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Title: Wavelet Analysis of Soil Reflectance for the Characterization of Soil Properties

Author
item BILGILI, A - CORNELL UNIVERSITY
item Hively, Wells - Dean
item VAN ES, H - CORNELL UNIVERSITY
item Reeves Iii, James
item GASTON, LEWIS - LOUISIANA STATE UNIV

Submitted to: Meeting Abstract
Publication Type: Proceedings
Publication Acceptance Date: 7/10/2008
Publication Date: 7/17/2008
Citation: Bilgili, A.V., Hively, W.D., Van Es, H., Reeves, J.B., Gaston, L. 2008. Wavelet analysis of soil reflectance for characterization of soil properties. In: Proceedings of the Southern Regional Cooperative Soil Survey Conferences, July 14-17, 2008, Gainesville, Florida. 2008 CDROM.

Interpretive Summary:

Technical Abstract: Wavelet analysis has proven to be effective in many fields including signal processing and digital image analysis. Recently, it has been adapted to spectroscopy, where the reflectance of various materials is measured with respect to wavelength (nm) or wave number (cm-1). Spectra can cover broad wavelength ranges within which wavelength-specific reflectance values can be highly autocorrelated, making the use of traditional statistical procedures impractical for correlating the spectral information with the variable of interest. The spectra also need to processed prior to correlation to remove noise which may originate because of instrument or atmospheric conditions. Wavelet analysis can provide a good technique to address the aforementioned problems, by reducing the number of necessary wavelengths to the most significant minimum, removing multi-collinearity among the spectral wavelengths, and filtering noise. This project applied wavelet analysis to hyperspectral visible/near-mid infrared reflectance spectra of soil materials, and evaluated its combined use with simple Multiple Linear Regression Analysis (MLR). Wavelet analyses successfully reduced the number of wavelengths (predictors) used in the correlation of reflectance spectra with soil properties, and helped with the spectral characterization of certain soil analytes by incorporating different wavelet bases at different scales.