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
2015-02-28 10:52:03	ga_ls7e_ard_3-0-0_106069_2015-02-28_final
2015-03-01 09:56:26	ga_ls7e_ard_3-0-0_097069_2015-03-01_final
2017-02-28 10:36:43	ga_ls7e_ard_3-0-0_103069_2017-02-28_final
2017-03-03 11:07:39	ga_ls7e_ard_3-0-0_108069_2017-03-03_final
2017-03-04 10:12:02	ga_ls7e_ard_3-0-0_099069_2017-03-04_final
2017-03-13 10:05:54	ga_ls7e_ard_3-0-0_098069_2017-03-13_final
2017-04-20 11:07:56	ga_ls7e_ard_3-0-0_108069_2017-04-20_final
2017-04-21 10:12:19	ga_ls7e_ard_3-0-0_099069_2017-04-21_final
2017-04-22 10:55:35	ga_ls7e_ard_3-0-0_106069_2017-04-22_final
2017-05-06 11:08:01	ga_ls7e_ard_3-0-0_108069_2017-05-06_final
2017-05-23 10:12:26	ga_ls7e_ard_3-0-0_099069_2017-05-23_final
2017-05-24 10:55:42	ga_ls7e_ard_3-0-0_106069_2017-05-24_final
2017-05-25 10:00:05	ga_ls7e_ard_3-0-0_097069_2017-05-25_final
2017-06-02 10:49:34	ga_ls7e_ard_3-0-0_105069_2017-06-02_final
2017-06-04 10:37:13	ga_ls7e_ard_3-0-0_103069_2017-06-04_final
2017-06-11 10:43:26	ga_ls7e_ard_3-0-0_104069_2017-06-11_final
2017-06-13 10:31:05	ga_ls7e_ard_3-0-0_102069_2017-06-13_final
2017-06-17 10:06:22	ga_ls7e_ard_3-0-0_098069_2017-06-17_final
2017-06-18 10:49:38	ga_ls7e_ard_3-0-0_105069_2017-06-18_final
2017-06-24 10:12:34	ga_ls7e_ard_3-0-0_099069_2017-06-24_final
2017-06-25 10:55:50	ga_ls7e_ard_3-0-0_106069_2017-06-25_final
2017-06-26 10:00:13	ga_ls7e_ard_3-0-0_097069_2017-06-26_final
2017-07-06 10:37:18	ga_ls7e_ard_3-0-0_103069_2017-07-06_final
2017-07-09 11:08:13	ga_ls7e_ard_3-0-0_108069_2017-07-09_final
2017-07-10 10:12:35	ga_ls7e_ard_3-0-0_099069_2017-07-10_final
2017-07-11 10:55:51	ga_ls7e_ard_3-0-0_106069_2017-07-11_final
2017-07-12 10:00:14	ga_ls7e_ard_3-0-0_097069_2017-07-12_final
2017-07-25 11:08:12	ga_ls7e_ard_3-0-0_108069_2017-07-25_final
2017-07-26 10:12:35	ga_ls7e_ard_3-0-0_099069_2017-07-26_final
2017-07-27 10:55:50	ga_ls7e_ard_3-0-0_106069_2017-07-27_final
2017-08-10 11:08:10	ga_ls7e_ard_3-0-0_108069_2017-08-10_final
2017-08-23 10:37:16	ga_ls7e_ard_3-0-0_103069_2017-08-23_final
2017-08-26 11:08:10	ga_ls7e_ard_3-0-0_108069_2017-08-26_final
2017-09-05 10:06:21	ga_ls7e_ard_3-0-0_098069_2017-09-05_final
2017-09-12 10:12:31	ga_ls7e_ard_3-0-0_099069_2017-09-12_final
2017-09-13 10:55:47	ga_ls7e_ard_3-0-0_106069_2017-09-13_final
2017-09-14 10:00:09	ga_ls7e_ard_3-0-0_097069_2017-09-14_final
2017-09-15 10:43:25	ga_ls7e_ard_3-0-0_104069_2017-09-15_final
2017-09-21 10:06:19	ga_ls7e_ard_3-0-0_098069_2017-09-21_final
2017-09-22 10:49:35	ga_ls7e_ard_3-0-0_105069_2017-09-22_final
2017-09-24 10:37:14	ga_ls7e_ard_3-0-0_103069_2017-09-24_final
2017-12-01 10:12:25	ga_ls7e_ard_3-0-0_099069_2017-12-01_final
2017-12-02 10:55:40	ga_ls7e_ard_3-0-0_106069_2017-12-02_final
2017-12-03 10:00:03	ga_ls7e_ard_3-0-0_097069_2017-12-03_final
2017-12-04 10:43:18	ga_ls7e_ard_3-0-0_104069_2017-12-04_final
2017-12-06 10:30:55	ga_ls7e_ard_3-0-0_102069_2017-12-06_final
2018-03-28 10:29:30	ga_ls7e_ard_3-0-0_102069_2018-03-28_final
2018-08-10 10:33:19	ga_ls7e_ard_3-0-0_103069_2018-08-10_final
2018-08-14 10:08:31	ga_ls7e_ard_3-0-0_099069_2018-08-14_final
2018-08-15 10:51:46	ga_ls7e_ard_3-0-0_106069_2018-08-15_final
2020-08-03 09:38:38	ga_ls7e_ard_3-1-0_099069_2020-08-03_final
2020-08-04 10:21:50	ga_ls7e_ard_3-1-0_106069_2020-08-04_final
2020-08-05 09:26:09	ga_ls7e_ard_3-1-0_097069_2020-08-04_final
2020-09-03 10:32:16	ga_ls7e_ard_3-1-0_108069_2020-09-03_final
2020-09-04 09:36:35	ga_ls7e_ard_3-1-0_099069_2020-09-04_final
2020-09-05 10:19:46	ga_ls7e_ard_3-1-0_106069_2020-09-05_final
2020-09-07 10:07:17	ga_ls7e_ard_3-1-0_104069_2020-09-07_final
2020-09-09 09:54:47	ga_ls7e_ard_3-1-0_102069_2020-09-09_final
2020-09-23 10:06:13	ga_ls7e_ard_3-1-0_104069_2020-09-23_final
2020-09-25 09:53:44	ga_ls7e_ard_3-1-0_102069_2020-09-25_final
2020-09-29 09:28:45	ga_ls7e_ard_3-1-0_098069_2020-09-28_final
2020-09-30 10:11:57	ga_ls7e_ard_3-1-0_105069_2020-09-30_final
2020-10-18 09:58:26	ga_ls7e_ard_3-1-0_103069_2020-10-18_final
2020-10-31 09:26:41	ga_ls7e_ard_3-1-0_098069_2020-10-30_final
2020-11-01 10:09:52	ga_ls7e_ard_3-1-0_105069_2020-11-01_final
2020-11-03 09:57:22	ga_ls7e_ard_3-1-0_103069_2020-11-03_final
2020-11-12 09:50:35	ga_ls7e_ard_3-1-0_102069_2020-11-12_final
2020-11-16 09:25:35	ga_ls7e_ard_3-1-0_098069_2020-11-15_final
2020-11-17 10:08:46	ga_ls7e_ard_3-1-0_105069_2020-11-17_final
2020-11-23 09:31:16	ga_ls7e_ard_3-1-0_099069_2020-11-23_final
2020-11-25 09:18:46	ga_ls7e_ard_3-1-0_097069_2020-11-24_final
2020-11-26 10:01:57	ga_ls7e_ard_3-1-0_104069_2020-11-26_final
2020-11-28 09:49:27	ga_ls7e_ard_3-1-0_102069_2020-11-28_final
2020-12-02 09:24:26	ga_ls7e_ard_3-1-0_098069_2020-12-01_final
2020-12-03 10:07:37	ga_ls7e_ard_3-1-0_105069_2020-12-03_final
2020-12-05 09:55:07	ga_ls7e_ard_3-1-0_103069_2020-12-05_final
2020-12-10 10:13:17	ga_ls7e_ard_3-1-0_106069_2020-12-10_final
2020-12-12 10:00:46	ga_ls7e_ard_3-1-0_104069_2020-12-12_final
2020-12-14 09:48:15	ga_ls7e_ard_3-1-0_102069_2020-12-14_final
2020-12-18 09:23:14	ga_ls7e_ard_3-1-0_098069_2020-12-17_final
2020-12-21 09:53:54	ga_ls7e_ard_3-1-0_103069_2020-12-21_final
2021-01-09 10:23:29	ga_ls7e_ard_3-1-0_108069_2021-01-09_final
2021-01-10 09:27:47	ga_ls7e_ard_3-1-0_099069_2021-01-09_final
2021-05-02 09:19:01	ga_ls7e_ard_3-2-0_099069_2021-05-01_final
2021-12-29 09:40:52	ga_ls7e_ard_3-2-1_106069_2021-12-29_final
2022-01-09 09:21:14	ga_ls7e_ard_3-2-1_103069_2022-01-08_final
2022-01-12 09:51:52	ga_ls7e_ard_3-2-1_108069_2022-01-12_final
2022-01-13 08:56:09	ga_ls7e_ard_3-2-1_099069_2022-01-12_final
2022-01-14 09:39:19	ga_ls7e_ard_3-2-1_106069_2022-01-14_final
2022-01-15 08:43:36	ga_ls7e_ard_3-2-1_097069_2022-01-14_final
2022-01-16 09:26:46	ga_ls7e_ard_3-2-1_104069_2022-01-15_final
2022-01-18 09:14:13	ga_ls7e_ard_3-2-1_102069_2022-01-17_final
2022-01-22 08:49:06	ga_ls7e_ard_3-2-1_098069_2022-01-21_final
2022-01-23 09:32:16	ga_ls7e_ard_3-2-1_105069_2022-01-23_final
2022-02-01 09:25:12	ga_ls7e_ard_3-2-1_104069_2022-01-31_final
2022-02-02 10:08:22	ga_ls7e_ard_3-2-1_111069_2022-02-02_final
2022-02-03 09:12:38	ga_ls7e_ard_3-2-1_102069_2022-02-02_final
2022-02-07 08:47:31	ga_ls7e_ard_3-2-1_098069_2022-02-06_final
2022-02-08 09:30:40	ga_ls7e_ard_3-2-1_105069_2022-02-08_final
2022-02-10 09:18:06	ga_ls7e_ard_3-2-1_103069_2022-02-09_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