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
2016-06-12 10:20:15	ga_ls7e_ard_3-0-0_100073_2016-06-12_final
2016-09-16 10:20:25	ga_ls7e_ard_3-0-0_100073_2016-09-16_final
2016-10-18 10:20:26	ga_ls7e_ard_3-0-0_100073_2016-10-18_final
2016-11-03 10:20:21	ga_ls7e_ard_3-0-0_100073_2016-11-03_final
2017-01-06 10:19:57	ga_ls7e_ard_3-0-0_100073_2017-01-06_final
2017-02-07 10:19:40	ga_ls7e_ard_3-0-0_100073_2017-02-07_final
2017-03-27 10:19:56	ga_ls7e_ard_3-0-0_100073_2017-03-27_final
2017-05-14 10:20:11	ga_ls7e_ard_3-0-0_100073_2017-05-14_final
2017-06-15 10:20:19	ga_ls7e_ard_3-0-0_100073_2017-06-15_final
2017-07-17 10:20:22	ga_ls7e_ard_3-0-0_100073_2017-07-17_final
2017-08-18 10:20:19	ga_ls7e_ard_3-0-0_100073_2017-08-18_final
2017-09-03 10:20:19	ga_ls7e_ard_3-0-0_100073_2017-09-03_final
2017-09-19 10:20:16	ga_ls7e_ard_3-0-0_100073_2017-09-19_final
2017-10-05 10:20:18	ga_ls7e_ard_3-0-0_100073_2017-10-05_final
2017-11-22 10:20:16	ga_ls7e_ard_3-0-0_100073_2017-11-22_final
2017-12-24 10:19:58	ga_ls7e_ard_3-0-0_100073_2017-12-24_final
2018-01-09 10:19:46	ga_ls7e_ard_3-0-0_100073_2018-01-09_final
2018-02-26 10:19:07	ga_ls7e_ard_3-0-0_100073_2018-02-26_final
2018-04-15 10:18:27	ga_ls7e_ard_3-0-0_100073_2018-04-15_final
2018-05-01 10:18:10	ga_ls7e_ard_3-0-0_100073_2018-05-01_final
2018-05-17 10:17:54	ga_ls7e_ard_3-0-0_100073_2018-05-17_final
2018-06-02 10:17:39	ga_ls7e_ard_3-0-0_100073_2018-06-02_final
2018-06-18 10:17:21	ga_ls7e_ard_3-0-0_100073_2018-06-18_final
2018-07-04 10:17:02	ga_ls7e_ard_3-0-0_100073_2018-07-04_final
2018-08-05 10:16:28	ga_ls7e_ard_3-0-0_100073_2018-08-05_final
2018-08-21 10:16:09	ga_ls7e_ard_3-0-0_100073_2018-08-21_final
2018-09-06 10:15:49	ga_ls7e_ard_3-0-0_100073_2018-09-06_final
2018-09-22 10:15:28	ga_ls7e_ard_3-0-0_100073_2018-09-22_final
2018-10-08 10:15:05	ga_ls7e_ard_3-0-0_100073_2018-10-08_final
2018-10-24 10:14:42	ga_ls7e_ard_3-0-0_100073_2018-10-24_final
2018-11-09 10:14:21	ga_ls7e_ard_3-0-0_100073_2018-11-09_final
2018-11-25 10:13:58	ga_ls7e_ard_3-0-0_100073_2018-11-25_final
2018-12-11 10:13:33	ga_ls7e_ard_3-0-0_100073_2018-12-11_final
2018-12-27 10:13:05	ga_ls7e_ard_3-0-0_100073_2018-12-27_final
2019-01-12 10:12:35	ga_ls7e_ard_3-0-0_100073_2019-01-12_final
2019-01-28 10:12:04	ga_ls7e_ard_3-0-0_100073_2019-01-28_final
2019-02-13 10:11:36	ga_ls7e_ard_3-0-0_100073_2019-02-13_final
2019-03-01 10:11:06	ga_ls7e_ard_3-1-0_100073_2019-03-01_final
2019-03-17 10:10:35	ga_ls7e_ard_3-1-0_100073_2019-03-17_final
2019-04-02 10:10:03	ga_ls7e_ard_3-0-0_100073_2019-04-02_final
2019-04-18 10:09:29	ga_ls7e_ard_3-0-0_100073_2019-04-18_final
2019-05-04 10:08:53	ga_ls7e_ard_3-0-0_100073_2019-05-04_final
2019-05-20 10:08:15	ga_ls7e_ard_3-0-0_100073_2019-05-20_final
2019-06-05 10:07:41	ga_ls7e_ard_3-0-0_100073_2019-06-05_final
2019-06-21 10:07:06	ga_ls7e_ard_3-0-0_100073_2019-06-21_final
2019-07-07 10:06:30	ga_ls7e_ard_3-0-0_100073_2019-07-07_final
2019-07-23 10:05:52	ga_ls7e_ard_3-0-0_100073_2019-07-23_final
2019-08-08 10:05:13	ga_ls7e_ard_3-0-0_100073_2019-08-08_final
2019-08-24 10:04:33	ga_ls7e_ard_3-1-0_100073_2019-08-24_final
2019-09-09 10:03:51	ga_ls7e_ard_3-1-0_100073_2019-09-09_final
2019-09-25 10:03:08	ga_ls7e_ard_3-1-0_100073_2019-09-25_final
2019-10-11 10:02:29	ga_ls7e_ard_3-1-0_100073_2019-10-11_final
2019-10-27 10:01:48	ga_ls7e_ard_3-1-0_100073_2019-10-27_final
2019-11-12 10:01:05	ga_ls7e_ard_3-1-0_100073_2019-11-12_final
2019-11-28 10:00:19	ga_ls7e_ard_3-1-0_100073_2019-11-28_final
2019-12-14 09:59:32	ga_ls7e_ard_3-1-0_100073_2019-12-14_final
2019-12-30 09:58:42	ga_ls7e_ard_3-1-0_100073_2019-12-30_final
2020-01-15 09:57:54	ga_ls7e_ard_3-1-0_100073_2020-01-15_final
2020-01-31 09:57:06	ga_ls7e_ard_3-1-0_100073_2020-01-31_final
2020-02-16 09:56:17	ga_ls7e_ard_3-1-0_100073_2020-02-16_final
2020-03-19 09:54:33	ga_ls7e_ard_3-1-0_100073_2020-03-19_final
2020-04-04 09:53:39	ga_ls7e_ard_3-1-0_100073_2020-04-04_final
2020-04-20 09:52:44	ga_ls7e_ard_3-1-0_100073_2020-04-20_final
2020-05-06 09:51:46	ga_ls7e_ard_3-1-0_100073_2020-05-06_final
2020-06-07 09:49:51	ga_ls7e_ard_3-1-0_100073_2020-06-07_final
2020-06-23 09:48:55	ga_ls7e_ard_3-1-0_100073_2020-06-23_final
2020-07-09 09:47:57	ga_ls7e_ard_3-1-0_100073_2020-07-09_final
2020-07-25 09:46:58	ga_ls7e_ard_3-1-0_100073_2020-07-25_final
2020-08-10 09:45:58	ga_ls7e_ard_3-1-0_100073_2020-08-10_final
2020-08-26 09:44:56	ga_ls7e_ard_3-1-0_100073_2020-08-26_final
2020-09-11 09:43:53	ga_ls7e_ard_3-1-0_100073_2020-09-11_final
2020-09-27 09:42:50	ga_ls7e_ard_3-1-0_100073_2020-09-27_final
2020-10-13 09:41:49	ga_ls7e_ard_3-1-0_100073_2020-10-13_final
2020-10-29 09:40:46	ga_ls7e_ard_3-1-0_100073_2020-10-29_final
2020-11-14 09:39:41	ga_ls7e_ard_3-1-0_100073_2020-11-14_final
2020-11-30 09:38:32	ga_ls7e_ard_3-1-0_100073_2020-11-30_final
2021-02-18 09:32:43	ga_ls7e_ard_3-2-0_100073_2021-02-18_final
2021-03-06 09:31:29	ga_ls7e_ard_3-2-0_100073_2021-03-06_final
2021-04-07 09:28:54	ga_ls7e_ard_3-2-0_100073_2021-04-06_final
2021-04-23 09:27:33	ga_ls7e_ard_3-2-0_100073_2021-04-22_final
2021-05-09 09:26:13	ga_ls7e_ard_3-2-0_100073_2021-05-08_final
2021-05-25 09:24:51	ga_ls7e_ard_3-2-0_100073_2021-05-24_final
2021-06-10 09:23:31	ga_ls7e_ard_3-2-0_100073_2021-06-09_final
2021-06-26 09:22:12	ga_ls7e_ard_3-2-0_100073_2021-06-25_final
2021-07-12 09:20:52	ga_ls7e_ard_3-2-0_100073_2021-07-11_final
2021-07-28 09:19:29	ga_ls7e_ard_3-2-0_100073_2021-07-27_final
2021-08-13 09:18:03	ga_ls7e_ard_3-2-0_100073_2021-08-12_final
2021-08-29 09:16:40	ga_ls7e_ard_3-2-0_100073_2021-08-28_final
2021-09-14 09:15:16	ga_ls7e_ard_3-2-0_100073_2021-09-13_final
2021-09-30 09:13:50	ga_ls7e_ard_3-2-0_100073_2021-09-29_final
2021-10-16 09:12:26	ga_ls7e_ard_3-2-0_100073_2021-10-15_final
2021-11-01 09:10:58	ga_ls7e_ard_3-2-0_100073_2021-10-31_final
2021-11-17 09:09:25	ga_ls7e_ard_3-2-1_100073_2021-11-16_final
2021-12-03 09:07:54	ga_ls7e_ard_3-2-1_100073_2021-12-02_final
2021-12-19 09:06:22	ga_ls7e_ard_3-2-1_100073_2021-12-18_final
2022-01-04 09:04:46	ga_ls7e_ard_3-2-1_100073_2022-01-03_final
2022-01-20 09:03:15	ga_ls7e_ard_3-2-1_100073_2022-01-19_final
2022-02-05 09:01:40	ga_ls7e_ard_3-2-1_100073_2022-02-04_final
2022-02-21 09:00:04	ga_ls7e_ard_3-2-1_100073_2022-02-20_final
2022-03-09 08:58:30	ga_ls7e_ard_3-2-1_100073_2022-03-08_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years