Search ga_ls7e_ard_3 across February 2016

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
2016-02-01 10:42:14	ga_ls7e_ard_3-0-0_104068_2016-02-01_final
2016-02-01 10:42:38	ga_ls7e_ard_3-0-0_104069_2016-02-01_final
2016-02-01 10:45:02	ga_ls7e_ard_3-0-0_104075_2016-02-01_final
2016-02-01 10:45:26	ga_ls7e_ard_3-0-0_104076_2016-02-01_final
2016-02-01 10:45:49	ga_ls7e_ard_3-0-0_104077_2016-02-01_final
2016-02-01 10:46:13	ga_ls7e_ard_3-0-0_104078_2016-02-01_final
2016-02-01 10:47:01	ga_ls7e_ard_3-0-0_104080_2016-02-01_final
2016-02-02 09:46:13	ga_ls7e_ard_3-0-0_095067_2016-02-02_final
2016-02-07 10:04:48	ga_ls7e_ard_3-0-0_098067_2016-02-07_final
2016-02-07 10:05:12	ga_ls7e_ard_3-0-0_098068_2016-02-07_final
2016-02-07 10:05:36	ga_ls7e_ard_3-0-0_098069_2016-02-07_final
2016-02-07 10:05:59	ga_ls7e_ard_3-0-0_098070_2016-02-07_final
2016-02-07 10:06:23	ga_ls7e_ard_3-0-0_098071_2016-02-07_final
2016-02-07 10:06:47	ga_ls7e_ard_3-0-0_098072_2016-02-07_final
2016-02-07 10:07:11	ga_ls7e_ard_3-0-0_098073_2016-02-07_final
2016-02-07 10:07:35	ga_ls7e_ard_3-0-0_098074_2016-02-07_final
2016-02-07 10:07:59	ga_ls7e_ard_3-0-0_098075_2016-02-07_final
2016-02-07 10:08:23	ga_ls7e_ard_3-1-0_098076_2016-02-07_final
2016-02-07 10:09:11	ga_ls7e_ard_3-0-0_098078_2016-02-07_final
2016-02-07 10:09:35	ga_ls7e_ard_3-0-0_098079_2016-02-07_final
2016-02-07 10:09:59	ga_ls7e_ard_3-0-0_098080_2016-02-07_final
2016-02-07 10:10:23	ga_ls7e_ard_3-0-0_098081_2016-02-07_final
2016-02-07 10:10:47	ga_ls7e_ard_3-0-0_098082_2016-02-07_final
2016-02-07 10:11:11	ga_ls7e_ard_3-0-0_098083_2016-02-07_final
2016-02-07 10:11:35	ga_ls7e_ard_3-0-0_098084_2016-02-07_final
2016-02-07 10:11:59	ga_ls7e_ard_3-0-0_098085_2016-02-07_final
2016-02-07 11:46:28	ga_ls7e_ard_3-0-0_114074_2016-02-07_final
2016-02-07 11:46:52	ga_ls7e_ard_3-0-0_114075_2016-02-07_final
2016-02-07 11:47:16	ga_ls7e_ard_3-0-0_114076_2016-02-07_final
2016-02-07 11:47:40	ga_ls7e_ard_3-0-0_114077_2016-02-07_final
2016-02-07 11:48:04	ga_ls7e_ard_3-0-0_114078_2016-02-07_final
2016-02-07 11:48:28	ga_ls7e_ard_3-0-0_114079_2016-02-07_final
2016-02-07 11:48:52	ga_ls7e_ard_3-0-0_114080_2016-02-07_final
2016-02-07 11:49:16	ga_ls7e_ard_3-0-0_114081_2016-02-07_final
2016-02-08 09:13:10	ga_ls7e_ard_3-0-0_089077_2016-02-07_final
2016-02-08 09:13:34	ga_ls7e_ard_3-0-0_089078_2016-02-07_final
2016-02-08 09:13:58	ga_ls7e_ard_3-0-0_089079_2016-02-07_final
2016-02-08 09:14:22	ga_ls7e_ard_3-0-0_089080_2016-02-07_final
2016-02-08 09:14:46	ga_ls7e_ard_3-1-0_089081_2016-02-07_final
2016-02-08 09:15:10	ga_ls7e_ard_3-0-0_089082_2016-02-07_final
2016-02-08 09:15:34	ga_ls7e_ard_3-0-0_089083_2016-02-07_final
2016-02-08 09:15:58	ga_ls7e_ard_3-0-0_089084_2016-02-07_final
2016-02-08 09:16:22	ga_ls7e_ard_3-0-0_089085_2016-02-07_final
2016-02-08 09:16:46	ga_ls7e_ard_3-0-0_089086_2016-02-07_final
2016-02-08 09:17:57	ga_ls7e_ard_3-0-0_089089_2016-02-07_final
2016-02-08 09:18:21	ga_ls7e_ard_3-0-0_089090_2016-02-07_final
2016-02-08 10:48:28	ga_ls7e_ard_3-0-0_105068_2016-02-08_final
2016-02-08 10:48:52	ga_ls7e_ard_3-0-0_105069_2016-02-08_final
2016-02-08 10:49:15	ga_ls7e_ard_3-0-0_105070_2016-02-08_final
2016-02-08 10:49:39	ga_ls7e_ard_3-0-0_105071_2016-02-08_final
2016-02-08 10:50:03	ga_ls7e_ard_3-0-0_105072_2016-02-08_final
2016-02-08 10:50:27	ga_ls7e_ard_3-0-0_105073_2016-02-08_final
2016-02-08 10:50:51	ga_ls7e_ard_3-0-0_105074_2016-02-08_final
2016-02-08 10:51:15	ga_ls7e_ard_3-0-0_105075_2016-02-08_final
2016-02-08 10:51:39	ga_ls7e_ard_3-0-0_105076_2016-02-08_final
2016-02-08 10:52:03	ga_ls7e_ard_3-0-0_105077_2016-02-08_final
2016-02-08 10:52:27	ga_ls7e_ard_3-0-0_105078_2016-02-08_final
2016-02-08 10:52:51	ga_ls7e_ard_3-0-0_105079_2016-02-08_final
2016-02-08 10:53:15	ga_ls7e_ard_3-1-0_105080_2016-02-08_final
2016-02-08 10:53:39	ga_ls7e_ard_3-0-0_105081_2016-02-08_final
2016-02-08 10:54:03	ga_ls7e_ard_3-0-0_105082_2016-02-08_final
2016-02-09 09:52:27	ga_ls7e_ard_3-0-0_096067_2016-02-09_final
2016-02-09 09:53:38	ga_ls7e_ard_3-0-0_096070_2016-02-09_final
2016-02-09 09:54:02	ga_ls7e_ard_3-0-0_096071_2016-02-09_final
2016-02-09 09:54:26	ga_ls7e_ard_3-0-0_096072_2016-02-09_final
2016-02-09 09:54:50	ga_ls7e_ard_3-0-0_096073_2016-02-09_final
2016-02-09 09:55:38	ga_ls7e_ard_3-0-0_096075_2016-02-09_final
2016-02-09 09:56:02	ga_ls7e_ard_3-0-0_096076_2016-02-09_final
2016-02-09 09:56:26	ga_ls7e_ard_3-0-0_096077_2016-02-09_final
2016-02-09 09:56:50	ga_ls7e_ard_3-0-0_096078_2016-02-09_final
2016-02-09 09:57:14	ga_ls7e_ard_3-0-0_096079_2016-02-09_final
2016-02-09 09:57:38	ga_ls7e_ard_3-0-0_096080_2016-02-09_final
2016-02-09 09:58:02	ga_ls7e_ard_3-0-0_096081_2016-02-09_final
2016-02-09 09:58:26	ga_ls7e_ard_3-0-0_096082_2016-02-09_final
2016-02-09 09:58:50	ga_ls7e_ard_3-0-0_096083_2016-02-09_final
2016-02-09 09:59:14	ga_ls7e_ard_3-0-0_096084_2016-02-09_final
2016-02-09 09:59:38	ga_ls7e_ard_3-0-0_096085_2016-02-09_final
2016-02-09 10:00:02	ga_ls7e_ard_3-1-0_096086_2016-02-09_final
2016-02-09 11:34:07	ga_ls7e_ard_3-0-0_112074_2016-02-09_final
2016-02-09 11:34:31	ga_ls7e_ard_3-0-0_112075_2016-02-09_final
2016-02-09 11:34:55	ga_ls7e_ard_3-0-0_112076_2016-02-09_final
2016-02-09 11:35:19	ga_ls7e_ard_3-0-0_112077_2016-02-09_final
2016-02-09 11:35:43	ga_ls7e_ard_3-0-0_112078_2016-02-09_final
2016-02-09 11:36:07	ga_ls7e_ard_3-1-0_112079_2016-02-09_final
2016-02-09 11:36:31	ga_ls7e_ard_3-0-0_112080_2016-02-09_final
2016-02-09 11:36:55	ga_ls7e_ard_3-0-0_112081_2016-02-09_final
2016-02-09 11:37:19	ga_ls7e_ard_3-0-0_112082_2016-02-09_final
2016-02-09 11:37:43	ga_ls7e_ard_3-0-0_112083_2016-02-09_final
2016-02-09 11:38:07	ga_ls7e_ard_3-0-0_112084_2016-02-09_final
2016-02-13 09:30:56	ga_ls7e_ard_3-0-0_092075_2016-02-13_final
2016-02-13 09:31:20	ga_ls7e_ard_3-0-0_092076_2016-02-13_final
2016-02-15 09:19:22	ga_ls7e_ard_3-0-0_090077_2016-02-14_final
2016-02-15 09:19:46	ga_ls7e_ard_3-0-0_090078_2016-02-14_final
2016-02-15 09:20:10	ga_ls7e_ard_3-0-0_090079_2016-02-14_final
2016-02-15 09:20:34	ga_ls7e_ard_3-0-0_090080_2016-02-14_final
2016-02-15 09:20:58	ga_ls7e_ard_3-0-0_090081_2016-02-14_final
2016-02-15 09:21:22	ga_ls7e_ard_3-1-0_090082_2016-02-14_final
2016-02-15 09:21:46	ga_ls7e_ard_3-0-0_090083_2016-02-14_final
2016-02-15 09:22:10	ga_ls7e_ard_3-0-0_090084_2016-02-14_final
2016-02-15 09:22:34	ga_ls7e_ard_3-1-0_090085_2016-02-14_final

Return to ga_ls7e_ard_3 across February 2016 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

2016

February

All days