Dielectric properties of saline soil based on a modified Dobson dielectric model

Abstract

Soil salinization is a major concern for agricultural development in arid areas. In this paper, a modified Dobson dielectric model was applied to simulate the dielectric constant of saline soil in the Ugan-Kuqa river delta oasis of Xinjiang Uygur autonomous region, northwestern China. The model performance was examined through analyzing the influences of its parameters on the soil dielectric constant and the relationship between radar backscattering coefficient and the dielectric constant of saline soil. The results of the study indicate that: (1) The real part of the soil dielectric constant is affected by soil water content at low radar frequencies; the imaginary part is closely related with both the soil water content and soil salt content. (2) The soil water and salt contents are related with the coefficient of dialectical loss, which is consistent with the natural conditions of saline soil in arid areas and provides valuable references for the study of soil dielectric properties. (3) The changes of soil water content and soil salt content have instant influences on the dielectric constant of saline soil. Subsequently, the radar backscattering coefficient is affected to respond to the dielectric constant of saline soil. The radar backscattering coefficient is most responsible to the radar’s cross polarization pattern with a correlation coefficient of R 2=0.75. This study provides a potential method to monitor soil salinization and soil water content by using a soil dielectric model and radar techniques.

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References

  1. Amezketa E. 2006. An integrated methodology for assessing soil salinization, a pre-condition for land desertification. Journal of Arid Environments, 67(4): 594–606.

    Article  Google Scholar 

  2. Attema E P W, Ulaby F T. 1978. Vegetation modeled as a water cloud. Radio Science, 13(2): 357–364.

    Article  Google Scholar 

  3. Bindlish R, Barros A P. 2001. Parameterization of vegetation backscatter in radar-based, soil moisture estimation. Remote Sensing of Environment, 76(1): 130–137.

    Article  Google Scholar 

  4. Davenport I J, Fernandez G J, Gurney R J. 2005. A sensitivity analysis of soil moisture retrieval from the Tau-Omega microwave emission model. IEEE Transactions on Geoscience and Remote Sensing, 43(6): 1304–1316.

    Article  Google Scholar 

  5. Dehaan R L, Taylor G R. 2002. Field-derived spectra of salinized soils and vegetation as indicators of irrigation-induced soil-salinization. Remote Sensing of Environment, 80: 406–417.

    Article  Google Scholar 

  6. Dong X G, Zhou J L, Chen Y B. 2007. Water and Salt Monitoring in Arid Inland Areas: Model and Application. Beijing: Science Press, 1–27. (in Chinese)

    Google Scholar 

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

    Article  Google Scholar 

  8. Ha X P. 2009. Remote sensing-based monitoring model for soil salinization in arid areas. MSc Thesis. Urumqi: Xinjiang University. (in Chinese)

    Google Scholar 

  9. He Y F, Zhang B, Ma C Q. 2004. Study on dynamic change of land sali-alkalization in Songnen Plain—a case study in Nongpan county. Journal of Soil and Water Conservation, 18(3): 146–153. (in Chinese)

    Google Scholar 

  10. Hu Q R. 2003. Studies on microwave dielectric behavior of moist salt soil and inversion of the moisture and salt content. PhD Dissertation. Beijing: Institute of Remote Sensing Application, Chinese Academy of Sciences. (in Chinese)

    Google Scholar 

  11. Ma X D, Chen Y N, Zhu C G, et al. 2011. The variation in soil moisture and the appropriate groundwater table for desert riparian forest along the lower Tarim River. Journal of Geographical Sciences, 21(1): 150–162.

    Article  Google Scholar 

  12. Pankova E I. 2007. A new monograph on salt-affected soils and salinization dynamics in the Terek River delta. Eurasian Soil Science, 40(1): 99–100.

    Article  Google Scholar 

  13. Qiao Y L.1996. An application of aerial remote sensing to monitor salinization at Xinding Basin. Advances in Space Research, 18(7): 133–139.

    Article  Google Scholar 

  14. Saysel A K, Barlas Y. 2001. A dynamic model of salinization on irrigated lands. Ecological Modelling, 139(2–3): 177–199.

    Article  Google Scholar 

  15. Shao Y, Lu Y, Dong Q, et al. 2002. Study on soil microwave dielectric characteristic as salinity and water content. Journal of Remote Sensing, 6(6): 423–428. (in Chinese)

    Google Scholar 

  16. Shi J C, Chen K S, Li Q, et al. 2002. A Parameterized surface reflectivity model and estimation of bare surface soil moisture with L-band radiometer. IEEE Transactions on Geoscience and Remote Sensing, 40(12): 2674–2686.

    Article  Google Scholar 

  17. Shi X X, Wang J, Ren C Y, et al. 2004. Study on the modeling of soil salinization in semi-arid area based on GIS and Geo-CA model. Journal of Northeast Normal University, 36(2): 88–94. (in Chinese)

    Google Scholar 

  18. Stasyuk N V. 2001. Temporal dynamics of soil cover salinization in the Terek delta. Russian Journal of Ecology, 32(1): 22–28.

    Article  Google Scholar 

  19. Tian C Y, Zhou H F, Liu G Q. 2000. The proposal on control of soil salinizing and agricultural sustaining development in 21’s century in Xinjiang. Arid Land Geography, 23(3): 178–181. (in Chinese)

    Google Scholar 

  20. Ulaby F T, Sarabandi K, McDonald K, et al. 1990. Michigan microwave canopy scattering model. International Journal of Remote Sensing, 11(7): 1223–1253.

    Article  Google Scholar 

  21. Wang Z Q. 1993. China Salinity Soil. Beijing: Science Press, 400–515. (in Chinese)

    Google Scholar 

  22. Wang J M, Shi J C, Shao Y. 2005. Soil moisture content monitoring based on ERS wind scatterometer data. Journal of China University of Mining and Technology, 15(4): 305–308.

    Google Scholar 

  23. Wu S L. 2006. Simulation of a combined passive/active microwave remote sensing approach for soil moisture retrieval. Proceedings of the Third International Symposium on Future Intelligent Earth Observation Satellites. Beijing: Science Press, 305–308. (in Chinese)

    Google Scholar 

  24. Xiong W C. 2005. Studies on microwave dielectric behavior of moist salt soil and inversion of the moisture and salt content. MSc Thesis. Beijing: Institute of Remote Sensing Application, Chinese Academy of Sciences. (in Chinese)

    Google Scholar 

  25. Yang H, Shi J, Li Z, et al. 2003. Temporal and spatial soil moisture change pattern detection using multi temporal Radarsat SCANSAR images. Proceedings of IGRASS, IEEE, 2: 1420–1422.

    Google Scholar 

  26. Zhang J X, Liu Z J, Sun X X. 2009. Changing landscape in the three gorges reservoir area of Yangtze River from 1977 to 2005: land use/land cover, vegetation cover changes estimated using multi-source satellite data. International Journal of Applied Earth Observation and Geoinformation, 11(6): 403–412.

    Article  Google Scholar 

  27. Zhao Q G. 1991. Land degradation and its control. China Land Science, 5(2): 22–25. (in Chinese)

    Google Scholar 

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Correspondence to Jianli Ding.

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Tashpolat, N., Ding, J. & Yu, D. Dielectric properties of saline soil based on a modified Dobson dielectric model. J. Arid Land 7, 696–705 (2015). https://doi.org/10.1007/s40333-015-0130-0

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Keywords

  • saline soil
  • dielectric constant
  • dielectric constant model
  • backscattering coefficient
  • Radarsat-2 images