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
2015-04-26 10:45:53	ga_ls7e_ard_3-0-0_105068_2015-04-26_final
2015-05-12 10:46:01	ga_ls7e_ard_3-0-0_105068_2015-05-12_final
2015-05-28 10:46:05	ga_ls7e_ard_3-0-0_105068_2015-05-28_final
2015-07-15 10:46:21	ga_ls7e_ard_3-0-0_105068_2015-07-15_final
2015-07-31 10:46:23	ga_ls7e_ard_3-0-0_105068_2015-07-31_final
2015-08-16 10:46:27	ga_ls7e_ard_3-0-0_105068_2015-08-16_final
2015-09-17 10:46:33	ga_ls7e_ard_3-0-0_105068_2015-09-17_final
2015-10-03 10:46:33	ga_ls7e_ard_3-0-0_105068_2015-10-03_final
2015-11-04 10:47:06	ga_ls7e_ard_3-0-0_105068_2015-11-04_final
2015-11-20 10:47:24	ga_ls7e_ard_3-0-0_105068_2015-11-20_final
2015-12-22 10:47:53	ga_ls7e_ard_3-0-0_105068_2015-12-22_final
2016-01-07 10:48:07	ga_ls7e_ard_3-0-0_105068_2016-01-07_final
2016-01-23 10:48:20	ga_ls7e_ard_3-0-0_105068_2016-01-23_final
2016-02-08 10:48:28	ga_ls7e_ard_3-0-0_105068_2016-02-08_final
2016-02-24 10:48:29	ga_ls7e_ard_3-0-0_105068_2016-02-24_final
2016-03-11 10:48:40	ga_ls7e_ard_3-0-0_105068_2016-03-11_final
2016-03-27 10:48:46	ga_ls7e_ard_3-0-0_105068_2016-03-27_final
2016-05-14 10:49:00	ga_ls7e_ard_3-0-0_105068_2016-05-14_final
2016-05-30 10:49:06	ga_ls7e_ard_3-0-0_105068_2016-05-30_final
2016-06-15 10:49:10	ga_ls7e_ard_3-0-0_105068_2016-06-15_final
2016-07-01 10:49:10	ga_ls7e_ard_3-0-0_105068_2016-07-01_final
2016-07-17 10:49:11	ga_ls7e_ard_3-0-0_105068_2016-07-17_final
2016-08-02 10:49:13	ga_ls7e_ard_3-0-0_105068_2016-08-02_final
2016-08-18 10:49:14	ga_ls7e_ard_3-0-0_105068_2016-08-18_final
2016-09-19 10:49:20	ga_ls7e_ard_3-0-0_105068_2016-09-19_final
2016-10-05 10:49:22	ga_ls7e_ard_3-0-0_105068_2016-10-05_final
2016-10-21 10:49:20	ga_ls7e_ard_3-0-0_105068_2016-10-21_final
2016-11-06 10:49:14	ga_ls7e_ard_3-0-0_105068_2016-11-06_final
2016-11-22 10:49:08	ga_ls7e_ard_3-0-0_105068_2016-11-22_final
2016-12-08 10:49:05	ga_ls7e_ard_3-0-0_105068_2016-12-08_final
2016-12-24 10:48:59	ga_ls7e_ard_3-0-0_105068_2016-12-24_final
2017-01-09 10:48:49	ga_ls7e_ard_3-0-0_105068_2017-01-09_final
2017-01-25 10:48:38	ga_ls7e_ard_3-0-0_105068_2017-01-25_final
2017-02-10 10:48:30	ga_ls7e_ard_3-0-0_105068_2017-02-10_final
2017-02-26 10:48:40	ga_ls7e_ard_3-0-0_105068_2017-02-26_final
2017-03-14 10:48:47	ga_ls7e_ard_3-0-0_105068_2017-03-14_final
2017-05-01 10:49:03	ga_ls7e_ard_3-0-0_105068_2017-05-01_final
2017-05-17 10:49:06	ga_ls7e_ard_3-0-0_105068_2017-05-17_final
2017-06-02 10:49:10	ga_ls7e_ard_3-0-0_105068_2017-06-02_final
2017-06-18 10:49:14	ga_ls7e_ard_3-0-0_105068_2017-06-18_final
2017-07-04 10:49:16	ga_ls7e_ard_3-0-0_105068_2017-07-04_final
2017-07-20 10:49:16	ga_ls7e_ard_3-0-0_105068_2017-07-20_final
2017-08-05 10:49:14	ga_ls7e_ard_3-0-0_105068_2017-08-05_final
2017-09-22 10:49:11	ga_ls7e_ard_3-0-0_105068_2017-09-22_final
2017-10-08 10:49:13	ga_ls7e_ard_3-0-0_105068_2017-10-08_final
2017-10-24 10:49:15	ga_ls7e_ard_3-0-0_105068_2017-10-24_final
2017-11-09 10:49:14	ga_ls7e_ard_3-0-0_105068_2017-11-09_final
2017-11-25 10:49:09	ga_ls7e_ard_3-0-0_105068_2017-11-25_final
2017-12-27 10:48:50	ga_ls7e_ard_3-0-0_105068_2017-12-27_final
2018-01-12 10:48:37	ga_ls7e_ard_3-0-0_105068_2018-01-12_final
2018-04-18 10:47:18	ga_ls7e_ard_3-0-0_105068_2018-04-18_final
2018-05-04 10:47:01	ga_ls7e_ard_3-0-0_105068_2018-05-04_final
2018-05-20 10:46:45	ga_ls7e_ard_3-0-0_105068_2018-05-20_final
2018-06-05 10:46:30	ga_ls7e_ard_3-0-0_105068_2018-06-05_final
2018-07-07 10:45:53	ga_ls7e_ard_3-0-0_105068_2018-07-07_final
2018-08-24 10:45:00	ga_ls7e_ard_3-0-0_105068_2018-08-24_final
2018-09-09 10:44:40	ga_ls7e_ard_3-0-0_105068_2018-09-09_final
2018-09-25 10:44:18	ga_ls7e_ard_3-0-0_105068_2018-09-25_final
2018-10-11 10:43:55	ga_ls7e_ard_3-0-0_105068_2018-10-11_final
2018-10-27 10:43:33	ga_ls7e_ard_3-0-0_105068_2018-10-27_final
2018-11-12 10:43:12	ga_ls7e_ard_3-0-0_105068_2018-11-12_final
2018-11-28 10:42:48	ga_ls7e_ard_3-0-0_105068_2018-11-28_final
2019-01-15 10:41:24	ga_ls7e_ard_3-0-0_105068_2019-01-15_final
2019-03-20 10:39:24	ga_ls7e_ard_3-1-0_105068_2019-03-20_final
2019-04-21 10:38:16	ga_ls7e_ard_3-0-0_105068_2019-04-21_final
2019-05-07 10:37:40	ga_ls7e_ard_3-0-0_105068_2019-05-07_final
2019-06-24 10:35:54	ga_ls7e_ard_3-0-0_105068_2019-06-24_final
2019-08-11 10:34:00	ga_ls7e_ard_3-0-0_105068_2019-08-11_final
2019-08-27 10:33:19	ga_ls7e_ard_3-1-0_105068_2019-08-27_final
2019-09-12 10:32:38	ga_ls7e_ard_3-1-0_105068_2019-09-12_final
2019-09-28 10:31:55	ga_ls7e_ard_3-1-0_105068_2019-09-28_final
2019-11-15 10:29:51	ga_ls7e_ard_3-1-0_105068_2019-11-15_final
2020-02-19 10:25:02	ga_ls7e_ard_3-1-0_105068_2020-02-19_final
2020-09-30 10:11:33	ga_ls7e_ard_3-1-0_105068_2020-09-30_final
2020-12-03 10:07:13	ga_ls7e_ard_3-1-0_105068_2020-12-03_final
2021-01-04 10:04:53	ga_ls7e_ard_3-1-0_105068_2021-01-04_final
2021-01-20 10:03:46	ga_ls7e_ard_3-2-0_105068_2021-01-20_final
2021-02-21 10:01:23	ga_ls7e_ard_3-2-0_105068_2021-02-21_final
2021-03-09 10:00:09	ga_ls7e_ard_3-2-0_105068_2021-03-09_final
2021-04-10 09:57:33	ga_ls7e_ard_3-2-0_105068_2021-04-10_final
2021-04-26 09:56:12	ga_ls7e_ard_3-2-0_105068_2021-04-26_final
2021-05-12 09:54:52	ga_ls7e_ard_3-2-0_105068_2021-05-12_final
2021-05-28 09:53:30	ga_ls7e_ard_3-2-0_105068_2021-05-28_final
2021-06-13 09:52:11	ga_ls7e_ard_3-2-0_105068_2021-06-13_final
2021-06-29 09:50:52	ga_ls7e_ard_3-2-0_105068_2021-06-29_final
2021-07-15 09:49:30	ga_ls7e_ard_3-2-0_105068_2021-07-15_final
2021-07-31 09:48:07	ga_ls7e_ard_3-2-0_105068_2021-07-31_final
2021-08-16 09:46:42	ga_ls7e_ard_3-2-0_105068_2021-08-16_final
2021-09-01 09:45:19	ga_ls7e_ard_3-2-0_105068_2021-09-01_final
2021-09-17 09:43:54	ga_ls7e_ard_3-2-0_105068_2021-09-17_final
2021-10-03 09:42:29	ga_ls7e_ard_3-2-0_105068_2021-10-03_final
2021-10-19 09:41:04	ga_ls7e_ard_3-2-0_105068_2021-10-19_final
2021-11-04 09:39:35	ga_ls7e_ard_3-2-0_105068_2021-11-04_final
2021-11-20 09:38:02	ga_ls7e_ard_3-2-1_105068_2021-11-20_final
2021-12-06 09:36:31	ga_ls7e_ard_3-2-1_105068_2021-12-06_final
2021-12-22 09:34:59	ga_ls7e_ard_3-2-1_105068_2021-12-22_final
2022-01-07 09:33:23	ga_ls7e_ard_3-2-1_105068_2022-01-07_final
2022-01-23 09:31:52	ga_ls7e_ard_3-2-1_105068_2022-01-23_final
2022-02-08 09:30:16	ga_ls7e_ard_3-2-1_105068_2022-02-08_final
2022-03-12 09:27:07	ga_ls7e_ard_3-2-1_105068_2022-03-11_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