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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

70 results

Time (local)	Label
2013-06-12 10:22:54	ga_ls8c_ard_3-0-0_100081_2013-06-12_final
2013-12-31 09:22:54	ga_ls8c_ard_3-0-0_090087_2013-12-30_final
2014-04-21 10:09:26	ga_ls8c_ard_3-0-0_099068_2014-04-21_final
2014-05-17 09:11:39	ga_ls8c_ard_3-0-0_089079_2014-05-16_final
2014-08-18 10:19:46	ga_ls8c_ard_3-0-0_100078_2014-08-18_final
2015-05-05 09:57:20	ga_ls8c_ard_3-0-0_096086_2015-05-05_final
2015-05-10 10:13:23	ga_ls8c_ard_3-0-0_099080_2015-05-10_final
2015-08-31 10:57:23	ga_ls8c_ard_3-0-0_106080_2015-08-31_final
2015-10-21 09:44:28	ga_ls8c_ard_3-0-0_095067_2015-10-21_final
2015-12-27 10:17:02	ga_ls8c_ard_3-0-0_100071_2015-12-27_final
2016-03-18 11:41:38	ga_ls8c_ard_3-0-0_114067_2016-03-18_final
2016-04-25 11:07:27	ga_ls8c_ard_3-0-0_108075_2016-04-25_final
2016-05-02 11:13:45	ga_ls8c_ard_3-0-0_109075_2016-05-02_final
2016-05-31 09:06:47	ga_ls8c_ard_3-0-0_088082_2016-05-30_final
2016-10-14 09:58:30	ga_ls8c_ard_3-0-0_096086_2016-10-14_final
2016-11-03 09:28:12	ga_ls8c_ard_3-0-0_092072_2016-11-02_final
2016-12-03 09:40:33	ga_ls8c_ard_3-0-0_094072_2016-12-03_final
2017-01-01 09:10:21	ga_ls8c_ard_3-0-0_089074_2016-12-31_final
2017-03-06 10:49:13	ga_ls8c_ard_3-0-0_105075_2017-03-06_final
2017-03-12 10:15:16	ga_ls8c_ard_3-0-0_099083_2017-03-12_final
2017-03-26 10:27:29	ga_ls8c_ard_3-0-0_101083_2017-03-26_final
2017-07-18 10:13:22	ga_ls8c_ard_3-0-0_099078_2017-07-18_final
2017-07-28 09:10:27	ga_ls8c_ard_3-0-0_089075_2017-07-27_final
2017-08-07 09:44:25	ga_ls8c_ard_3-0-0_095067_2017-08-07_final
2017-09-01 09:38:20	ga_ls8c_ard_3-0-0_094067_2017-09-01_final
2017-09-14 09:10:37	ga_ls8c_ard_3-0-0_089075_2017-09-13_final
2017-10-25 10:40:44	ga_ls8c_ard_3-0-0_104068_2017-10-25_final
2017-11-14 10:20:21	ga_ls8c_ard_3-0-0_100079_2017-11-14_final
2018-07-15 09:09:41	ga_ls8c_ard_3-0-0_089075_2018-07-14_final
2018-08-11 10:32:39	ga_ls8c_ard_3-0-0_102081_2018-08-11_final
2018-10-01 09:21:49	ga_ls8c_ard_3-0-0_091073_2018-09-30_final
2019-02-08 10:46:46	ga_ls8c_ard_3-0-0_105069_2019-02-08_final
2019-03-04 09:57:38	ga_ls8c_ard_3-0-0_097070_2019-03-04_final
2019-05-18 09:39:49	ga_ls8c_ard_3-0-0_094072_2019-05-18_final
2019-08-04 11:35:08	ga_ls8c_ard_3-1-0_112081_2019-08-04_final
2019-10-02 11:14:53	ga_ls8c_ard_3-1-0_109076_2019-10-02_final
2019-12-03 09:44:44	ga_ls8c_ard_3-1-0_095067_2019-12-03_final
2019-12-25 09:13:34	ga_ls8c_ard_3-1-0_089082_2019-12-24_final
2020-01-08 09:27:52	ga_ls8c_ard_3-1-0_091087_2020-01-07_final
2020-03-03 11:07:29	ga_ls8c_ard_3-1-0_108074_2020-03-03_final
2020-03-08 11:24:24	ga_ls8c_ard_3-1-0_111070_2020-03-08_final
2020-03-13 10:09:36	ga_ls8c_ard_3-1-0_098084_2020-03-13_final
2020-07-15 10:27:56	ga_ls8c_ard_3-1-0_102068_2020-07-15_final
2020-08-06 11:29:50	ga_ls8c_ard_3-1-0_112068_2020-08-06_final
2020-09-12 10:08:57	ga_ls8c_ard_3-2-1_099066_2020-09-12_final
2020-10-02 11:24:24	ga_ls8c_ard_3-1-0_111069_2020-10-02_final
2020-10-25 11:31:48	ga_ls8c_ard_3-1-0_112072_2020-10-25_final
2021-01-22 11:24:38	ga_ls8c_ard_3-2-0_111070_2021-01-22_final
2021-02-04 09:17:37	ga_ls8c_ard_3-2-0_090077_2021-02-03_final
2021-03-27 11:24:17	ga_ls8c_ard_3-2-0_111070_2021-03-27_final
2021-07-14 10:55:29	ga_ls8c_ard_3-2-0_106075_2021-07-14_final
2021-07-19 09:39:34	ga_ls8c_ard_3-2-0_093086_2021-07-19_final
2021-08-09 11:30:23	ga_ls8c_ard_3-2-0_112069_2021-08-09_final
2021-09-12 11:20:11	ga_ls8c_ard_3-2-0_110074_2021-09-12_final
2021-09-23 09:25:10	ga_ls8c_ard_3-2-0_091080_2021-09-22_final
2021-11-10 09:28:51	ga_ls8c_ard_3-2-0_091089_2021-11-09_final
2021-12-30 10:49:15	ga_ls8c_ard_3-2-1_105074_2021-12-30_final
2022-02-06 10:13:15	ga_ls8c_ard_3-2-1_099077_2022-02-06_final
2022-02-15 10:04:13	ga_ls8c_ard_3-2-1_098070_2022-02-15_final
2022-03-04 09:13:43	ga_ls8c_ard_3-2-1_089083_2022-03-03_final
2022-03-30 11:23:26	ga_ls8c_ard_3-2-1_111068_2022-03-30_final
2022-05-13 10:10:38	ga_ls8c_ard_3-2-1_099071_2022-05-13_final
2022-05-14 10:53:07	ga_ls8c_ard_3-2-1_106069_2022-05-14_final
2023-01-30 09:39:13	ga_ls8c_ard_3-2-1_093084_2023-01-30_final
2023-02-02 10:05:20	ga_ls8c_ard_3-2-1_098072_2023-02-02_final
2023-07-26 10:19:29	ga_ls8c_ard_3-2-1_100078_2023-07-26_final
2023-10-18 09:53:32	ga_ls8c_ard_3-2-1_096074_2023-10-18_final
2023-10-24 10:55:46	ga_ls8c_ard_3-2-1_106075_2023-10-24_final
2023-11-02 09:16:19	ga_ls8c_ard_3-2-1_089089_2023-11-01_final
2023-12-01 10:19:54	ga_ls8c_ard_3-2-1_100078_2023-12-01_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