Assessing the Impact of TEC Fluctuations on ALOS-PALSAR Images

Luca Spogli, Elvira Musicò, Claudio Cesaroni, John Peter Merryman Boncori, Giorgiana De Franceschi, Roberto Seu

Abstract

Trans-ionospheric waves experience delay proportional to the Total Electron Content (TEC), being the number of free electrons present along a satellite-receiver ray path. TEC is a highly variable quantity, influenced by different helio-geophysical parameters, such as solar activity, season, time of the day, etc. Such large variability may lead to TEC spatial and temporal fluctuations over different scales, affecting the quality of the Synthetic Aperture Radar (SAR) signals and, in turn, limiting further developments of interferometric techniques, such as InSAR (Interferometric SAR). In the specific, the need of catching qualitative and quantitative correspondences between TEC fluctuations and InSAR image streaks is a key point to drive the development of future mitigation techniques to improve the quality of the SAR imaging. In this paper calibrated TEC values, derived from the RINEX data provided by the RING (Rete Integrata Nazionale GPS) network of GPS receivers, are analysed to assess the ionosphere conditions during the ALOS (Advanced Land Observing Satellite) – PALSAR (Phased Array type L-band Synthetic Aperture Radar) passages over central Italy.

References

  1. Bechor, N. B., H. A. Zebker, Measuring two-dimensional movements using a single InSAR pair, Geophys. Res. Lett., 33, L16311, 2006, DOI:10.1029/ 2006GL026883.
  2. Bürgmann, R., Rosen, P. A., Fielding, E. J., Synthetic aperture radar interferometry to measure Earth's surface topography and its deformation. Annual review of earth and planetary sciences, 28(1), 169- 209, 2000, DOI:10.1146/annurev.earth.28.1.169.
  3. Cesaroni, C., Spogli, L., Alfonsi, L., De Franceschi, G., Ciraolo, L., Monico, J. F. G., Scotto, C., Romano, V., Aquino, M., Bougard, B., L-band scintillations and calibrated total electron content gradients over Brazil during the last solar maximum. Journal of Space Weather and Space Climate, 5, A36, 2015a, DOI:10.1051/ swsc/2015038.
  4. Cesaroni C., A multi instrumental approach to the study of equatorial ionosphere over South-America, PhD dissertation, 2015b, DOI: 10.6092/unibo/amsdottorato/6889.
  5. Chen, A. C., Zebker, H. A., Reducing ionospheric effects in InSAR data using accurate coregistration. IEEE Transactions on Geoscience and Remote Sensing, 52(1), 60-70, 2014, DOI:10.1109/TGRS.2012.2236098.
  6. Ferretti, A., Monti Guarnieri, A., Prati, C., Rocca, F., Massonnet, D., InSAR Principles: Guidelines for SAR Interferometry Processing and Interpretation. The Nederlands, Noordwijk: ESA Publications. TM-19, 2007, ISBN: 92-9092-233-8.
  7. Foster, M.P., A.N. Evans. An evaluation of interpolation techniques for reconstructing ionospheric TEC maps. IEEE Trans. Geosci. Remote Sens., 46 (7), 2153- 2164, 2008, DOI: 10.1109/TGRS.2008.916642.
  8. Gray, A. L., Mattar, K. E., Sofko, G., Influence of ionospheric electron density fluctuations on satellite radar interferometry,Geophys. Res. Lett., 27(10), 1451-1454, 2000, DOI: 10.1029/2000GL000016.
  9. Hanssen, R.F., (2001) Radar Interferometry: Data Interpretation and Error Analysis. Kluwer Academic Publishers, Dordrecht, 328 pp. ISBN: 0-7923-6945-9.
  10. Kelley, M. C., The Earth's Ionosphere: Plasma Physics and Electrodynamics (2nd ed.). Academic Press, 2009, ISBN: 9780120884254.
  11. Mannucci, A.J., B.D. Wilson, D.N. Yuan, C.H. Ho, U.J. Lindqwister, T.F. Runge. A global mapping technique for GPS-derived ionospheric total electron content measurements. Radio Sci., 33 (3), 565, 1998, DOI: 10.1029/97RS02707.
  12. Meyer, F. J., Agram, P. S. Developing an Error Model for Ionospheric Phase Distortions in L-Band SAR and InSAR Data. In FRINGE'15: Advances in the Science and Applications of SAR Interferometry and Sentinel1 InSAR Workshop, Frascati, Italy, 23-27 March 2015.
  13. Reuveni, Y., Bock, Y., Tong, X., Moore, A. W., Calibrating interferometric synthetic aperture radar (InSAR) images with regional GPS network atmosphere models, Geophys. J. Int. 202, 2106-2119, 2015, DOI: 10.1093/gji/ggv253
  14. Sibson, R., A brief description of natural neighbor interpolation (Chapter 2). In V. Barnett. Interpreting Multivariate Data. Chichester: John Wiley. pp. 21-36, 1981.
  15. Zhu, W., Ding, X. L., Jung, H. S., Zhang, Q., Zhang, B. C., & Qu, W. (2016). Investigation of ionospheric effects on SAR Interferometry (InSAR): A case study of Hong Kong. Advances in Space Research, 58, 564- 576 2016, DOI: 10.1016/j.asr.2016.05.004.
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Paper Citation


in Harvard Style

Spogli L., Musicò E., Cesaroni C., Boncori J., Franceschi G. and Seu R. (2016). Assessing the Impact of TEC Fluctuations on ALOS-PALSAR Images . In Proceedings of the Fifth International Conference on Telecommunications and Remote Sensing - Volume 1: ICTRS, ISBN 978-989-758-200-4, pages 15-21. DOI: 10.5220/0006226700150021


in Bibtex Style

@conference{ictrs16,
author={Luca Spogli and Elvira Musicò and Claudio Cesaroni and John Peter Merryman Boncori and Giorgiana De Franceschi and Roberto Seu},
title={Assessing the Impact of TEC Fluctuations on ALOS-PALSAR Images},
booktitle={Proceedings of the Fifth International Conference on Telecommunications and Remote Sensing - Volume 1: ICTRS,},
year={2016},
pages={15-21},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006226700150021},
isbn={978-989-758-200-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fifth International Conference on Telecommunications and Remote Sensing - Volume 1: ICTRS,
TI - Assessing the Impact of TEC Fluctuations on ALOS-PALSAR Images
SN - 978-989-758-200-4
AU - Spogli L.
AU - Musicò E.
AU - Cesaroni C.
AU - Boncori J.
AU - Franceschi G.
AU - Seu R.
PY - 2016
SP - 15
EP - 21
DO - 10.5220/0006226700150021