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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

43 results

Time (local)	Label
2021-11-04 10:37:19	ga_ls9c_ard_3-2-1_103081_2021-11-04_final.stac-item
2021-11-07 09:17:52	ga_ls9c_ard_3-2-1_090076_2021-11-06_final.stac-item
2021-12-16 11:26:22	ga_ls9c_ard_3-2-1_111074_2021-12-16_final.stac-item
2022-01-01 11:23:59	ga_ls9c_ard_3-2-1_111068_2022-01-01_final.stac-item
2022-01-01 11:24:46	ga_ls9c_ard_3-2-1_111070_2022-01-01_final.stac-item
2022-01-10 11:18:33	ga_ls9c_ard_3-2-1_110070_2022-01-10_final.stac-item
2022-01-21 09:22:21	ga_ls9c_ard_3-2-1_091073_2022-01-20_final.stac-item
2022-04-07 11:24:25	ga_ls9c_ard_3-2-1_111070_2022-04-07_final.stac-item
2022-04-13 10:49:40	ga_ls9c_ard_3-2-1_105076_2022-04-13_final.stac-item
2022-05-16 09:57:21	ga_ls9c_ard_3-2-1_096085_2022-05-16_final.stac-item
2022-08-03 10:49:53	ga_ls9c_ard_3-2-1_105076_2022-08-03_final.stac-item
2022-08-19 09:10:44	ga_ls9c_ard_3-2-1_089075_2022-08-18_final.stac-item
2022-08-20 11:32:29	ga_ls9c_ard_3-2-1_112074_2022-08-20_final.stac-item
2022-09-10 10:10:57	ga_ls9c_ard_3-2-1_099071_2022-09-10_final.stac-item
2022-10-25 11:20:22	ga_ls9c_ard_3-2-1_110074_2022-10-25_final.stac-item
2022-12-06 10:20:08	ga_ls9c_ard_3-2-1_100078_2022-12-06_final.stac-item
2023-01-18 09:58:18	ga_ls9c_ard_3-2-1_097070_2023-01-18_final.stac-item
2023-01-29 11:19:56	ga_ls9c_ard_3-2-1_110073_2023-01-29_final.stac-item
2023-02-11 09:12:37	ga_ls9c_ard_3-2-1_089079_2023-02-10_final.stac-item
2023-02-18 10:53:36	ga_ls9c_ard_3-2-1_106069_2023-02-18_final.stac-item
2023-02-22 10:28:47	ga_ls9c_ard_3-2-1_102069_2023-02-22_final.stac-item
2023-03-08 10:40:36	ga_ls9c_ard_3-2-1_104068_2023-03-08_final.stac-item
2023-03-20 09:28:47	ga_ls9c_ard_3-2-1_092074_2023-03-19_final.stac-item
2023-07-03 09:21:35	ga_ls9c_ard_3-2-1_091073_2023-07-02_final.stac-item
2023-07-18 10:18:30	ga_ls9c_ard_3-2-1_100076_2023-07-18_final.stac-item
2023-08-20 09:21:53	ga_ls9c_ard_3-2-1_091073_2023-08-19_final.stac-item
2023-09-15 09:57:15	ga_ls9c_ard_3-2-1_097068_2023-09-15_final.stac-item
2023-09-22 10:02:37	ga_ls9c_ard_3-2-1_098066_2023-09-22_final.stac-item
2023-10-03 09:46:29	ga_ls9c_ard_3-2-1_095072_2023-10-03_final.stac-item
2023-10-07 09:22:12	ga_ls9c_ard_3-2-1_091073_2023-10-06_final.stac-item
2023-10-17 09:57:49	ga_ls9c_ard_3-2-1_097069_2023-10-17_final.stac-item
2023-11-01 10:53:44	ga_ls9c_ard_3-2-1_106070_2023-11-01_final.stac-item
2023-11-14 10:27:39	ga_ls9c_ard_3-2-1_101082_2023-11-14_final.stac-item
2023-12-20 11:37:59	ga_ls9c_ard_3-2-1_113072_2023-12-20_final.stac-item
2024-01-02 11:11:25	ga_ls9c_ard_3-2-1_108083_2024-01-02_final.stac-item
2024-02-05 09:19:48	ga_ls9c_ard_3-2-1_090082_2024-02-04_final.stac-item
2024-02-20 10:14:04	ga_ls9c_ard_3-2-1_099079_2024-02-20_final.stac-item
2024-02-21 10:55:42	ga_ls9c_ard_3-2-1_106075_2024-02-21_final.stac-item
2024-03-11 09:46:11	ga_ls9c_ard_3-2-1_095071_2024-03-11_final.stac-item
2024-03-28 10:30:05	ga_ls9c_ard_3-2-1_102073_2024-03-28_final.stac-item
2024-04-08 11:52:23	ga_ls9c_ard_3-2-1_115078_2024-04-08_final.stac-item
2024-04-15 10:16:48	ga_ls9c_ard_3-2-1_100071_2024-04-15_final.stac-item
2024-05-30 11:23:27	ga_ls9c_ard_3-2-1_111069_2024-05-30_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