Skip to main content
Log in

Simple algorithm for soil moisture retrieval with co-polarized SAR data

  • Published:
Journal of Electronics (China)

Abstract

In this paper, an empirical methodology to retrieve bare soil moisture by Synthetic Aperture Radar (SAR) is developed. The model is based on Advanced Integral Equation Model (AIEM). Since AIEM cannot express cross-polarized backscattering coefficients accurately, we propose an empirical model to retrieve soil moisture for bare farmland only with co-polarized SAR data. The soil moisture can be obtained by solving an equation of HH and VV polarized data without any field measurements. Both simulated and real SAR data are used to validate the accuracy of the model. This method is especially effective in a large area where the surface roughness is difficult to be completely measured.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Fawwaz T. Ulaby, Richard K. Moore, and Adrian K. Fung. Microwave Remote Sensing (volume II): Radar Remote Sensing and Surface Scattering and Emission Theory. London, Addison-Wesley Press, 1982, Chapter 11–Chapter 12.

    Google Scholar 

  2. Adrian K. Fung, Zongqian Li, and K. S. Chen. Backscattering from a randomly rough dielectric surface. IEEE Transactions on Geoscience and Remote Sensing, 30(1992)2, 356–369.

    Article  Google Scholar 

  3. Tzong-Dar Wu, K. S. Chen, Jiancheng Shi, et al.. A transition model for the reflection coefficient in surface scattering. IEEE Transactions on Geoscience and Remote Sensing, 39(2001)9, 2040–2050.

    Article  Google Scholar 

  4. Qin Li, Jiancheng Shi, and K. S. Chen. A generalized power law spectrum and its applications to the backscattering of soil surfaces based on the integral equation model. IEEE Transactions on Geoscience and Remote Sensing, 40(2002)2, 271–280.

    Article  Google Scholar 

  5. T. D. Wu and K. S. Chen. A reappraisal of the validity of the IEM model for backscattering from rough surface. IEEE Transactions on Geoscience and Remote Sensing, 42(2004)4, 743–753.

    Article  Google Scholar 

  6. Shuguo Wang, Xujun Han, and Xin Li. Derivation of surface soil moisture using multi-angle ASAR data in the middle stream of heihe river basin. Geoscience and Remote Sensing Symposium, IGARSS’09, Kaapstad, South Africa, July 12–17, 2009, 3, Vol. 5, 18–521.

  7. Lina Xu, Jiong Li, and Ruiqing Niu. Soil moisture estimation over Jianghan plain using ENVISAT ASAR data. 2010 International Conference on Multimedia Technology (ICMT), Ningbo, China, October 29–31, 2010, 1–4.

  8. Zhen Li, Xin Ren, and Xinwu Li. Soil moisture measurement and retrieval using Envisat ASAR imagery. Geoscience and Remote Sensing Symposium, 2004. IGARSS’04, Anchorage, Alaska, USA, September 20–24, 2004, 5, 3539–3542.

  9. Peng Guo, Jiancheng Shi, Qiang Liu, et al.. A new algorithm for soil moisture retrieval with l-band radiometer. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, PP (2013)99, 1–9. DOI: 10.1109/JSTARS. 2013. 2244852.

    Article  Google Scholar 

  10. Yisok Oh, Kamal Sarabandi, and Fawwaz T. Ulaby. Semi-empirical model of the ensemble-averaged differential mueller matrix for microwave backscattering from bare soil surfaces. IEEE Transactions on Geoscience and Remote Sensing, 40(2002)6, 1348–1355.

    Article  Google Scholar 

  11. Mehrez Zribi and Monique Dechambre. A new empirical model to retrieve soil moisture and roughness from radar data. Remote Sensing of Environment, 84(2002)1, 42–52.

    Article  Google Scholar 

  12. M. Zribi, T. N. Baghdadi, N. Holah, et al.. New methodology for soil surface moisture estimation and its application to ENVISAT-ASAR multi-incidence data inversion. Remote Sensing of Environment, 96 (2005), 485–496.

    Article  Google Scholar 

  13. Yu Fan and Zhao Yingshi. A new method for soil moisture inversion by synthetic aperture radar. Geomatics and Information Science of Wuhan University, 35(2010)3, 318–321 (in Chinese). 余凡, 赵英时. 合成孔径雷达反演裸露地表土壤水分的新方. 武汉大学学报·信息科学, 35(2010)3, 318–321.

    Google Scholar 

  14. J. C. Shi and K. S. Chen. Estimation of bare surface soil moisture with l-band multi-polarization radar measurements. Geoscience and Remote Sensing Symposium, 2005, IGARSS’05, Seoul, Korea, July 25–29, 2005, Vol. 3, 2191–2194.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dan Wang.

Additional information

Supported by the Research Program of Science and Technology at Universities of Inner Mongolia Autonomous Region (NJZZ11069) and the Natural Science Foundation of Inner Mongolia Autonomous Region (2011BS0904).

Communication author: Wang Dan, born in 1989, female, Master Degree.

About this article

Cite this article

Wang, D., Huang, P., Huang, M. et al. Simple algorithm for soil moisture retrieval with co-polarized SAR data. J. Electron.(China) 30, 237–242 (2013). https://doi.org/10.1007/s11767-013-3047-9

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11767-013-3047-9

Key words

CLC index

Navigation