Soil Surface Moisture From EnviSat RA-2: From Modelling Towards Implementation

  • S. M. S. BramerEmail author
  • P. A. M. Berry
Conference paper
Part of the International Association of Geodesy Symposia book series (IAG SYMPOSIA, volume 135)


This paper presents the current status of ongoing research into the extraction of soil surface moisture data from Radar Altimeter backscatter. One of the motivations for this work is to facilitate comparisons with GRACE data over specific targets such as the Okavango Delta.

Natural land targets for the monitoring of Radar Altimeter backscatter have previously been identified and modelled, utilising data provided by the ERS-1 Geodetic and 35-day Missions. These spatial models have been employed for cross-calibration between ERS-1/2 ice and ocean mode sigma0. The inherent variability of all but a few desert regions meant that the original techniques could not be used beyond these calibration zones.

A new automated technique has made it possible to develop models of wetter regions with the aim of taking these models as close to “dry earth” conditions as possible.

In parallel with this process a semi-empirical model of Radar Altimeter backscatter, which makes use of engineering and scientific parameters, has been developed and is undergoing final calibration.

The use of the spatial models in conjunction with the new semi-empirical backscatter model will enable predictions of soil surface moisture levels using values provided by EnviSat RA-2 backscatter.


Sigma0 Model Soil Surface Moisture Okavango Delta Radar Altimeter Grace Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors would like to thank the European Space Agency for providing the ERS and Envisat data used in this study.


  1. Andersen, O.B., P. Berry, J. Freeman, F.G. Lemoine, S.C. Lutsckhe, F. Jascobsen, and M. Butts (2008). Satellite Altimetry and GRACE gravimetry for studies of annual water storage variations in Bangladesh. Terr. Atm. Ocean Sci., 19(1–2), 47–52.Google Scholar
  2. Beneveniste, J. et al. (2002). ENVISAT RA-2/MWR Product Handbook, Issue 1.2 PO-TN-ERS-RA-0050, European Space Agency.Google Scholar
  3. Berry, P.A.M., A. Jasper, and H. Bracke (1997). Retracking ERS-1 altimeter waveforms overland for topographic height determination: an expert system approach. ESA Pub. SP414, 1, 403–408.Google Scholar
  4. Bramer, S.M.S. and P.A.M. Berry (2006). Cross Calibration of Multi-Mission Altimeter and TRMM PR Sigma0 Over Natural Land Targets. In: Proceedings of the Symposium on 15 Years Progress in Radar Altimetry, Venice, Italy, March 13–17.Google Scholar
  5. Bramer, S.M.S., P.A.M. Berry, J.A. Freeman, and B. Rommen (2007). Global analysis of Envisat Ku and S Band Sigma0 over all Surfaces. In: Proceedings, ESA: ENVISAT Symposium, Montreux, Switzerland, April 23–27.Google Scholar
  6. British Columbia Ministry of Agriculture, Food and Fisheries. (2002). Water Conservation Factsheet. Order No. 619.000-1.Google Scholar
  7. Capp, P. (2001). Altimeter waveform product ALT>WAP compact user guide, Issue 4.0, PF-UG-NRL-AL-001, Infoterra Ltd.Google Scholar
  8. Geoscience Australia (2004). Scanned 1:250 000 Geology Maps Commonwealth of Australia
  9. Johnson, C.P.D. (2002). Geodetic applications of satellite radar altimetry over land. PhD Thesis, De Montfort University, UK.Google Scholar
  10. Johnson, C.P.D. and P.A.M. Berry (2002). Cross-calibration and validation of altimeter backscatter over natural land targets. In: Proceedings of European Geophysical Assembly, Nice, France, April 21–26.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.EAPRS LabDe Montfort UniversityLeicesterUK
  2. 2.EAPRS LabDe Montfort UniversityLeicesterUK

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