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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

51 results

Time (local)	Label
2021-11-20 09:42:49	ga_ls9c_ard_3-2-1_094073_2021-11-20_final.stac-item
2021-11-22 11:03:08	ga_ls9c_ard_3-2-1_107074_2021-11-22_final.stac-item
2021-12-07 09:52:10	ga_ls9c_ard_3-2-1_096070_2021-12-07_final.stac-item
2021-12-26 10:27:46	ga_ls9c_ard_3-2-1_101082_2021-12-26_final.stac-item
2022-01-05 09:27:09	ga_ls9c_ard_3-2-1_091085_2022-01-04_final.stac-item
2022-01-23 10:46:53	ga_ls9c_ard_3-2-1_105068_2022-01-23_final.stac-item
2022-02-04 11:14:23	ga_ls9c_ard_3-2-1_109075_2022-02-04_final.stac-item
2022-02-07 11:47:41	ga_ls9c_ard_3-2-1_114081_2022-02-07_final.stac-item
2022-02-11 09:41:15	ga_ls9c_ard_3-2-1_094074_2022-02-11_final.stac-item
2022-04-13 09:11:11	ga_ls9c_ard_3-2-1_089077_2022-04-12_final.stac-item
2022-06-25 10:42:19	ga_ls9c_ard_3-2-1_104073_2022-06-25_final.stac-item
2022-07-16 09:22:42	ga_ls9c_ard_3-2-1_091075_2022-07-15_final.stac-item
2022-08-10 09:16:51	ga_ls9c_ard_3-2-1_090075_2022-08-09_final.stac-item
2022-08-12 10:42:36	ga_ls9c_ard_3-2-1_104073_2022-08-12_final.stac-item
2022-08-17 09:22:17	ga_ls9c_ard_3-2-1_091073_2022-08-16_final.stac-item
2022-08-21 10:36:04	ga_ls9c_ard_3-2-1_103072_2022-08-21_final.stac-item
2022-08-26 09:21:43	ga_ls9c_ard_3-2-1_090087_2022-08-25_final.stac-item
2022-08-28 09:06:34	ga_ls9c_ard_3-2-1_088080_2022-08-27_final.stac-item
2022-10-14 10:03:59	ga_ls9c_ard_3-2-1_097084_2022-10-14_final.stac-item
2022-11-07 09:13:21	ga_ls9c_ard_3-2-1_089081_2022-11-06_final.stac-item
2022-11-26 09:40:16	ga_ls9c_ard_3-2-1_094071_2022-11-26_final.stac-item
2022-12-07 09:29:18	ga_ls9c_ard_3-2-1_091090_2022-12-06_final.stac-item
2022-12-27 10:39:51	ga_ls9c_ard_3-2-1_103081_2022-12-27_final.stac-item
2023-01-12 10:39:51	ga_ls9c_ard_3-2-1_103081_2023-01-12_final.stac-item
2023-03-13 09:21:50	ga_ls9c_ard_3-2-1_091072_2023-03-12_final.stac-item
2023-03-23 09:58:51	ga_ls9c_ard_3-2-1_097072_2023-03-23_final.stac-item
2023-03-29 09:22:26	ga_ls9c_ard_3-2-1_091074_2023-03-28_final.stac-item
2023-04-22 10:13:46	ga_ls9c_ard_3-2-1_099079_2023-04-22_final.stac-item
2023-05-01 10:07:03	ga_ls9c_ard_3-2-1_098078_2023-05-01_final.stac-item
2023-07-07 10:35:24	ga_ls9c_ard_3-2-1_103072_2023-07-07_final.stac-item
2023-07-27 10:13:08	ga_ls9c_ard_3-2-1_099078_2023-07-27_final.stac-item
2023-08-09 09:39:35	ga_ls9c_ard_3-2-1_094071_2023-08-09_final.stac-item
2023-09-20 10:16:59	ga_ls9c_ard_3-2-1_100071_2023-09-20_final.stac-item
2023-09-29 11:52:49	ga_ls9c_ard_3-2-1_115079_2023-09-29_final.stac-item
2023-10-14 11:07:46	ga_ls9c_ard_3-2-1_108074_2023-10-14_final.stac-item
2023-10-16 10:53:25	ga_ls9c_ard_3-2-1_106069_2023-10-16_final.stac-item
2023-10-23 11:05:12	ga_ls9c_ard_3-2-1_107083_2023-10-23_final.stac-item
2023-11-08 09:23:27	ga_ls9c_ard_3-2-1_091076_2023-11-07_final.stac-item
2023-11-18 09:57:22	ga_ls9c_ard_3-2-1_097068_2023-11-18_final.stac-item
2023-11-29 11:24:12	ga_ls9c_ard_3-2-1_110084_2023-11-29_final.stac-item
2023-12-02 10:11:01	ga_ls9c_ard_3-2-1_099071_2023-12-02_final.stac-item
2023-12-02 11:53:06	ga_ls9c_ard_3-2-1_115079_2023-12-02_final.stac-item
2023-12-25 10:20:03	ga_ls9c_ard_3-2-1_100078_2023-12-25_final.stac-item
2024-01-16 09:45:18	ga_ls9c_ard_3-2-1_094084_2024-01-16_final.stac-item
2024-02-10 11:12:02	ga_ls9c_ard_3-2-1_109069_2024-02-10_final.stac-item
2024-04-01 10:03:45	ga_ls9c_ard_3-2-1_098069_2024-04-01_final.stac-item
2024-04-19 11:32:04	ga_ls9c_ard_3-2-1_112074_2024-04-19_final.stac-item
2024-04-27 09:06:46	ga_ls9c_ard_3-2-1_088082_2024-04-26_final.stac-item
2024-04-30 09:34:27	ga_ls9c_ard_3-2-1_093074_2024-04-30_final.stac-item
2024-05-13 09:06:42	ga_ls9c_ard_3-2-1_088082_2024-05-12_final.stac-item
2024-05-14 09:46:21	ga_ls9c_ard_3-2-1_095073_2024-05-14_final.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