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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

60 results

Time (local)	Label
2013-08-23 09:36:17	ga_ls8c_ard_3-0-0_092088_2013-08-23_final
2013-11-03 10:21:26	ga_ls8c_ard_3-0-0_100078_2013-11-03_final
2014-02-03 10:41:52	ga_ls8c_ard_3-0-0_104069_2014-02-03_final
2014-05-11 11:27:17	ga_ls8c_ard_3-0-0_111078_2014-05-11_final
2014-07-25 09:26:09	ga_ls8c_ard_3-0-0_092068_2014-07-24_final
2014-08-19 09:25:21	ga_ls8c_ard_3-0-0_091081_2014-08-18_final
2015-03-25 09:57:29	ga_ls8c_ard_3-0-0_097070_2015-03-25_final
2015-08-27 09:39:37	ga_ls8c_ard_3-0-0_094071_2015-08-27_final
2015-10-27 10:47:06	ga_ls8c_ard_3-0-0_105069_2015-10-27_final
2015-12-05 10:52:32	ga_ls8c_ard_3-0-0_106067_2015-12-05_final
2015-12-17 11:19:38	ga_ls8c_ard_3-0-0_110073_2015-12-17_final
2016-01-16 11:30:45	ga_ls8c_ard_3-0-0_112070_2016-01-16_final
2016-01-27 09:34:31	ga_ls8c_ard_3-0-0_093073_2016-01-27_final
2016-05-09 09:42:59	ga_ls8c_ard_3-0-0_094080_2016-05-09_final
2016-09-10 10:07:33	ga_ls8c_ard_3-0-0_098078_2016-09-10_final
2016-09-27 10:46:50	ga_ls8c_ard_3-0-0_105068_2016-09-27_final
2016-10-02 09:34:30	ga_ls8c_ard_3-0-0_092088_2016-10-02_final
2016-11-22 10:04:18	ga_ls8c_ard_3-0-0_097085_2016-11-22_final
2017-02-02 10:47:03	ga_ls8c_ard_3-0-0_105069_2017-02-02_final
2017-06-20 11:23:25	ga_ls8c_ard_3-0-0_111068_2017-06-20_final
2017-10-23 09:18:12	ga_ls8c_ard_3-0-0_090078_2017-10-22_final
2017-12-09 10:08:52	ga_ls8c_ard_3-2-1_099066_2017-12-09_final
2018-02-01 09:35:07	ga_ls8c_ard_3-0-0_093075_2018-02-01_final
2018-08-20 10:27:21	ga_ls8c_ard_3-0-0_101083_2018-08-20_final
2018-10-17 09:28:19	ga_ls8c_ard_3-0-0_091089_2018-10-16_final
2018-11-01 10:16:49	ga_ls8c_ard_3-0-0_100071_2018-11-01_final
2018-11-20 10:48:56	ga_ls8c_ard_3-0-0_105074_2018-11-20_final
2018-11-25 09:28:35	ga_ls8c_ard_3-0-0_092074_2018-11-24_final
2019-02-02 11:25:03	ga_ls8c_ard_3-0-0_111072_2019-02-02_final
2019-02-14 10:09:40	ga_ls8c_ard_3-0-0_099069_2019-02-14_final
2019-03-12 09:15:43	ga_ls8c_ard_3-1-0_089089_2019-03-11_final
2019-09-06 10:39:39	ga_ls8c_ard_3-1-0_103081_2019-09-06_final
2019-09-19 10:07:38	ga_ls8c_ard_3-1-0_098078_2019-09-19_final
2019-09-28 09:58:42	ga_ls8c_ard_3-1-0_097071_2019-09-28_final
2019-11-26 11:23:25	ga_ls8c_ard_3-1-0_110082_2019-11-26_final
2020-01-01 09:21:19	ga_ls8c_ard_3-1-0_090086_2019-12-31_final
2020-01-24 09:27:24	ga_ls8c_ard_3-1-0_091086_2020-01-23_final
2020-01-26 09:12:38	ga_ls8c_ard_3-1-0_089080_2020-01-25_final
2020-06-08 10:12:42	ga_ls8c_ard_3-1-0_099077_2020-06-08_final
2020-06-30 09:35:01	ga_ls8c_ard_3-1-0_093075_2020-06-30_final
2020-07-11 09:17:45	ga_ls8c_ard_3-1-0_090078_2020-07-10_final
2020-09-21 10:04:25	ga_ls8c_ard_3-1-0_098070_2020-09-21_final
2020-12-22 10:29:36	ga_ls8c_ard_3-2-0_102071_2020-12-22_final
2021-08-11 09:40:21	ga_ls8c_ard_3-2-0_094072_2021-08-11_final
2021-11-18 10:13:27	ga_ls8c_ard_3-2-0_099077_2021-11-18_final
2021-12-29 10:03:37	ga_ls8c_ard_3-2-1_098068_2021-12-29_final
2022-01-22 10:53:22	ga_ls8c_ard_3-2-1_106069_2022-01-22_final
2022-02-20 10:23:07	ga_ls8c_ard_3-2-1_101071_2022-02-20_final
2022-05-07 09:11:11	ga_ls8c_ard_3-2-1_089077_2022-05-06_final
2022-06-09 09:57:53	ga_ls8c_ard_3-2-1_096085_2022-06-09_final
2023-02-16 10:18:21	ga_ls8c_ard_3-2-1_100074_2023-02-16_final
2023-02-20 09:51:58	ga_ls8c_ard_3-2-1_096070_2023-02-20_final
2023-04-27 11:23:24	ga_ls8c_ard_3-2-1_110084_2023-04-27_final
2023-06-25 09:27:59	ga_ls8c_ard_3-2-1_091089_2023-06-24_final
2023-07-25 09:35:00	ga_ls8c_ard_3-2-1_093075_2023-07-25_final
2023-09-03 10:25:28	ga_ls8c_ard_3-2-1_101077_2023-09-03_final
2023-09-09 09:46:48	ga_ls8c_ard_3-2-1_095073_2023-09-09_final
2023-10-15 09:22:15	ga_ls8c_ard_3-2-1_091073_2023-10-14_final
2023-10-15 09:22:15	ga_ls8c_ard_3-2-1_091073_2023-10-14_nrt
2023-10-28 10:33:28	ga_ls8c_ard_3-2-1_102081_2023-10-28_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