10.5880/GFZ.1.1.2015.001
Vey, Sibylle
GFZ German Research Centre for Geosciences
Güntner, Andreas
GFZ German Research Centre for Geosciences
Wickert, Jens
GFZ German Research Centre for Geosciences
Blume, Theresa
GFZ German Research Centre for Geosciences
Ramatschi, Markus
GFZ German Research Centre for Geosciences
Supplement to: Long-term soil moisture dynamics derived from GNSS interferometric reflectometry: A case study for Sutherland, South Africa
GFZ Data Services
2015
GNSS
reflectometry
soil moisture
signal-to-noise ratio
Vey, Sibylle
GFZ German Research Centre for Geosciences
Vey, Sibylle
GFZ German Research Centre for Geosciences
Güntner, Andreas
GFZ German Research Centre for Geosciences
Wickert, Jens
GFZ German Research Centre for Geosciences
Blume, Theresa
GFZ German Research Centre for Geosciences
Ramatschi, Markus
GFZ German Research Centre for Geosciences
Helmholtz Alliance of Remote Sensing of Earth System Dynamics (HGF EDA)
Benjamin Creutzfeldt
South African Astronomic Observatory
Pieter Fourie
South African Astronomic Observatory
Jaci Cloete
South African Astronomic Observatory
2015-06-30
2008-01-01/2014-09-01
en
10.1007/s10291-015-0474-0
10.1002/wat2.1097
10.1109/JSTARS.2009.2033612
45628 Bytes
1 Files
text/plain
CC BY 4.0
We provide data of a case study from the GNSS station Sutherland, South Africa (SUTM). This data set contains soil moisture derived from GNSS data using reflectometry. It covers a time period from January 1, 2008 to September 1, 2014 and gives the integral soil moisture over an area of 60 by 60 m for the uppermost surface (max. down to 10 cm. depth) The data are daily averages based on daily measurements from 6 different satellites. The GNSS derived soil moisture was validated by Time Domain Reflectometry (TDR) observations. The detailed description of the processing, the evaluation with TDR and the discussion of the results is described in Vey et al. (2015).The data are provided in ASCII format with four colums: (1) year (YEAR) (2) day of the year (DOY) (3) volumetric soil moisture as average over all satellite tracks (SM Vol %) (4) accuracy, root mean square error of soil moisture from a single satellite track compared to the mean of all satellites (RMSE Vol %).
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GNSS station Sutherland (SUTM) in South Africa