Search ga_ls7e_ard_3 whole collection

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

First 100 results (query limit)

Time (local)	Label
2010-05-03 10:57:44	ga_ls7e_ard_3-0-0_108069_2010-05-03_final
2010-05-05 10:45:22	ga_ls7e_ard_3-0-0_106069_2010-05-05_final
2010-05-06 09:49:44	ga_ls7e_ard_3-0-0_097069_2010-05-06_final
2010-06-29 10:51:57	ga_ls7e_ard_3-0-0_107070_2010-06-29_final
2010-06-30 09:55:56	ga_ls7e_ard_3-0-0_098069_2010-06-30_final
2010-07-01 10:39:12	ga_ls7e_ard_3-0-0_105069_2010-07-01_final
2010-07-22 10:57:46	ga_ls7e_ard_3-0-0_108069_2010-07-22_final
2010-07-23 10:02:09	ga_ls7e_ard_3-0-0_099069_2010-07-23_final
2011-01-16 10:46:53	ga_ls7e_ard_3-0-0_106070_2011-01-16_final
2011-01-17 09:50:52	ga_ls7e_ard_3-0-0_097069_2011-01-17_final
2011-01-18 10:34:08	ga_ls7e_ard_3-0-0_104069_2011-01-18_final
2011-01-18 10:34:32	ga_ls7e_ard_3-1-0_104070_2011-01-18_final
2016-07-03 10:37:13	ga_ls7e_ard_3-0-0_103069_2016-07-03_final
2016-07-03 10:37:37	ga_ls7e_ard_3-0-0_103070_2016-07-03_final
2016-07-04 11:20:52	ga_ls7e_ard_3-0-0_110070_2016-07-04_final
2016-07-06 11:08:07	ga_ls7e_ard_3-0-0_108069_2016-07-06_final
2016-07-06 11:08:31	ga_ls7e_ard_3-0-0_108070_2016-07-06_final
2016-07-17 10:49:35	ga_ls7e_ard_3-0-0_105069_2016-07-17_final
2016-07-17 10:49:59	ga_ls7e_ard_3-0-0_105070_2016-07-17_final
2016-07-19 10:37:13	ga_ls7e_ard_3-0-0_103069_2016-07-19_final
2016-07-19 10:37:37	ga_ls7e_ard_3-0-0_103070_2016-07-19_final
2016-08-27 10:43:30	ga_ls7e_ard_3-0-0_104069_2016-08-27_final
2016-08-29 10:31:09	ga_ls7e_ard_3-0-0_102069_2016-08-29_final
2016-08-29 10:31:33	ga_ls7e_ard_3-0-0_102070_2016-08-29_final
2016-08-30 11:14:49	ga_ls7e_ard_3-0-0_109070_2016-08-30_final
2016-09-04 09:54:29	ga_ls7e_ard_3-0-0_096070_2016-09-04_final
2016-09-05 10:37:21	ga_ls7e_ard_3-0-0_103069_2016-09-05_final
2016-09-05 10:37:45	ga_ls7e_ard_3-0-0_103070_2016-09-05_final
2017-01-09 10:49:13	ga_ls7e_ard_3-0-0_105069_2017-01-09_final
2017-01-09 10:49:37	ga_ls7e_ard_3-0-0_105070_2017-01-09_final
2017-01-10 09:53:59	ga_ls7e_ard_3-0-0_096070_2017-01-10_final
2018-03-19 10:35:48	ga_ls7e_ard_3-0-0_103069_2018-03-19_final
2018-03-19 10:36:12	ga_ls7e_ard_3-0-0_103070_2018-03-19_final
2018-03-22 11:06:40	ga_ls7e_ard_3-0-0_108069_2018-03-22_final
2018-03-22 11:07:04	ga_ls7e_ard_3-0-0_108070_2018-03-22_final
2018-05-13 10:41:05	ga_ls7e_ard_3-0-0_104069_2018-05-13_final
2018-05-15 10:28:41	ga_ls7e_ard_3-0-0_102069_2018-05-15_final
2018-07-06 10:03:03	ga_ls7e_ard_3-0-0_098069_2018-07-06_final
2018-07-07 10:46:17	ga_ls7e_ard_3-0-0_105069_2018-07-07_final
2018-07-08 09:51:02	ga_ls7e_ard_3-0-0_096070_2018-07-08_final
2018-09-20 10:26:17	ga_ls7e_ard_3-0-0_102069_2018-09-20_final
2018-09-21 11:09:55	ga_ls7e_ard_3-0-0_109070_2018-09-21_final
2018-10-06 10:25:54	ga_ls7e_ard_3-0-0_102069_2018-10-06_final
2018-10-10 10:01:04	ga_ls7e_ard_3-0-0_098069_2018-10-10_final
2018-10-17 10:07:04	ga_ls7e_ard_3-0-0_099069_2018-10-17_final
2018-10-18 10:50:19	ga_ls7e_ard_3-0-0_106069_2018-10-18_final
2018-10-19 09:54:40	ga_ls7e_ard_3-0-0_097069_2018-10-19_final
2018-10-19 09:55:04	ga_ls7e_ard_3-0-0_097070_2018-10-19_final
2018-10-20 10:37:55	ga_ls7e_ard_3-0-0_104069_2018-10-20_final
2018-10-26 10:00:43	ga_ls7e_ard_3-0-0_098069_2018-10-26_final
2018-10-27 10:43:57	ga_ls7e_ard_3-0-0_105069_2018-10-27_final
2018-10-29 10:31:33	ga_ls7e_ard_3-0-0_103069_2018-10-29_final
2018-11-01 11:02:23	ga_ls7e_ard_3-0-0_108069_2018-11-01_final
2018-11-02 10:06:44	ga_ls7e_ard_3-0-0_099069_2018-11-02_final
2018-11-11 10:00:21	ga_ls7e_ard_3-0-0_098069_2018-11-11_final
2018-11-12 10:43:36	ga_ls7e_ard_3-0-0_105069_2018-11-12_final
2018-11-14 10:31:11	ga_ls7e_ard_3-0-0_103069_2018-11-14_final
2018-11-14 10:31:35	ga_ls7e_ard_3-0-0_103070_2018-11-14_final
2018-11-18 10:06:22	ga_ls7e_ard_3-0-0_099069_2018-11-18_final
2018-11-27 09:59:58	ga_ls7e_ard_3-0-0_098069_2018-11-27_final
2018-11-27 10:00:22	ga_ls7e_ard_3-0-0_098070_2018-11-27_final
2018-12-04 10:05:58	ga_ls7e_ard_3-0-0_099069_2018-12-04_final
2018-12-05 10:49:12	ga_ls7e_ard_3-0-0_106069_2018-12-05_final
2018-12-05 10:49:35	ga_ls7e_ard_3-0-0_106070_2018-12-05_final
2018-12-06 09:53:33	ga_ls7e_ard_3-0-0_097069_2018-12-06_final
2018-12-13 09:59:32	ga_ls7e_ard_3-0-0_098069_2018-12-13_final
2018-12-14 10:42:46	ga_ls7e_ard_3-0-0_105069_2018-12-14_final
2018-12-16 10:30:21	ga_ls7e_ard_3-0-0_103069_2018-12-16_final
2018-12-17 11:13:59	ga_ls7e_ard_3-0-0_110070_2018-12-17_final
2018-12-22 09:53:06	ga_ls7e_ard_3-0-0_097069_2018-12-22_final
2018-12-23 10:36:20	ga_ls7e_ard_3-0-0_104069_2018-12-23_final
2018-12-25 10:23:54	ga_ls7e_ard_3-0-0_102069_2018-12-25_final
2018-12-25 10:24:18	ga_ls7e_ard_3-0-0_102070_2018-12-25_final
2019-01-04 11:00:41	ga_ls7e_ard_3-0-0_108069_2019-01-04_final
2019-01-05 10:05:02	ga_ls7e_ard_3-0-0_099069_2019-01-05_final
2019-01-05 10:05:26	ga_ls7e_ard_3-0-0_099070_2019-01-05_final
2019-01-06 10:48:16	ga_ls7e_ard_3-0-0_106069_2019-01-06_final
2019-01-06 10:48:40	ga_ls7e_ard_3-0-0_106070_2019-01-06_final
2019-01-07 09:52:37	ga_ls7e_ard_3-0-0_097069_2019-01-07_final
2019-01-07 09:53:01	ga_ls7e_ard_3-0-0_097070_2019-01-07_final
2019-01-21 10:04:32	ga_ls7e_ard_3-0-0_099069_2019-01-21_final
2019-01-22 10:47:45	ga_ls7e_ard_3-0-0_106069_2019-01-22_final
2019-01-24 10:35:20	ga_ls7e_ard_3-0-0_104069_2019-01-24_final
2019-04-11 10:01:57	ga_ls7e_ard_3-0-0_099069_2019-04-11_final
2019-04-12 10:45:11	ga_ls7e_ard_3-0-0_106069_2019-04-12_final
2019-04-13 09:49:55	ga_ls7e_ard_3-0-0_097070_2019-04-13_final
2019-04-14 10:32:45	ga_ls7e_ard_3-0-0_104069_2019-04-14_final
2019-04-14 10:33:09	ga_ls7e_ard_3-1-0_104070_2019-04-14_final
2019-04-23 10:26:14	ga_ls7e_ard_3-0-0_103069_2019-04-23_final
2019-04-26 10:57:02	ga_ls7e_ard_3-0-0_108069_2019-04-26_final
2019-04-27 10:01:22	ga_ls7e_ard_3-0-0_099069_2019-04-27_final
2019-04-27 10:01:46	ga_ls7e_ard_3-0-0_099070_2019-04-27_final
2019-04-28 10:44:35	ga_ls7e_ard_3-0-0_106069_2019-04-28_final
2019-05-06 09:54:51	ga_ls7e_ard_3-0-0_098069_2019-05-06_final
2019-05-07 10:38:04	ga_ls7e_ard_3-0-0_105069_2019-05-07_final
2019-05-09 10:25:38	ga_ls7e_ard_3-0-0_103069_2019-05-09_final
2019-05-22 09:54:13	ga_ls7e_ard_3-0-0_098069_2019-05-22_final
2019-05-23 10:37:26	ga_ls7e_ard_3-0-0_105069_2019-05-23_final
2019-05-30 10:43:23	ga_ls7e_ard_3-0-0_106069_2019-05-30_final
2019-06-01 10:30:57	ga_ls7e_ard_3-0-0_104069_2019-06-01_final

Return to ga_ls7e_ard_3 whole collection overview

ga_ls7e_ard_3: Geoscience Australia Landsat 7 Enhanced Thematic Mapper Plus Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years