Journal of the Indian Society of Remote Sensing

, Volume 42, Issue 3, pp 589–600 | Cite as

Studies on Textural and Compositional Characteristics of Sand and Clay Mixtures Using Hyperspectral Radiometry

Research Article
First Online:
Received:
Accepted:

Abstract

This paper examines the hyperspectral signatures (in the Visible Near Infrared (VNIR)-Shortwave Infrared (SWIR) regions) of soil samples with varying colour and minerals. 36 samples of sands (from river and beach) with differing clay contents were examined using a hyperspectral radiometer operating in the 350–2,500 nm range, and the spectral curves were obtained. Analysis of the spectra indicates that there is an overall increase in the reflectance in the VNIR-SWIR region with an increase in the content of kaolinite clay in the sand samples. As regards the red and black clays and sand mixtures, the overall reflectance increases with decreasing clay content. Several spectral parameters such as depth of absorption at 1,400 nm and 1,900 nm regions, radius of curvature of the absorption troughs, slope at a particular wavelength region and the peak reflectance values were derived. There exists a correlation between certain of these spectral parameters (depth, slope, position, peak reflectance, area under the curve and radius of the curve) and the compositional and textural parameters of the soils. Based on these well-defined relations, it is inferred that hyperspectral radiometry in the VNIR and SWIR regions can be used to identify the type of clay and estimate the clay content in a given soil and thus define its geotechnical category.

Keywords

Hyperspectral radiometry Sand and clays Geotechnical properties 
This is a preview of subscription content, log in to check access.

References

  1. Ben-Dor E., Goldlshleger N., Benyamini Y., Agassi M., & Blumberg, D. G. (2003). The spectral reflectance properties of soil structural crusts in the 1.2 to 2.5 m spectral region. Soil Science Society of America Journal, 67(1), 289–299.Google Scholar
  2. Bilgili, A. V., Cullu, M. A., van Es, H., Aydemir, A., & Dikilitas, S. K. (2009). Using hyperspectral VNIR spectroscopy for the characterisation of soil salinity, sustainable management of saline waters and salt affected soils for agriculture — Proceedings of the Second Bridging Workshop.Google Scholar
  3. Chang, C. W., Laird, D. A., Mausbach, M. J., & Hurburgh, C. R., Jr. (2001). Near-Infrared eflectance Spectroscopy-Principal components regression analyses of soil properties. Soil Science Society of America Journal, 65, 480–490.CrossRefGoogle Scholar
  4. Christy, C. D., & Dyer, S. A. (2006). Estimation of soil properties using a combination of spectral and scalar sensor data. Instrumentation and Measurement Technology Conference, 729–734.Google Scholar
  5. Clark. (1999). Spectroscopy of rocks and minerals, and principles of spectroscopy chapter 1: Spectroscopy of rocks and minerals, and principles of spectroscopy, In Manual of remote sensing, Volume 3, remote sensing for the earth sciences. ASPRS.Google Scholar
  6. Dawson, T. P. (2000). The potential for estimating chlorophyll content from a vegetation canopy using the medium resolution imaging spectrometer. International Journal of Remote Sensing, 21(10), 2043–2051.Google Scholar
  7. Farooq, S. (2012). Spectral reflectance of land covers, Department of Geology, Aligarh Muslim University, Aligarh - 202 002 (India), http://www.cps-amu.org/sf/notes/m1r-1-8.htm.2012.
  8. Fitton, G. (1997). X-ray fluorescence spectrometry. In R. Gill (Ed.), Modern Analytical Geochemistry: An Introduction to Quantitative Chemical Analysis for Earth, Environmental and Materials Scientists (pp. 87–115). Harlow: Addison Wesley Longman Ltd.Google Scholar
  9. Hewson R. D., Cudahy T. J., Jones M., & Thomas, M. (2012). Investigations into soil composition and texture using infrared spectroscopy (2–14 μm) applied and environmental soil science volume 2012, Article ID 535646, 12 pages.Google Scholar
  10. Hunt, G. R. (1977). Spectral signatures of particulate minerals in the visible and near infrared. Geophysics, 42(3), 501–513.CrossRefGoogle Scholar
  11. Kaniraj, S. R. (1988). Design aids in soil mechanics foundation engineering. New Delhi: Tata Mc-Graw hill Publishing Company Private Ltd.Google Scholar
  12. Kariuki, P. C. (2003). Spectroscopy and swelling soils—An integrated approach. A thesis work. Delft University of Technology.Google Scholar
  13. Kariuki, P. C., & Van der Meer, F. D. (2003). Swelling clay mapping for characterizing expansive soils; results from laboratory spectroscopy and hysens dais analysis. Presented at the 3rd EARSeL Workshop on Imaging Spectroscopy, Oberpfaffenhofen, May (13–16) 2003.Google Scholar
  14. Lenka V., & Plevove, E. (2005). Identification of Clay Minerals and Micas in Sedimentary Rocks. Geomater, 2(2 (138)), 167–175.Google Scholar
  15. Lucas, Y., & Gagelli, J. (2002). Hyperspectral detection of sand, Seventh International Conference on Remote Sensing for Marine and Coastal Environments, Miami, Florida.Google Scholar
  16. Magendran T., Sanjeevi S., Bhattacharya A. K., Surada S. (2011). Hyperspectral Radiometry to Estimate the Grades of Iron Ores of Noamundi, India — A Preliminary Study. Journal of Indian Society of Remote Sensing, 39(4), 473–483.Google Scholar
  17. Matinfar, H. R., Alavi Panah, S. K., Zand, F., & Khodaei, K. (2011). Detection of soil salinity changes and mapping land cover types based upon remotely sensed data. Arabian Journal of Geosciences, 6(3), 729–734.Google Scholar
  18. Namdar, A. (2010). Mineralogy in Geotechnical Engineering. Journal of Engineering Science and Technology Review, 3(1), 108–110.Google Scholar
  19. Orueta, & Ustin. (1998). Remote Sensing of Soils in the Santa Monica Mountains: II. Hierarchical Foreground and Background Analysis. Remote Sensing of Environment, 68, 138–151.CrossRefGoogle Scholar
  20. Rossel, V., Catlle, S. R., Ortega A. S., & Fouad, Y. (2009). In situ measurements of soil colour, mineral composition and clay content byvis–NIR spectroscopy. Geoderma, 150, 253–266.Google Scholar
  21. Rossel V., Chappell A., Caritat P., & McKenzie, N. J. (2010). Mapping the information content of Australian visible-near infrared soil spectra. 19th World Congress of Soil Science, Soil Solutions for a Changing World.Google Scholar
  22. Stenberga, B., Rossel, R. A. V., Mouazen, A. M., & Wetterlind, J. (2010). Visible and near infrared spectroscopy in soil science Advances in Agronomy (Vol. 107, pp. 163–215). Burlington: Academic.Google Scholar
  23. Terzaghi, K., Peck, R. B. & Mesri, G. (1996). Soil mechanics in engineering practice. New York: John Wiley & SonsGoogle Scholar
  24. Tobias H. K., Dewit J., Buckley S. J., Thurmond J. B., Hunt D. W., & Swennen, R. (2012). Hyperspectral image analysis of different carbonate (limestone, karst and hydrothermal dolomites): the Quarry case study (Cantabria, North-west Spain). Sedimentology, 59, 623–645.Google Scholar
  25. Zhang, T., Li, L., & Zheng, B. (2013). Estimation of agricultural soil properties with imaging and laboratory spectroscopy. Journal of Applied Remote Sensing, 7(1), 073587. doi: 10.1117/1.JRS.7.073587.

Copyright information

© Indian Society of Remote Sensing 2014

Authors and Affiliations

  1. 1.Department of Civil EngineeringAnna UniversityChennaiIndia
  2. 2.Department of GeologyAnna UniversityChennaiIndia

Personalised recommendations