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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

44 results

Time (local)	Label
2021-11-13 11:38:10	ga_ls9c_ard_3-2-1_113074_2021-11-13_final.stac-item
2021-12-22 10:50:05	ga_ls9c_ard_3-2-1_105076_2021-12-22_final.stac-item
2022-01-03 09:33:55	ga_ls9c_ard_3-2-1_093071_2022-01-03_final.stac-item
2022-01-20 10:20:45	ga_ls9c_ard_3-2-1_100080_2022-01-20_final.stac-item
2022-02-06 09:27:56	ga_ls9c_ard_3-2-1_091087_2022-02-05_final.stac-item
2022-02-08 10:48:51	ga_ls9c_ard_3-2-1_105073_2022-02-08_final.stac-item
2022-02-16 09:58:33	ga_ls9c_ard_3-2-1_097071_2022-02-16_final.stac-item
2022-02-23 11:44:44	ga_ls9c_ard_3-2-1_114074_2022-02-23_final.stac-item
2022-04-09 09:37:33	ga_ls9c_ard_3-2-1_093081_2022-04-09_final.stac-item
2022-04-19 10:10:55	ga_ls9c_ard_3-2-1_099072_2022-04-19_final.stac-item
2022-05-20 11:07:03	ga_ls9c_ard_3-2-1_108074_2022-05-20_final.stac-item
2022-05-24 10:41:56	ga_ls9c_ard_3-2-1_104073_2022-05-24_final.stac-item
2022-08-02 11:46:42	ga_ls9c_ard_3-2-1_114079_2022-08-02_final.stac-item
2022-08-09 10:09:41	ga_ls9c_ard_3-2-1_099068_2022-08-09_final.stac-item
2022-10-28 11:51:39	ga_ls9c_ard_3-2-1_115075_2022-10-28_final.stac-item
2022-11-28 11:06:47	ga_ls9c_ard_3-2-1_108071_2022-11-28_final.stac-item
2022-12-19 11:29:18	ga_ls9c_ard_3-2-1_111081_2022-12-19_final.stac-item
2022-12-26 09:52:36	ga_ls9c_ard_3-2-1_096071_2022-12-26_final.stac-item
2023-01-10 10:47:03	ga_ls9c_ard_3-2-1_105068_2023-01-10_final.stac-item
2023-01-20 11:23:59	ga_ls9c_ard_3-2-1_111068_2023-01-20_final.stac-item
2023-02-18 09:17:30	ga_ls9c_ard_3-2-1_090076_2023-02-17_final.stac-item
2023-03-16 11:36:00	ga_ls9c_ard_3-2-1_112083_2023-03-16_final.stac-item
2023-03-18 09:40:46	ga_ls9c_ard_3-2-1_094073_2023-03-18_final.stac-item
2023-04-10 09:47:31	ga_ls9c_ard_3-2-1_095075_2023-04-10_final.stac-item
2023-04-21 09:33:42	ga_ls9c_ard_3-2-1_092087_2023-04-21_final.stac-item
2023-05-09 09:21:08	ga_ls9c_ard_3-2-1_090087_2023-05-08_final.stac-item
2023-05-15 10:18:31	ga_ls9c_ard_3-2-1_100076_2023-05-15_final.stac-item
2023-05-19 09:56:56	ga_ls9c_ard_3-2-1_096084_2023-05-19_final.stac-item
2023-06-01 09:26:44	ga_ls9c_ard_3-2-1_091086_2023-05-31_final.stac-item
2023-07-01 09:39:54	ga_ls9c_ard_3-2-1_093088_2023-07-01_final.stac-item
2023-08-01 10:27:46	ga_ls9c_ard_3-2-1_102068_2023-08-01_final.stac-item
2023-08-16 11:25:03	ga_ls9c_ard_3-2-1_111072_2023-08-16_final.stac-item
2023-09-22 10:04:36	ga_ls9c_ard_3-2-1_098071_2023-09-22_final.stac-item
2023-09-22 10:09:24	ga_ls9c_ard_3-2-1_098083_2023-09-22_final.stac-item
2023-12-02 11:51:30	ga_ls9c_ard_3-2-1_115075_2023-12-02_final.stac-item
2024-01-02 09:28:08	ga_ls9c_ard_3-2-1_092072_2024-01-01_final.stac-item
2024-02-05 10:53:30	ga_ls9c_ard_3-2-1_106069_2024-02-05_final.stac-item
2024-03-06 09:29:15	ga_ls9c_ard_3-2-1_092075_2024-03-05_final.stac-item
2024-03-09 11:38:38	ga_ls9c_ard_3-2-1_113074_2024-03-09_final.stac-item
2024-04-02 09:13:43	ga_ls9c_ard_3-2-1_089083_2024-04-01_final.stac-item
2024-04-09 09:22:15	ga_ls9c_ard_3-2-1_090089_2024-04-08_final.stac-item
2024-04-18 09:13:08	ga_ls9c_ard_3-2-1_089082_2024-04-17_final.stac-item
2024-05-12 11:37:14	ga_ls9c_ard_3-2-1_113072_2024-05-12_interim.stac-item
2024-05-28 11:41:24	ga_ls9c_ard_3-2-1_113083_2024-05-28_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