Assessing Organic Carbon of Grassland Soil in the Northern Tianshan Mountains of Xinjiang, China Using the Wavelet Decomposition of Hyperspectral Data

Abstract

Soil organic carbon (SOC) represents a significant fraction of the total amount of carbon involved in the global carbon cycle. Hyper spectral remote sensing has a valuable role in the monitoring of the dynamics of SOC. This study focused upon improving the accuracy of SOC quantification by applying wavelet analysis to reflectance spectra. Spectral measurements for all soil samples (three sub-regions in the northern Tianshan Mountains, China) were performed in a controlled laboratory environment. The results demonstrated that by decomposing soil spectra, the resultant wavelet coefficients can be used to generate higher R2 with SOC contents (R2 >0.95) compared to reflectance spectra (R2

Cite this paper

@article{Chen2011AssessingOC, title={Assessing Organic Carbon of Grassland Soil in the Northern Tianshan Mountains of Xinjiang, China Using the Wavelet Decomposition of Hyperspectral Data}, author={Yizhao Chen and Feng Yang and Jianlong Li and Cherry Li}, journal={2011 Fourth International Conference on Intelligent Computation Technology and Automation}, year={2011}, volume={2}, pages={35-38} }