Search ga_ls7e_ard_3 across June 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
2016-06-07 10:00:06	ga_ls7e_ard_3-0-0_097069_2016-06-07_final
2016-06-07 10:00:29	ga_ls7e_ard_3-0-0_097070_2016-06-07_final
2016-06-07 10:00:53	ga_ls7e_ard_3-0-0_097071_2016-06-07_final
2016-06-07 10:01:17	ga_ls7e_ard_3-0-0_097072_2016-06-07_final
2016-06-07 10:01:41	ga_ls7e_ard_3-0-0_097073_2016-06-07_final
2016-06-07 10:02:05	ga_ls7e_ard_3-0-0_097074_2016-06-07_final
2016-06-07 10:02:29	ga_ls7e_ard_3-0-0_097075_2016-06-07_final
2016-06-07 10:02:53	ga_ls7e_ard_3-1-0_097076_2016-06-07_final
2016-06-07 10:03:17	ga_ls7e_ard_3-0-0_097077_2016-06-07_final
2016-06-07 10:03:41	ga_ls7e_ard_3-0-0_097078_2016-06-07_final
2016-06-07 10:04:05	ga_ls7e_ard_3-0-0_097079_2016-06-07_final
2016-06-07 10:04:29	ga_ls7e_ard_3-0-0_097080_2016-06-07_final
2016-06-07 10:04:53	ga_ls7e_ard_3-0-0_097081_2016-06-07_final
2016-06-07 10:05:17	ga_ls7e_ard_3-0-0_097082_2016-06-07_final
2016-06-07 10:05:41	ga_ls7e_ard_3-0-0_097083_2016-06-07_final
2016-06-07 10:06:05	ga_ls7e_ard_3-0-0_097084_2016-06-07_final
2016-06-07 10:06:29	ga_ls7e_ard_3-0-0_097085_2016-06-07_final
2016-06-07 11:38:11	ga_ls7e_ard_3-0-0_113067_2016-06-07_final
2016-06-07 11:41:46	ga_ls7e_ard_3-0-0_113076_2016-06-07_final
2016-06-07 11:42:10	ga_ls7e_ard_3-0-0_113077_2016-06-07_final
2016-06-07 11:42:34	ga_ls7e_ard_3-0-0_113078_2016-06-07_final
2016-06-07 11:42:58	ga_ls7e_ard_3-0-0_113079_2016-06-07_final
2016-06-07 11:43:22	ga_ls7e_ard_3-1-0_113080_2016-06-07_final
2016-06-07 11:44:10	ga_ls7e_ard_3-0-0_113082_2016-06-07_final
2016-06-07 11:44:34	ga_ls7e_ard_3-0-0_113083_2016-06-07_final
2016-06-08 10:42:58	ga_ls7e_ard_3-0-0_104068_2016-06-08_final
2016-06-08 10:43:21	ga_ls7e_ard_3-0-0_104069_2016-06-08_final
2016-06-08 10:43:45	ga_ls7e_ard_3-1-0_104070_2016-06-08_final
2016-06-08 10:44:09	ga_ls7e_ard_3-0-0_104071_2016-06-08_final
2016-06-08 10:44:33	ga_ls7e_ard_3-0-0_104072_2016-06-08_final
2016-06-08 10:44:57	ga_ls7e_ard_3-0-0_104073_2016-06-08_final
2016-06-08 10:45:21	ga_ls7e_ard_3-0-0_104074_2016-06-08_final
2016-06-08 10:45:45	ga_ls7e_ard_3-0-0_104075_2016-06-08_final
2016-06-08 10:46:09	ga_ls7e_ard_3-0-0_104076_2016-06-08_final
2016-06-08 10:46:33	ga_ls7e_ard_3-0-0_104077_2016-06-08_final
2016-06-08 10:46:57	ga_ls7e_ard_3-0-0_104078_2016-06-08_final
2016-06-08 10:47:21	ga_ls7e_ard_3-0-0_104079_2016-06-08_final
2016-06-08 10:47:45	ga_ls7e_ard_3-0-0_104080_2016-06-08_final
2016-06-08 10:48:33	ga_ls7e_ard_3-0-0_104082_2016-06-08_final
2016-06-09 09:46:57	ga_ls7e_ard_3-0-0_095067_2016-06-09_final
2016-06-09 09:48:56	ga_ls7e_ard_3-0-0_095072_2016-06-09_final
2016-06-09 09:49:20	ga_ls7e_ard_3-1-0_095073_2016-06-09_final
2016-06-09 09:49:44	ga_ls7e_ard_3-0-0_095074_2016-06-09_final
2016-06-09 09:50:08	ga_ls7e_ard_3-0-0_095075_2016-06-09_final
2016-06-09 09:50:32	ga_ls7e_ard_3-0-0_095076_2016-06-09_final
2016-06-09 09:50:56	ga_ls7e_ard_3-0-0_095077_2016-06-09_final
2016-06-09 09:51:20	ga_ls7e_ard_3-0-0_095078_2016-06-09_final
2016-06-09 09:52:08	ga_ls7e_ard_3-0-0_095080_2016-06-09_final
2016-06-09 09:52:32	ga_ls7e_ard_3-0-0_095081_2016-06-09_final
2016-06-09 09:52:56	ga_ls7e_ard_3-0-0_095082_2016-06-09_final
2016-06-09 09:53:20	ga_ls7e_ard_3-0-0_095083_2016-06-09_final
2016-06-09 09:54:07	ga_ls7e_ard_3-0-0_095085_2016-06-09_final
2016-06-09 11:25:50	ga_ls7e_ard_3-0-0_111067_2016-06-09_final
2016-06-09 11:26:14	ga_ls7e_ard_3-0-0_111068_2016-06-09_final
2016-06-09 11:27:25	ga_ls7e_ard_3-0-0_111071_2016-06-09_final
2016-06-09 11:27:49	ga_ls7e_ard_3-0-0_111072_2016-06-09_final
2016-06-09 11:28:13	ga_ls7e_ard_3-0-0_111073_2016-06-09_final
2016-06-09 11:28:37	ga_ls7e_ard_3-0-0_111074_2016-06-09_final
2016-06-09 11:29:01	ga_ls7e_ard_3-0-0_111075_2016-06-09_final
2016-06-09 11:29:25	ga_ls7e_ard_3-0-0_111076_2016-06-09_final
2016-06-09 11:29:49	ga_ls7e_ard_3-0-0_111077_2016-06-09_final
2016-06-09 11:30:13	ga_ls7e_ard_3-0-0_111078_2016-06-09_final
2016-06-09 11:30:37	ga_ls7e_ard_3-0-0_111079_2016-06-09_final
2016-06-09 11:31:01	ga_ls7e_ard_3-0-0_111080_2016-06-09_final
2016-06-09 11:31:25	ga_ls7e_ard_3-0-0_111081_2016-06-09_final
2016-06-09 11:31:49	ga_ls7e_ard_3-1-0_111082_2016-06-09_final
2016-06-09 11:32:13	ga_ls7e_ard_3-0-0_111083_2016-06-09_final
2016-06-13 09:30:13	ga_ls7e_ard_3-0-0_091087_2016-06-13_final
2016-06-13 09:31:01	ga_ls7e_ard_3-0-0_091089_2016-06-13_final
2016-06-14 10:05:30	ga_ls7e_ard_3-0-0_098067_2016-06-14_final
2016-06-14 10:05:54	ga_ls7e_ard_3-0-0_098068_2016-06-14_final
2016-06-14 10:06:18	ga_ls7e_ard_3-0-0_098069_2016-06-14_final
2016-06-14 10:06:42	ga_ls7e_ard_3-0-0_098070_2016-06-14_final
2016-06-14 10:07:06	ga_ls7e_ard_3-0-0_098071_2016-06-14_final
2016-06-14 10:07:30	ga_ls7e_ard_3-0-0_098072_2016-06-14_final
2016-06-14 10:07:53	ga_ls7e_ard_3-0-0_098073_2016-06-14_final
2016-06-14 10:08:17	ga_ls7e_ard_3-0-0_098074_2016-06-14_final
2016-06-14 10:08:41	ga_ls7e_ard_3-0-0_098075_2016-06-14_final
2016-06-14 10:09:05	ga_ls7e_ard_3-0-0_098076_2016-06-14_final
2016-06-14 10:10:17	ga_ls7e_ard_3-0-0_098079_2016-06-14_final
2016-06-14 10:10:41	ga_ls7e_ard_3-1-0_098080_2016-06-14_final
2016-06-14 10:11:05	ga_ls7e_ard_3-0-0_098081_2016-06-14_final
2016-06-14 10:11:29	ga_ls7e_ard_3-0-0_098082_2016-06-14_final
2016-06-14 10:11:53	ga_ls7e_ard_3-0-0_098083_2016-06-14_final
2016-06-14 10:12:17	ga_ls7e_ard_3-0-0_098084_2016-06-14_final
2016-06-14 10:12:41	ga_ls7e_ard_3-0-0_098085_2016-06-14_final
2016-06-16 09:53:09	ga_ls7e_ard_3-0-0_096067_2016-06-16_final
2016-06-16 09:54:20	ga_ls7e_ard_3-0-0_096070_2016-06-16_final
2016-06-16 09:54:44	ga_ls7e_ard_3-0-0_096071_2016-06-16_final
2016-06-16 09:55:08	ga_ls7e_ard_3-0-0_096072_2016-06-16_final
2016-06-16 09:55:32	ga_ls7e_ard_3-0-0_096073_2016-06-16_final
2016-06-16 09:55:56	ga_ls7e_ard_3-0-0_096074_2016-06-16_final
2016-06-16 09:56:20	ga_ls7e_ard_3-0-0_096075_2016-06-16_final
2016-06-16 09:56:44	ga_ls7e_ard_3-0-0_096076_2016-06-16_final
2016-06-16 09:57:08	ga_ls7e_ard_3-0-0_096077_2016-06-16_final
2016-06-16 09:57:32	ga_ls7e_ard_3-0-0_096078_2016-06-16_final
2016-06-16 09:57:56	ga_ls7e_ard_3-0-0_096079_2016-06-16_final
2016-06-16 09:58:20	ga_ls7e_ard_3-0-0_096080_2016-06-16_final
2016-06-16 09:58:44	ga_ls7e_ard_3-0-0_096081_2016-06-16_final
2016-06-16 09:59:08	ga_ls7e_ard_3-0-0_096082_2016-06-16_final

Return to ga_ls7e_ard_3 across June 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

June

All days