Estimate of soil Cation Exchange Capacity using reflectance spectrometry

Document Type : Scientific article

Authors

1 Ph.D. Student of Forest Engineering, Department of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Karaj, I.R. Iran.

2 Associate Professor, Department of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Karaj, I.R. Iran.

3 Associate Professor, Department of Civil Engineering, University of Tehran, Tehran, I.R. Iran.

4 Associate Professor, Department of Soil Science, Faculty of Agriculture, Tarbiat Modares University, Tehran, I.R. Iran.

5 Professor, Department of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Karaj, I.R. Iran.

6 Ph.D. Student of RS & GIS, Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, I.R. Iran.

Abstract

CEC is the most important soil engineering properties used to determine the swelling potential of soil. Measuring CEC of soil is difficult, time-consuming, costly and consuming of dangerous chemical materials. In this study the ability of spectral reflectance to estimate the amount of CEC were investigated. So 45 soil samples were collected from Namkhaneh series of Kheyrood kenar Forest and their reflectance were measured in the range 350-2500 nm in dark room. Then the relationship between CEC and reflectance and first derivative of reflectance were analyzed by single band Pearson correlation, PLSR and two groups of narrowband soil indices (RI, DI). The results of this study showed that narrowband indices have stronger relationship than PLSR and the DI index in case first derivative have highest correlation (R2=0.82, RMSE=5.01). In the PLSR method between reflectance and CEC strong relationship was observed while the indices of first derivation reflectance and CEC have stronger relationship than row reflectance. So reflectance can be as a nondestructive, fast, easy and Cost effective method to estimate the CEC.

Keywords

References

- Amini, M., K. C. Abbaspour, H. Khademi, N. Fathianpour, M. Afyuni & R. Schulin, 2005. Neural network models to predict cation exchange capacity in arid regions of Iran, European Journal of Soil Science, 56(4): 551-559.
- Bahrami, H. A., S. Mirzaei, A. Darvishi Boloorani & S. K. Darvishzadeh, Alavipan ah, 2016. Analysis of Dust Storm Effects on Reflectance Spectra of Wheat Canopy, Journal of Remote Sensing and GIS, 7(4): 13-26. (In Persian)
- Bayat, H., N. Davatgar & M. Jalali, 2014. Prediction of CEC using fractal parameters by artificial neural networks, International Agrophys, 28(2): 143-152.
- Bower, C. A., R. F. Reitmeir & M. Fireman, 1952. Exchangeable cation analysis of saline and alkali soils, Soil Science, 73(4): 251-261.
- Bilgili, A.V., H. M. Van Es, F. Akbas, A. Durak & W. D. Hively, 2010. Visible-near infrared reflectance spectroscopy for assessment of soil properties in a semi-arid area of Turkey, Journal of Arid Environments, 74(2): 229-238.
- Blanco, M., J. Coello, H. Iturriaga, S. Maspoch & C. De La Pezuela, 1996. Quantitation of the active compound and major excipients in a pharmaceutical formulation by near infrared diffuse reflectance spectroscopy with fibre optical probe, Analytica Chimica Acta, 333(1-2): 147-156.
- Bartholomeus. H. M., M. E. Schaepman, L. Kooistra, A. Stevens, W. B. Hoogmoed & O. S. P. Spaargaren, 2008. Spectral reflectance based indices for soil organic carbon quantification, Geoderma, 145(1-2): 28-36.
- Clark, R. N., 1999. Spectroscopy of rocks and minerals, and principles of spectroscopy, Manual of Remote Sensing, 3: 3-58.
- Chen, F. H., 1988. Foundation on expansive soils, Elsevier Science Publishers.
- Das, B. M., 2008. Advanced Soil Mechanic. Taylor and Francis, New York, 370p.
- Gao, B. C. & A. F. H. Goetz, 1995. Retrieval of Equivalent Water Thickness and Information Related to Biochemical Components of Vegetation Canopies from AVIRIS Data, Remote Sensing of Environment. 52(3): 155-162.
- Ghorbani, H., H. Kashi, N. Hafezi Moghaddas & S. Emamghlozadeh, 2015. Estimation of Soil Cation Exchange Capacity using Multiple Regression, Artificial Neural Networks, and Adaptive Neuro-fuzzy Inference System Models in Golestan Province, Iran, Communications in Soil Science and Plant Analysis, 46(6): 763-780.
- Cho, M. A., A. Skidmore, F. Corsi, S. E. Van Wieren & I. Sobhan, 2007. Estimation of green grass/herb biomass from airborne hyperspectral imagery using spectral indices and partial least squares regression, International Journal of Applied Earth Observation and Geoinformation, 9(4): 414-424
 
- Gomez, C., P. Lagacherie & G. Coulouma, 2008. Continuum removal versus PLSR method for clay and calcium carbonate content estimation from laboratory and airborne hyperspectral measurements, Geoderma, 148(2):141-148.
- Hosseini Arablu, N., H. Khodaverdiloo, D. SH. Ghorbani & H. R. Momtaz, 2015. Effect of grouping soils based on their organic carbon and clay content on performance of hierarchical pedotransfer functions of soil cation exchange capacity, Electronic Journal of Soil Management and Sustainable Production, 4(4): 215-23. (In Persian)
- Hamberg, D. J., 1985. A simplified method for predicting heave in expansive soils. MS thesis. Colorado State University. Fort Collins, 150 p.
- Hansena, P. M. & J. K. Schjoerring, 2003. Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least squares regression, Remote sensing of environment, 86(2): 542-553.
- Haest, M., T. Cudahy, A. Rodger, C. Laukam, E. Martens & M. Caccetta, 2013. Unmixing the effects of vegetation in airborne hyperspectral mineral maps over the Rocklea Dome iron-rich palaeochannel system (Western Australia), Remote Sensing of Environment, 129(1): 17-31.
- Kariuki, P. C., F. Van der Meer & P. N. W. Verhoef, 2003. Cation exchange capacity (CEC) determination from spectroscopy, Journal of Remote Sensing, 24(1): 161-167.
- Zhang, J., Y. Tian, Y. Zhu, X. Yao & W. Cao, 2009. A near-infrared spectral index for estimating soil organic matter content, Ying yong sheng tai xue bao=The journal of applied ecology, 20(8): 1896-1904.
- Knadel, M., B. Stenberg, F. Deng, A. Thomsen & M. H. Greve, 2013. Comparing predictive abilities of three visible-near infrared spectrophotometers for soil organic carbon and clay determination, Journal of near infrared spectroscopy, 21(1): 67-80.
- Martens, H. & T. Naes, 1989. Multivariate calibration, Second edition. John Wiley and Sons Ltd press, Chichester, UK, 419 p.
- Mousavi, F. & E. Abdi, 2015. Studying the effect of polymeric materials in improving the potential of forest roads soil volume change, Forest Research and development, 1(2): 145-153. (In Persian)
- Nawar, S., H. Buddenbaum & J. Hill, 2015. Estimation of soil salinity using three quantitative methods based on visible and near-infrared reflectance spectroscopy: a case study from Egypt, Arabian Journal of Geosciences, 8(1): 5127-5140.
- Nelson, J. & D. J. Miller, 1992. Expansive Soils Problems and Practice in Foundation and Pavement Engineering, John Wiley & Sons press.
- Pearring, J. R., 1963. A study of basic mineralogical, physical–chemical, and engineering index properties of laterite soils. PhD thesis. Texas A&M University Texas. College Station. TX, USA, 186 p.
- Rossel, R. V. & A. B. McBratney, 2008. Diffuse reflectance spectroscopy as a tool for digital soil mapping, Digital Soil Mapping with Limited, 165-172.
- Summers, D., M. Lewis, B. Ostendorf & D. Chittleborough, 2011. Visible near-infrared reflectance spectroscopy as a predictive indicator of soil properties, Ecological Indicators, 11(1): 123-131.
- Salehi, A., M. Zainkafsh, G. Zahedi Amiri & R. Marvi Mohajer, 2005. A study of soil physical and chemical properties in relation to tree ecological groups in Nam-Khaneh district of Kheirood-Kenar forest, Iranian Journal of Natural Resource, 58(3): 567-578 (In Persian).
- Stenberg, B. & R. V. Rossel, 2010. Diffuse reflectance spectroscopy for high-resolution soil sensing, Proximal Soil Sensing, 29-47.
- Stenberg. B., R. A. Viscarra Rossel, A. M. Mouazen & J. Wetterlind, 2010. Visible and Near Infrared Spectroscopy in Soil Science, Advances in Agronomy, 107: 163-215.
- Savitzky, A. & M. J. E. Golay, 1964. Smoothing and Differentiation of Data by Simplified Least Square Procedure, Analytical Chemistry, Analytical chemistry, 36(8): 1627-1638.
- Tian, Y., J. Zhang, X. Yao, W. Cao & Y. Zhu, 2013. Laboratory assessment of three quantitative methods for estimating the organic matter content of soils in China based on visible/near-infrared reflectance spectra, Geoderma, 202:161-170.
- Tucker, C. J., 1979. Red and Photographic Infrared Linear Combinations for Monitoring Vegetation, Remote Sensing of Environment, 8(2): 127-150.
- Williams, P. C., 2001. Near-infrared technology in the agricultural and food industries. American Association of Cereal Chemists, Inc., St. Paul, Minnesota, USA, 330 p.
- Waruru, B., K. D. Shepherd, G. M. Ndegwa, P. T. Kamoni & A. M. Sila, 2014. Rapid estimation of soil engineering properties using diffuse reflectance near infrared spectroscopy, biosystems engineering, 121(1): 177-185.
- Walvoort, D. & A. B. McBratney, 2001. Diffuse reflectance spectrometry as a proximal sensing tool for precision agriculture. Proceedings of Third European Conference on Precision Agriculture. pp. 503-507.
- Waiser, T. H., C. L. S. Morgan, D. J. Brown & C. T. Hallmark, 2007. In situ characterization of soil clay content with visible near-infrared diffuse reflectance spectroscopy, Soil Science Society of America Journal, 71(1): 389-396.
- Wold, S., M. Sjöström & L. Eriksson, 2001. PLS-regression: a basic tool of chemometrics. Chemometrics and intelligent laboratory systems, 58(2): 109-130.
- Xie, H. T., X. M. Yang, C. F. Drury, J. Y. Yang & X. D. Zhang, 2011. Predicting soil organic carbon and total nitrogen using mid- and near-infrared spectra for Brookston clay loam soil in Southwestern Ontario, Canada, Canadian Journal of Soil Science, 91(1): 53-63.
- Yao, X., Y. Huang, G. Shang, C. Zhou, T. Cheng, Y. Tian, W. Cao & Y. Zhu. 2015. Evaluation of six algorithms to monitor wheat leaf nitrogen concentration, Remote Sensing, 7(11): 14939-14966.
- Yitagesu, F. A., F. Van der Meer, H. van der Werff & W. Zigterman, 2009. Quantifying engineering parameters of expansive soils from their reflectance spectra, Engineering Geology, 105(3-4): 151-160.
- Yu, X., Q. Liu, Y. Wang, X. Liu & X. Liu, 2016. Evaluation of MLSR and PLSR for estimating soil element contents using visible/near-infrared spectroscopy in apple orchards on the Jiaodong peninsula, Catena, 137(3): 340-349.
Forest Research and Development
Volume 4, Issue 3
December 2018
Pages 347-361

Files

Share

How to cite

Statistics