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
2017-03-03 09:31:09	ga_ls7e_ard_3-0-0_092075_2017-03-03_final
2017-03-05 09:20:00	ga_ls7e_ard_3-0-0_090078_2017-03-04_final
2017-03-05 09:20:24	ga_ls7e_ard_3-0-0_090079_2017-03-04_final
2017-03-05 09:20:48	ga_ls7e_ard_3-0-0_090080_2017-03-04_final
2017-05-08 09:20:22	ga_ls7e_ard_3-0-0_090078_2017-05-07_final
2017-05-08 09:20:46	ga_ls7e_ard_3-0-0_090079_2017-05-07_final
2017-05-08 09:21:10	ga_ls7e_ard_3-0-0_090080_2017-05-07_final
2017-05-08 09:21:34	ga_ls7e_ard_3-0-0_090081_2017-05-07_final
2017-05-08 09:21:58	ga_ls7e_ard_3-0-0_090082_2017-05-07_final
2017-05-08 09:22:22	ga_ls7e_ard_3-0-0_090083_2017-05-07_final
2017-05-08 09:22:45	ga_ls7e_ard_3-0-0_090084_2017-05-07_final
2017-07-20 09:15:58	ga_ls7e_ard_3-0-0_089082_2017-07-19_final
2017-07-20 09:16:22	ga_ls7e_ard_3-0-0_089083_2017-07-19_final
2017-07-20 09:16:46	ga_ls7e_ard_3-0-0_089084_2017-07-19_final
2017-07-20 09:17:10	ga_ls7e_ard_3-0-0_089085_2017-07-19_final
2017-07-20 09:17:34	ga_ls7e_ard_3-0-0_089086_2017-07-19_final
2017-08-05 09:15:56	ga_ls7e_ard_3-0-0_089082_2017-08-04_final
2017-08-05 09:16:20	ga_ls7e_ard_3-0-0_089083_2017-08-04_final
2017-08-05 09:16:44	ga_ls7e_ard_3-0-0_089084_2017-08-04_final
2017-08-05 09:17:08	ga_ls7e_ard_3-0-0_089085_2017-08-04_final
2017-08-05 09:17:32	ga_ls7e_ard_3-0-0_089086_2017-08-04_final
2017-09-06 09:15:55	ga_ls7e_ard_3-0-0_089082_2017-09-05_final
2017-09-06 09:16:19	ga_ls7e_ard_3-0-0_089083_2017-09-05_final
2017-09-06 09:16:43	ga_ls7e_ard_3-0-0_089084_2017-09-05_final
2017-09-06 09:17:07	ga_ls7e_ard_3-0-0_089085_2017-09-05_final
2017-09-06 09:17:31	ga_ls7e_ard_3-0-0_089086_2017-09-05_final
2017-09-11 09:31:39	ga_ls7e_ard_3-0-0_092075_2017-09-11_final
2017-11-09 09:15:56	ga_ls7e_ard_3-0-0_089082_2017-11-08_final
2017-11-09 09:16:20	ga_ls7e_ard_3-0-0_089083_2017-11-08_final
2017-11-09 09:16:44	ga_ls7e_ard_3-0-0_089084_2017-11-08_final
2017-11-09 09:17:08	ga_ls7e_ard_3-0-0_089085_2017-11-08_final
2017-11-09 09:17:32	ga_ls7e_ard_3-0-0_089086_2017-11-08_final
2018-10-02 09:15:25	ga_ls7e_ard_3-0-0_090078_2018-10-01_final
2018-10-02 09:15:49	ga_ls7e_ard_3-0-0_090079_2018-10-01_final
2018-10-02 09:16:13	ga_ls7e_ard_3-0-0_090080_2018-10-01_final
2018-10-02 09:16:37	ga_ls7e_ard_3-0-0_090081_2018-10-01_final
2018-10-02 09:17:01	ga_ls7e_ard_3-0-0_090082_2018-10-01_final
2018-10-02 09:17:25	ga_ls7e_ard_3-0-0_090083_2018-10-01_final
2018-10-02 09:17:49	ga_ls7e_ard_3-0-0_090084_2018-10-01_final
2018-10-09 09:20:38	ga_ls7e_ard_3-0-0_091076_2018-10-08_final
2018-10-09 09:21:02	ga_ls7e_ard_3-0-0_091077_2018-10-08_final
2018-10-09 09:21:50	ga_ls7e_ard_3-0-0_091079_2018-10-08_final
2018-10-09 09:22:14	ga_ls7e_ard_3-0-0_091080_2018-10-08_final
2018-10-18 09:15:01	ga_ls7e_ard_3-0-0_090078_2018-10-17_final
2018-10-18 09:16:37	ga_ls7e_ard_3-1-0_090082_2018-10-17_final
2018-10-18 09:17:01	ga_ls7e_ard_3-0-0_090083_2018-10-17_final
2018-10-18 09:17:25	ga_ls7e_ard_3-0-0_090084_2018-10-17_final
2018-11-01 09:25:54	ga_ls7e_ard_3-0-0_092075_2018-10-31_final
2018-11-03 09:14:41	ga_ls7e_ard_3-0-0_090078_2018-11-02_final
2018-11-03 09:15:05	ga_ls7e_ard_3-0-0_090079_2018-11-02_final
2018-11-03 09:15:29	ga_ls7e_ard_3-0-0_090080_2018-11-02_final
2018-11-03 09:15:53	ga_ls7e_ard_3-0-0_090081_2018-11-02_final
2018-11-03 09:16:17	ga_ls7e_ard_3-1-0_090082_2018-11-02_final
2018-11-03 09:16:41	ga_ls7e_ard_3-0-0_090083_2018-11-02_final
2018-11-03 09:17:05	ga_ls7e_ard_3-0-0_090084_2018-11-02_final
2018-11-10 09:19:55	ga_ls7e_ard_3-0-0_091076_2018-11-09_final
2018-11-10 09:20:19	ga_ls7e_ard_3-0-0_091077_2018-11-09_final
2018-11-10 09:20:42	ga_ls7e_ard_3-0-0_091078_2018-11-09_final
2018-11-10 09:21:06	ga_ls7e_ard_3-0-0_091079_2018-11-09_final
2018-11-10 09:21:30	ga_ls7e_ard_3-0-0_091080_2018-11-09_final
2018-11-12 09:09:54	ga_ls7e_ard_3-0-0_089082_2018-11-11_final
2018-11-12 09:10:18	ga_ls7e_ard_3-0-0_089083_2018-11-11_final
2018-11-12 09:10:42	ga_ls7e_ard_3-0-0_089084_2018-11-11_final
2018-11-12 09:11:06	ga_ls7e_ard_3-0-0_089085_2018-11-11_final
2018-11-12 09:11:30	ga_ls7e_ard_3-0-0_089086_2018-11-11_final
2018-12-05 09:13:54	ga_ls7e_ard_3-0-0_090078_2018-12-04_final
2018-12-05 09:14:18	ga_ls7e_ard_3-0-0_090079_2018-12-04_final
2018-12-05 09:14:42	ga_ls7e_ard_3-0-0_090080_2018-12-04_final
2018-12-05 09:15:06	ga_ls7e_ard_3-0-0_090081_2018-12-04_final
2018-12-05 09:15:30	ga_ls7e_ard_3-0-0_090082_2018-12-04_final
2018-12-05 09:16:18	ga_ls7e_ard_3-0-0_090084_2018-12-04_final
2018-12-19 09:24:41	ga_ls7e_ard_3-0-0_092075_2018-12-18_final
2018-12-21 09:13:27	ga_ls7e_ard_3-0-0_090078_2018-12-20_final
2018-12-21 09:13:51	ga_ls7e_ard_3-0-0_090079_2018-12-20_final
2018-12-21 09:14:15	ga_ls7e_ard_3-0-0_090080_2018-12-20_final
2018-12-21 09:14:39	ga_ls7e_ard_3-0-0_090081_2018-12-20_final
2018-12-21 09:15:03	ga_ls7e_ard_3-0-0_090082_2018-12-20_final
2018-12-21 09:15:27	ga_ls7e_ard_3-0-0_090083_2018-12-20_final
2019-02-23 09:11:29	ga_ls7e_ard_3-1-0_090078_2019-02-22_final
2019-02-23 09:11:53	ga_ls7e_ard_3-1-0_090079_2019-02-22_final
2019-02-23 09:12:17	ga_ls7e_ard_3-1-0_090080_2019-02-22_final
2019-02-23 09:12:41	ga_ls7e_ard_3-1-0_090081_2019-02-22_final
2019-02-23 09:13:05	ga_ls7e_ard_3-1-0_090082_2019-02-22_final
2019-02-23 09:13:29	ga_ls7e_ard_3-1-0_090083_2019-02-22_final
2019-02-23 09:13:53	ga_ls7e_ard_3-1-0_090084_2019-02-22_final
2019-03-02 09:16:39	ga_ls7e_ard_3-1-0_091076_2019-03-01_final
2019-03-02 09:17:03	ga_ls7e_ard_3-1-0_091077_2019-03-01_final
2019-03-02 09:17:51	ga_ls7e_ard_3-1-0_091079_2019-03-01_final
2019-03-02 09:18:15	ga_ls7e_ard_3-1-0_091080_2019-03-01_final
2019-04-03 09:15:35	ga_ls7e_ard_3-0-0_091076_2019-04-02_final
2019-04-03 09:15:59	ga_ls7e_ard_3-0-0_091077_2019-04-02_final
2019-04-03 09:16:23	ga_ls7e_ard_3-0-0_091078_2019-04-02_final
2019-04-03 09:16:47	ga_ls7e_ard_3-0-0_091079_2019-04-02_final
2019-04-03 09:17:11	ga_ls7e_ard_3-0-0_091080_2019-04-02_final
2019-04-05 09:05:33	ga_ls7e_ard_3-0-0_089082_2019-04-04_final
2019-04-19 09:15:01	ga_ls7e_ard_3-0-0_091076_2019-04-18_final
2019-04-19 09:15:25	ga_ls7e_ard_3-0-0_091077_2019-04-18_final
2019-04-19 09:15:49	ga_ls7e_ard_3-0-0_091078_2019-04-18_final
2019-04-19 09:16:13	ga_ls7e_ard_3-0-0_091079_2019-04-18_final
2019-04-19 09:16:37	ga_ls7e_ard_3-0-0_091080_2019-04-18_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