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
2017-03-21 10:55:23	ga_ls7e_ard_3-0-0_106069_2017-03-21_final
2017-03-21 10:55:47	ga_ls7e_ard_3-0-0_106070_2017-03-21_final
2017-03-22 09:59:46	ga_ls7e_ard_3-0-0_097069_2017-03-22_final
2017-03-22 10:00:10	ga_ls7e_ard_3-0-0_097070_2017-03-22_final
2017-03-23 10:43:02	ga_ls7e_ard_3-0-0_104069_2017-03-23_final
2017-03-23 10:43:26	ga_ls7e_ard_3-1-0_104070_2017-03-23_final
2017-03-25 10:30:41	ga_ls7e_ard_3-0-0_102069_2017-03-25_final
2017-03-25 10:31:05	ga_ls7e_ard_3-0-0_102070_2017-03-25_final
2017-03-26 11:14:21	ga_ls7e_ard_3-0-0_109070_2017-03-26_final
2017-03-28 11:02:00	ga_ls7e_ard_3-0-0_107070_2017-03-28_final
2017-04-23 10:00:22	ga_ls7e_ard_3-0-0_097070_2017-04-23_final
2017-04-24 10:43:14	ga_ls7e_ard_3-0-0_104069_2017-04-24_final
2017-04-24 10:43:38	ga_ls7e_ard_3-1-0_104070_2017-04-24_final
2017-04-27 11:14:33	ga_ls7e_ard_3-0-0_109070_2017-04-27_final
2017-04-29 11:02:12	ga_ls7e_ard_3-0-0_107070_2017-04-29_final
2017-04-30 10:06:11	ga_ls7e_ard_3-0-0_098069_2017-04-30_final
2017-04-30 10:06:35	ga_ls7e_ard_3-0-0_098070_2017-04-30_final
2017-05-01 10:49:27	ga_ls7e_ard_3-0-0_105069_2017-05-01_final
2017-05-01 10:49:51	ga_ls7e_ard_3-0-0_105070_2017-05-01_final
2017-05-02 09:54:14	ga_ls7e_ard_3-0-0_096070_2017-05-02_final
2017-05-03 10:37:06	ga_ls7e_ard_3-0-0_103069_2017-05-03_final
2017-05-03 10:37:30	ga_ls7e_ard_3-0-0_103070_2017-05-03_final
2017-06-05 11:20:53	ga_ls7e_ard_3-0-0_110070_2017-06-05_final
2017-06-07 11:08:08	ga_ls7e_ard_3-0-0_108069_2017-06-07_final
2017-06-07 11:08:32	ga_ls7e_ard_3-0-0_108070_2017-06-07_final
2017-08-04 10:06:23	ga_ls7e_ard_3-0-0_098069_2017-08-04_final
2017-08-05 10:49:38	ga_ls7e_ard_3-0-0_105069_2017-08-05_final
2017-08-05 10:50:02	ga_ls7e_ard_3-0-0_105070_2017-08-05_final
2017-08-07 10:37:16	ga_ls7e_ard_3-0-0_103069_2017-08-07_final
2017-08-07 10:37:40	ga_ls7e_ard_3-0-0_103070_2017-08-07_final
2017-09-06 10:49:37	ga_ls7e_ard_3-0-0_105069_2017-09-06_final
2017-09-06 10:50:01	ga_ls7e_ard_3-0-0_105070_2017-09-06_final
2017-09-08 10:37:15	ga_ls7e_ard_3-0-0_103069_2017-09-08_final
2017-09-08 10:37:39	ga_ls7e_ard_3-0-0_103070_2017-09-08_final
2017-09-29 10:55:47	ga_ls7e_ard_3-0-0_106069_2017-09-29_final
2017-09-30 10:00:10	ga_ls7e_ard_3-0-0_097069_2017-09-30_final
2017-09-30 10:00:34	ga_ls7e_ard_3-0-0_097070_2017-09-30_final
2017-10-26 10:37:17	ga_ls7e_ard_3-0-0_103069_2017-10-26_final
2017-10-26 10:37:41	ga_ls7e_ard_3-0-0_103070_2017-10-26_final
2017-10-29 11:08:11	ga_ls7e_ard_3-0-0_108069_2017-10-29_final
2017-10-29 11:08:35	ga_ls7e_ard_3-0-0_108070_2017-10-29_final
2017-10-30 10:12:34	ga_ls7e_ard_3-0-0_099069_2017-10-30_final
2017-10-30 10:12:58	ga_ls7e_ard_3-0-0_099070_2017-10-30_final
2017-10-31 10:55:49	ga_ls7e_ard_3-0-0_106069_2017-10-31_final
2017-11-24 10:06:17	ga_ls7e_ard_3-0-0_098069_2017-11-24_final
2017-11-24 10:06:41	ga_ls7e_ard_3-0-0_098070_2017-11-24_final
2017-11-25 10:49:33	ga_ls7e_ard_3-0-0_105069_2017-11-25_final
2017-11-25 10:49:57	ga_ls7e_ard_3-0-0_105070_2017-11-25_final
2017-11-27 10:37:10	ga_ls7e_ard_3-0-0_103069_2017-11-27_final
2017-11-28 11:20:50	ga_ls7e_ard_3-0-0_110070_2017-11-28_final
2017-12-29 10:36:51	ga_ls7e_ard_3-0-0_103069_2017-12-29_final
2018-01-02 10:12:05	ga_ls7e_ard_3-0-0_099069_2018-01-02_final
2018-01-02 10:12:29	ga_ls7e_ard_3-0-0_099070_2018-01-02_final
2018-01-14 10:36:38	ga_ls7e_ard_3-0-0_103069_2018-01-14_final
2018-01-14 10:37:02	ga_ls7e_ard_3-0-0_103070_2018-01-14_final
2018-01-18 10:12:15	ga_ls7e_ard_3-0-0_099070_2018-01-18_final
2018-01-19 10:55:06	ga_ls7e_ard_3-0-0_106069_2018-01-19_final
2018-01-23 10:30:19	ga_ls7e_ard_3-0-0_102069_2018-01-23_final
2018-01-23 10:30:43	ga_ls7e_ard_3-0-0_102070_2018-01-23_final
2018-01-27 10:05:55	ga_ls7e_ard_3-0-0_098070_2018-01-27_final
2018-01-29 09:53:32	ga_ls7e_ard_3-0-0_096070_2018-01-29_final
2018-03-10 10:42:06	ga_ls7e_ard_3-0-0_104069_2018-03-10_final
2018-03-10 10:42:30	ga_ls7e_ard_3-1-0_104070_2018-03-10_final
2018-03-12 10:30:07	ga_ls7e_ard_3-0-0_102070_2018-03-12_final
2018-04-01 10:04:43	ga_ls7e_ard_3-0-0_098069_2018-04-01_final
2018-04-01 10:05:07	ga_ls7e_ard_3-0-0_098070_2018-04-01_final
2018-04-02 10:47:58	ga_ls7e_ard_3-0-0_105069_2018-04-02_final
2018-04-02 10:48:22	ga_ls7e_ard_3-0-0_105070_2018-04-02_final
2018-04-03 09:52:43	ga_ls7e_ard_3-0-0_096070_2018-04-03_final
2018-04-23 11:06:09	ga_ls7e_ard_3-0-0_108069_2018-04-23_final
2018-04-23 11:06:33	ga_ls7e_ard_3-0-0_108070_2018-04-23_final
2018-04-24 10:10:31	ga_ls7e_ard_3-0-0_099069_2018-04-24_final
2018-04-24 10:10:55	ga_ls7e_ard_3-0-0_099070_2018-04-24_final
2018-06-07 10:34:30	ga_ls7e_ard_3-0-0_103069_2018-06-07_final
2018-06-08 11:18:09	ga_ls7e_ard_3-0-0_110070_2018-06-08_final
2018-06-10 11:05:21	ga_ls7e_ard_3-0-0_108069_2018-06-10_final
2018-06-11 10:09:43	ga_ls7e_ard_3-0-0_099069_2018-06-11_final
2018-06-12 10:52:57	ga_ls7e_ard_3-0-0_106069_2018-06-12_final
2018-06-13 09:57:19	ga_ls7e_ard_3-0-0_097069_2018-06-13_final
2018-06-24 11:17:51	ga_ls7e_ard_3-0-0_110070_2018-06-24_final
2018-06-26 11:05:03	ga_ls7e_ard_3-0-0_108069_2018-06-26_final
2018-06-26 11:05:27	ga_ls7e_ard_3-0-0_108070_2018-06-26_final
2018-07-18 10:27:33	ga_ls7e_ard_3-0-0_102069_2018-07-18_final
2018-07-18 10:27:57	ga_ls7e_ard_3-0-0_102070_2018-07-18_final
2018-07-26 11:17:15	ga_ls7e_ard_3-0-0_110070_2018-07-26_final
2018-07-28 11:04:27	ga_ls7e_ard_3-0-0_108069_2018-07-28_final
2018-07-28 11:04:51	ga_ls7e_ard_3-0-0_108070_2018-07-28_final
2018-07-29 10:08:49	ga_ls7e_ard_3-0-0_099069_2018-07-29_final
2018-07-29 10:09:13	ga_ls7e_ard_3-0-0_099070_2018-07-29_final
2018-07-30 10:52:03	ga_ls7e_ard_3-0-0_106069_2018-07-30_final
2018-07-31 09:56:25	ga_ls7e_ard_3-0-0_097069_2018-07-31_final
2018-08-25 09:50:10	ga_ls7e_ard_3-0-0_096070_2018-08-25_final
2018-08-26 10:33:00	ga_ls7e_ard_3-0-0_103069_2018-08-26_final
2018-08-27 11:16:38	ga_ls7e_ard_3-0-0_110070_2018-08-27_final
2018-08-29 11:03:50	ga_ls7e_ard_3-0-0_108069_2018-08-29_final
2018-08-30 10:08:12	ga_ls7e_ard_3-0-0_099069_2018-08-30_final
2018-08-30 10:08:36	ga_ls7e_ard_3-0-0_099070_2018-08-30_final
2018-08-31 10:51:26	ga_ls7e_ard_3-0-0_106069_2018-08-31_final
2018-08-31 10:51:50	ga_ls7e_ard_3-0-0_106070_2018-08-31_final
2018-09-01 09:55:48	ga_ls7e_ard_3-0-0_097069_2018-09-01_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