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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

50 results

Time (local)	Label
2014-06-05 09:37:52	ga_ls8c_ard_3-0-0_094067_2014-06-05_final
2014-06-10 11:41:19	ga_ls8c_ard_3-0-0_113082_2014-06-10_final
2014-12-25 09:21:47	ga_ls8c_ard_3-0-0_091072_2014-12-24_final
2015-01-02 10:13:09	ga_ls8c_ard_3-0-0_099077_2015-01-02_final
2015-01-05 10:41:16	ga_ls8c_ard_3-0-0_104070_2015-01-05_final
2015-08-20 09:33:47	ga_ls8c_ard_3-0-0_093072_2015-08-20_final
2015-09-23 09:22:52	ga_ls8c_ard_3-0-0_091075_2015-09-22_final
2016-03-26 09:16:49	ga_ls8c_ard_3-0-0_090076_2016-03-25_final
2017-01-22 09:27:59	ga_ls8c_ard_3-0-0_092072_2017-01-21_final
2017-07-24 09:32:21	ga_ls8c_ard_3-0-0_093068_2017-07-24_final
2017-10-05 09:28:55	ga_ls8c_ard_3-0-0_092074_2017-10-04_final
2017-11-22 09:28:04	ga_ls8c_ard_3-0-0_092072_2017-11-21_final
2018-02-01 09:33:55	ga_ls8c_ard_3-0-0_093072_2018-02-01_final
2018-02-10 09:27:42	ga_ls8c_ard_3-0-0_092072_2018-02-09_final
2018-08-16 09:09:57	ga_ls8c_ard_3-0-0_089075_2018-08-15_final
2018-12-27 09:28:32	ga_ls8c_ard_3-0-0_092074_2018-12-26_final
2019-08-04 11:30:21	ga_ls8c_ard_3-1-0_112069_2019-08-04_final
2019-10-27 09:28:15	ga_ls8c_ard_3-1-0_092072_2019-10-26_final
2019-11-17 09:45:57	ga_ls8c_ard_3-1-0_095070_2019-11-17_final
2019-12-14 09:28:58	ga_ls8c_ard_3-2-0_092074_2019-12-13_final
2020-10-17 10:46:21	ga_ls8c_ard_3-1-0_104082_2020-10-17_final
2021-02-04 10:52:55	ga_ls8c_ard_3-2-0_106068_2021-02-04_final
2021-05-27 09:16:24	ga_ls8c_ard_3-2-0_090075_2021-05-26_final
2021-06-30 09:06:14	ga_ls8c_ard_3-2-0_088080_2021-06-29_final
2021-10-14 09:38:39	ga_ls8c_ard_3-2-0_094067_2021-10-14_final
2021-11-17 09:29:00	ga_ls8c_ard_3-2-0_092074_2021-11-16_final
2021-11-20 11:37:59	ga_ls8c_ard_3-2-0_113072_2021-11-20_final
2021-12-29 10:03:37	ga_ls8c_ard_3-2-1_098068_2021-12-29_final
2022-04-10 09:28:28	ga_ls8c_ard_3-2-1_092074_2022-04-09_final
2022-05-30 09:16:39	ga_ls8c_ard_3-2-1_090075_2022-05-29_final
2022-10-02 10:24:31	ga_ls8c_ard_3-2-1_101073_2022-10-02_final
2022-10-12 09:22:12	ga_ls8c_ard_3-2-1_091072_2022-10-11_final
2022-11-20 09:29:11	ga_ls8c_ard_3-2-1_092074_2022-11-19_final
2022-12-06 09:29:13	ga_ls8c_ard_3-2-1_092074_2022-12-05_final
2022-12-31 09:22:06	ga_ls8c_ard_3-2-1_091072_2022-12-30_final
2023-02-08 09:29:01	ga_ls8c_ard_3-2-1_092074_2023-02-07_final
2023-03-19 09:39:09	ga_ls8c_ard_3-2-1_093085_2023-03-19_final
2023-07-13 09:11:25	ga_ls8c_ard_3-2-1_089078_2023-07-12_final
2023-07-19 10:13:13	ga_ls8c_ard_3-2-1_099078_2023-07-19_final
2023-08-22 11:37:38	ga_ls8c_ard_3-2-1_113072_2023-08-22_final
2023-10-06 09:27:58	ga_ls8c_ard_3-2-1_092072_2023-10-05_final
2024-01-17 09:33:46	ga_ls8c_ard_3-2-1_093071_2024-01-17_final
2024-01-19 09:22:59	ga_ls8c_ard_3-2-1_091075_2024-01-18_final
2024-01-21 09:10:12	ga_ls8c_ard_3-2-1_089074_2024-01-20_final
2024-02-11 09:28:46	ga_ls8c_ard_3-2-1_092074_2024-02-10_final
2024-02-18 09:33:43	ga_ls8c_ard_3-2-1_093071_2024-02-18_final
2024-03-05 09:34:21	ga_ls8c_ard_3-2-1_093073_2024-03-05_final
2024-03-19 11:23:52	ga_ls8c_ard_3-2-1_111069_2024-03-19_final
2024-03-23 09:21:48	ga_ls8c_ard_3-2-1_091073_2024-03-22_final
2024-03-26 11:31:30	ga_ls8c_ard_3-2-1_112073_2024-03-26_final

Return to ga_ls8c_ard_3 whole collection overview

ga_ls8c_ard_3: Geoscience Australia Landsat 8 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