-04_final.stac-item
2022-08-08 11:11:17	ga_ls9c_ard_3-2-1_108083_2022-08-08_final.stac-item
2022-08-19 10:49:13	ga_ls9c_ard_3-2-1_105074_2022-08-19_final.stac-item
2022-09-29 09:06:42	ga_ls9c_ard_3-2-1_088080_2022-09-28_final.stac-item
2022-10-01 10:33:37	ga_ls9c_ard_3-2-1_102081_2022-10-01_final.stac-item
2022-10-07 11:32:37	ga_ls9c_ard_3-2-1_112074_2022-10-07_final.stac-item
2022-10-11 09:33:27	ga_ls9c_ard_3-2-1_092085_2022-10-11_final.stac-item
2022-10-21 10:05:00	ga_ls9c_ard_3-2-1_098071_2022-10-21_final.stac-item
2022-10-22 10:50:15	ga_ls9c_ard_3-2-1_105076_2022-10-22_final.stac-item
2022-11-05 09:28:05	ga_ls9c_ard_3-2-1_091087_2022-11-04_final.stac-item
2022-12-15 10:09:35	ga_ls9c_ard_3-2-1_099067_2022-12-15_final.stac-item
2022-12-29 10:27:55	ga_ls9c_ard_3-2-1_101082_2022-12-29_final.stac-item
2022-12-30 09:28:18	ga_ls9c_ard_3-2-1_092072_2022-12-29_final.stac-item
2023-01-17 09:21:27	ga_ls9c_ard_3-2-1_090086_2023-01-16_final.stac-item
2023-01-28 10:36:16	ga_ls9c_ard_3-2-1_103072_2023-01-28_final.stac-item
2023-02-11 09:12:37	ga_ls9c_ard_3-2-1_089079_2023-02-10_final.stac-item
2023-02-17 10:09:10	ga_ls9c_ard_3-2-1_099066_2023-02-17_final.stac-item
2023-04-01 11:31:25	ga_ls9c_ard_3-2-1_112072_2023-04-01_final.stac-item
2023-04-17 09:58:01	ga_ls9c_ard_3-2-1_096086_2023-04-17_final.stac-item
2023-04-22 10:15:21	ga_ls9c_ard_3-2-1_099083_2023-04-22_final.stac-item
2023-04-28 09:39:00	ga_ls9c_ard_3-2-1_093085_2023-04-28_final.stac-item
2023-05-04 10:35:30	ga_ls9c_ard_3-2-1_103072_2023-05-04_final.stac-item
2023-08-16 11:24:15	ga_ls9c_ard_3-2-1_111070_2023-08-16_final.stac-item
2023-09-14 10:52:52	ga_ls9c_ard_3-2-1_106068_2023-09-14_final.stac-item
2023-09-21 12:37:31	ga_ls9c_ard_3-2-1_123067_2023-09-21_final.stac-item
2023-10-09 10:49:32	ga_ls9c_ard_3-2-1_105075_2023-10-09_final.stac-item
2023-11-15 09:31:13	ga_ls9c_ard_3-2-1_092080_2023-11-15_final.stac-item
2024-01-03 10:13:23	ga_ls9c_ard_3-2-1_099077_2024-01-03_final.stac-item
2024-01-07 09:47:02	ga_ls9c_ard_3-2-1_095073_2024-01-07_final.stac-item
2024-01-11 09:27:56	ga_ls9c_ard_3-2-1_091087_2024-01-10_final.stac-item
2024-01-28 11:44:53	ga_ls9c_ard_3-2-1_114074_2024-01-28_final.stac-item
2024-02-15 11:32:31	ga_ls9c_ard_3-2-1_112074_2024-02-15_final.stac-item
2024-03-01 09:11:28	ga_ls9c_ard_3-2-1_089077_2024-02-29_final.stac-item
2024-03-29 09:33:39	ga_ls9c_ard_3-2-1_093071_2024-03-29_final.stac-item
2024-05-16 09:33:08	ga_ls9c_ard_3-2-1_093071_2024-05-16_nrt.stac-item
2024-05-16 11:13:37	ga_ls9c_ard_3-2-1_109075_2024-05-16_nrt.stac-item
2024-05-21 09:57:14	ga_ls9c_ard_3-2-1_096085_2024-05-21_nrt.stac-item
2024-05-25 09:33:40	ga_ls9c_ard_3-2-1_092088_2024-05-25_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