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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
2013-06-13 09:25:16	ga_ls8c_ard_3-0-0_091076_2013-06-12_final
2013-07-27 09:46:23	ga_ls8c_ard_3-0-0_095067_2013-07-27_final
2013-08-24 10:15:10	ga_ls8c_ard_3-0-0_099077_2013-08-24_final
2014-02-04 11:24:19	ga_ls8c_ard_3-0-0_111067_2014-02-04_final
2014-05-11 09:44:00	ga_ls8c_ard_3-0-0_095067_2014-05-11_final
2014-09-23 11:29:58	ga_ls8c_ard_3-0-0_112068_2014-09-23_final
2015-01-03 09:17:56	ga_ls8c_ard_3-1-0_090078_2015-01-02_final
2015-05-02 09:26:05	ga_ls8c_ard_3-0-0_091085_2015-05-01_final
2015-11-17 09:27:59	ga_ls8c_ard_3-0-0_092072_2015-11-16_final
2016-03-13 09:44:15	ga_ls8c_ard_3-0-0_095067_2016-03-13_final
2016-09-30 11:18:08	ga_ls8c_ard_3-0-0_110069_2016-09-30_final
2017-02-02 10:47:03	ga_ls8c_ard_3-0-0_105069_2017-02-02_final
2017-02-28 09:44:16	ga_ls8c_ard_3-0-0_095067_2017-02-28_final
2017-03-20 09:22:57	ga_ls8c_ard_3-0-0_091076_2017-03-19_final
2017-08-18 09:33:31	ga_ls8c_ard_3-0-0_092086_2017-08-18_final
2017-11-14 10:19:33	ga_ls8c_ard_3-0-0_100077_2017-11-14_final
2018-03-14 09:28:14	ga_ls8c_ard_3-0-0_092074_2018-03-13_final
2018-03-17 09:56:19	ga_ls8c_ard_3-0-0_097067_2018-03-17_final
2018-03-26 09:50:53	ga_ls8c_ard_3-0-0_096069_2018-03-26_final
2018-03-30 11:07:00	ga_ls8c_ard_3-0-0_108074_2018-03-30_final
2018-06-23 09:43:23	ga_ls8c_ard_3-0-0_095067_2018-06-23_final
2018-07-05 10:08:13	ga_ls8c_ard_3-0-0_099067_2018-07-05_final
2018-08-10 09:43:48	ga_ls8c_ard_3-0-0_095067_2018-08-10_final
2018-11-11 09:17:02	ga_ls8c_ard_3-0-0_090076_2018-11-10_final
2018-12-12 10:14:59	ga_ls8c_ard_3-0-0_099082_2018-12-12_final
2018-12-16 11:24:22	ga_ls8c_ard_3-0-0_111070_2018-12-16_final
2018-12-20 09:22:45	ga_ls8c_ard_3-0-0_091075_2018-12-19_final
2019-01-19 09:33:52	ga_ls8c_ard_3-0-0_093072_2019-01-19_final
2019-01-21 09:22:18	ga_ls8c_ard_3-0-0_091074_2019-01-20_final
2019-02-08 10:48:46	ga_ls8c_ard_3-0-0_105074_2019-02-08_final
2019-03-28 10:46:10	ga_ls8c_ard_3-1-0_105068_2019-03-28_final
2019-05-04 09:28:06	ga_ls8c_ard_3-0-0_092074_2019-05-03_final
2019-06-05 09:33:12	ga_ls8c_ard_3-0-0_092086_2019-06-05_final
2019-08-03 10:49:52	ga_ls8c_ard_3-1-0_105076_2019-08-03_final
2020-01-15 09:28:50	ga_ls8c_ard_3-1-0_092074_2020-01-14_final
2020-05-24 10:52:14	ga_ls8c_ard_3-1-0_106068_2020-05-24_final
2021-06-23 10:39:18	ga_ls8c_ard_3-2-0_103081_2021-06-23_final
2021-07-08 09:58:05	ga_ls8c_ard_3-2-0_096086_2021-07-08_final
2021-08-02 09:44:28	ga_ls8c_ard_3-2-0_095067_2021-08-02_final
2021-11-22 09:44:45	ga_ls8c_ard_3-2-0_095067_2021-11-22_final
2022-01-11 09:34:41	ga_ls8c_ard_3-2-1_093073_2022-01-11_final
2022-03-03 10:04:10	ga_ls8c_ard_3-2-1_098070_2022-03-03_final
2022-04-27 10:08:30	ga_ls8c_ard_3-2-1_099066_2022-04-27_final
2022-05-10 11:17:48	ga_ls8c_ard_3-2-1_110069_2022-05-10_final
2022-06-05 10:19:21	ga_ls8c_ard_3-2-1_100077_2022-06-05_final
2022-07-26 10:49:46	ga_ls8c_ard_3-2-1_105075_2022-07-26_final
2022-11-16 09:58:18	ga_ls8c_ard_3-2-1_096085_2022-11-16_final
2022-12-09 10:04:06	ga_ls8c_ard_3-2-1_097084_2022-12-09_final
2022-12-11 11:25:01	ga_ls8c_ard_3-2-1_111070_2022-12-11_final
2023-08-08 11:23:57	ga_ls8c_ard_3-2-1_111069_2023-08-08_final
2023-10-24 10:52:58	ga_ls8c_ard_3-2-1_106068_2023-10-24_final
2024-02-14 11:37:44	ga_ls8c_ard_3-2-1_113072_2024-02-14_final
2024-03-28 11:17:30	ga_ls8c_ard_3-2-1_110069_2024-03-28_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years