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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

66 results

Time (local)	Label
2013-05-04 10:15:43	ga_ls8c_ard_3-0-0_099079_2013-05-04_final
2014-11-16 10:55:47	ga_ls8c_ard_3-0-0_106075_2014-11-16_final
2015-01-15 09:40:15	ga_ls8c_ard_3-0-0_094072_2015-01-15_final
2015-02-08 10:33:09	ga_ls8c_ard_3-0-0_102081_2015-02-08_final
2015-04-28 11:23:22	ga_ls8c_ard_3-0-0_111069_2015-04-28_final
2015-05-05 09:57:20	ga_ls8c_ard_3-0-0_096086_2015-05-05_final
2015-10-06 10:33:17	ga_ls8c_ard_3-0-0_102081_2015-10-06_final
2015-12-03 11:08:05	ga_ls8c_ard_3-0-0_108075_2015-12-03_final
2015-12-17 11:18:27	ga_ls8c_ard_3-0-0_110070_2015-12-17_final
2016-01-02 11:18:25	ga_ls8c_ard_3-0-0_110070_2016-01-02_final
2016-02-06 10:09:33	ga_ls8c_ard_3-0-0_099068_2016-02-06_final
2016-03-25 11:52:56	ga_ls8c_ard_3-0-0_115080_2016-03-25_final
2016-05-24 10:39:03	ga_ls8c_ard_3-0-0_103081_2016-05-24_final
2016-06-14 09:21:35	ga_ls8c_ard_3-0-0_090088_2016-06-13_final
2016-08-24 09:29:00	ga_ls8c_ard_3-0-0_091090_2016-08-23_final
2016-11-08 11:24:25	ga_ls8c_ard_3-0-0_111069_2016-11-08_final
2017-02-02 10:48:14	ga_ls8c_ard_3-0-0_105072_2017-02-02_final
2017-02-25 09:20:58	ga_ls8c_ard_3-0-0_090086_2017-02-24_final
2017-07-27 11:41:46	ga_ls8c_ard_3-0-0_114067_2017-07-27_final
2017-08-18 09:32:19	ga_ls8c_ard_3-0-0_092083_2017-08-18_final
2017-09-24 08:10:54	ga_ls8c_ard_3-2-1_079080_2017-09-23_final
2017-09-27 10:19:30	ga_ls8c_ard_3-0-0_100077_2017-09-27_final
2017-11-06 11:08:14	ga_ls8c_ard_3-0-0_108075_2017-11-06_final
2018-01-07 11:18:25	ga_ls8c_ard_3-0-0_110070_2018-01-07_final
2018-04-16 10:09:14	ga_ls8c_ard_3-0-0_099069_2018-04-16_final
2018-04-23 10:18:56	ga_ls8c_ard_3-0-0_100078_2018-04-23_final
2018-06-07 11:22:53	ga_ls8c_ard_3-0-0_111069_2018-06-07_final
2018-10-25 10:13:24	ga_ls8c_ard_3-0-0_099078_2018-10-25_final
2018-11-06 10:39:22	ga_ls8c_ard_3-0-0_103081_2018-11-06_final
2018-12-11 11:07:49	ga_ls8c_ard_3-0-0_108075_2018-12-11_final
2019-01-14 09:16:32	ga_ls8c_ard_3-0-0_090075_2019-01-13_final
2019-01-14 10:58:13	ga_ls8c_ard_3-0-0_106082_2019-01-14_final
2019-05-03 10:26:55	ga_ls8c_ard_3-0-0_101082_2019-05-03_final
2019-06-28 09:34:44	ga_ls8c_ard_3-1-0_093074_2019-06-28_final
2019-07-05 11:19:49	ga_ls8c_ard_3-1-0_110074_2019-07-05_final
2019-07-16 09:22:02	ga_ls8c_ard_3-1-0_091073_2019-07-15_final
2019-10-01 10:33:37	ga_ls8c_ard_3-1-0_102081_2019-10-01_final
2019-11-26 11:17:26	ga_ls8c_ard_3-1-0_110067_2019-11-26_final
2019-12-08 10:09:39	ga_ls8c_ard_3-1-0_098083_2019-12-08_final
2019-12-12 09:40:08	ga_ls8c_ard_3-1-0_094071_2019-12-12_final
2020-03-24 11:25:28	ga_ls8c_ard_3-1-0_111073_2020-03-24_final
2020-06-29 10:33:25	ga_ls8c_ard_3-1-0_102082_2020-06-29_final
2020-08-01 11:14:28	ga_ls8c_ard_3-1-0_109076_2020-08-01_final
2020-09-04 09:22:15	ga_ls8c_ard_3-1-0_091073_2020-09-03_final
2021-02-02 11:05:41	ga_ls8c_ard_3-2-0_108069_2021-02-02_final
2021-03-08 09:21:01	ga_ls8c_ard_3-2-0_090086_2021-03-07_final
2021-06-12 10:55:48	ga_ls8c_ard_3-2-0_106076_2021-06-12_final
2021-08-19 10:29:02	ga_ls8c_ard_3-2-0_102070_2021-08-19_final
2022-02-08 09:56:53	ga_ls8c_ard_3-2-1_097067_2022-02-08_final
2022-03-18 09:22:47	ga_ls8c_ard_3-2-1_091075_2022-03-17_final
2022-05-07 10:49:40	ga_ls8c_ard_3-2-1_105076_2022-05-07_final
2022-05-14 09:21:25	ga_ls8c_ard_3-2-1_090087_2022-05-13_final
2022-05-23 10:49:21	ga_ls8c_ard_3-2-1_105075_2022-05-23_final
2022-05-28 11:07:28	ga_ls8c_ard_3-2-1_108074_2022-05-28_final
2022-07-10 10:50:02	ga_ls8c_ard_3-2-1_105076_2022-07-10_final
2022-10-23 09:07:20	ga_ls8c_ard_3-2-1_088081_2022-10-22_final
2022-11-03 10:28:07	ga_ls8c_ard_3-2-1_101082_2022-11-03_final
2022-12-17 10:47:04	ga_ls8c_ard_3-2-1_105068_2022-12-17_final
2023-03-20 10:19:12	ga_ls8c_ard_3-2-1_100077_2023-03-20_final
2023-03-22 10:02:25	ga_ls8c_ard_3-2-1_098066_2023-03-22_final
2023-03-31 11:40:14	ga_ls8c_ard_3-2-1_113079_2023-03-31_final
2023-04-02 11:25:27	ga_ls8c_ard_3-2-1_111073_2023-04-02_final
2023-07-16 09:39:56	ga_ls8c_ard_3-2-1_094072_2023-07-16_final
2023-08-26 11:14:07	ga_ls8c_ard_3-2-1_109075_2023-08-26_final
2023-11-15 10:17:30	ga_ls8c_ard_3-2-1_100072_2023-11-15_final
2023-11-21 09:40:04	ga_ls8c_ard_3-2-1_094071_2023-11-21_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