Spectral Characteristics of Cr and Cu in Agricultural Soil at Beijing Plain Based on SWIR Spectroscopy and PLSR

Abstract:

Heavy metals pollution in agricultural soils has been an important problem to human health, mapping large-scale spatial distribution of soil heavy metals is urgently needed. Instead of traditional methods, time-consuming and destructive, soil properties predicted by remote sensing technology shows a lot of advantages, which makes large area of real-time dynamic monitoring as possible. However, before achieving prediction using spectra data, the first thing to do is that finding the spectral characteristics of soil heavy metals. In this paper, taking Cr and Cu for example, the correlations between soil heavy metals content and laboratory-measured reflectance is studied using partial least squares regression (PLSR), which is an adaptive method to examine linear between spectrum and concentration. First of all, using the raw spectra, remove outliers of heavy metals concentration by PLSR modeling. Next, though comparing RMSEC and RMSEV against PLSR components, and cumulative explanatory of spectral components to metal content using different pre-precessing methods, find the right pre-pcocessing is CR and optimum number of components to Cr and Cu are 3 and 2 respectively. Simultaneously, with the meaning of PLSR models regression coefficients, we analysis the spectral characteristics of Cr and Cu, although can not to realize the prediction only take use of these spectra, which is still essential to achieve simulating spatial distribution of soil heavy metal by remote sensing.

• Periodical: Advanced Materials Research (Volumes 765-767)
• Pages: 3066-3072
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.765-767.3066
• Online since: September 2013
• Authors: Shu Min Li, Hong Li, Dan Feng Sun, Lian Di Zhou
• Keywords: Agricultural Soil, Partial Least Square Regression (PLSR), Spectral Characteristics, SWIR

References

[1] KooistraL, WehrensR, Leuven RS EW, et al. Analytica Chimica Acta, 2001, 446: 97~105.

[2] Kooistra L, Leuven R S EW, WehrensR, et al. International Journal of Remote Sensing, 2003, 24(24): 4995~5010.

[3] Kemper T, Sommer S. [J]. Environmental Science and Technology, 2002, 36(12): 2742~2 748.

[4] Grzegorz S, Gregory W M, Tomasz I S, et al. Journal of Environment Quality, 2004, 33: 2056~(2069).

[5] Li Jubao, Tian Qingjiu, Wu Yunzhao. Remote Sensing Information 2005, (3): 10-13.

[6] Wu Yunzhao, Chen Jun, Wu Xinmin, et al. Applied Geochemistry, 2005, 20: 1051~1059.

[7] Wu Yunzhao, Chen Jun, Ji Junfeng, et al. Environmental Science & Technology, 2005, 39(3): 873~878.

[8] Xie Xianli, Sun Bo, Hao Hongtao. Acta Pedologica Sinica 2007, 44(6): 982-993.

[9] Dunn, B.W., Beecher, H.G., Batten, G. D., Ciavarella, S. Australian Journal of Experimental Agriculture. 2002, 42(5): 607-614.

[10] Morgan, C.L.S., Waiser, TH.H., Brown, D.J., Hallmark, C.T. Geoderma. 2009, 151(3-4): 245-256.

[11] Escribano, P., Palacios-Orueta, A., Oyonarte, C., Chabrillat, S. Journal of Arid Environment 2010, 74(9): 1041-1051.

DOI: 10.1016/j.jaridenv.2010.02.001

[12] Fontan, J.M., Calvache, S., Lopez-Bellido, R.J., Lopez-Bellido, L. Geoderma. 2010, 156(3-4): 93-98.

[13] Wang Huiwen, Methodology and Application of Partial Least Squares Regression[M], Beijing: National Defence Industry Press, (1999).

[14] M. Kuester, K. Thome, K. Krause, K. Canham, E. Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International.

[15] Francesca Garfagnoli, Luca Innocenti, Silvia Vettori, Sandro Moretti and Leandro Chiarantini. Hyperspectral 2010 Workshop, Frascati, Italy, 17-19 March 2010 (ESA SP-683, May 2010).

[16] Savitzky A., and Golay, M.J.E. Analytical Chemistry 1964, 36 (8): 1627-1639.

[17] Ali Volkan Bilgili, M. Ali Cullu, Harold van Es, Aydin Aydemir and Salih Aydemir. Arid Land Research and Management. 2011, (25): 19-37.

DOI: 10.1080/15324982.2010.528153

[18] Clark, R. N. and T. Roush. Journal of Geophysical Research. 1984, (89): 6329-6340.

[19] Viscarra Rossel, R.A., Walvoort, D.J.J., McBratney, A.B., Janik, L.J. and Skjemstad, J. O. Geoderma. 2006, 131: 59-75.

DOI: 10.1016/j.geoderma.2005.03.007

[20] Wold, S. Technometrics. 1978, (20): 397-406.

[21] Huang Changping, Liu Bo, Zhang Xia, Tong Qingxi. Remote Sensing Technology and Application. 2010, 25(3): 353-357, 341.

[22] Li Minzan, Spectral analysis technology and application [M], Beijing: Science Press, (2006).

[23] CAMO Inc, The Unscrambler user manual, CAMO Inc., 2004, Corvallis, OR.

[24] Qin Jing, Kong Xiangbin, Jiang Guanghui, Liu Yi, Li Cuizhen. Transactions of the CSAE 24. 2008 (3): 124-129.