Comparative Analysis of Wavelet Transformation Techniques in Enhancing Soil Organic Carbon Detection Through Hyperspectral Imaging

Advancements in hyperspectral imaging technology open new avenues for Soil Organic Carbon (SOC) estimation, a critical factor in enhancing agricultural productivity and understanding carbon sequestration. This study analyzed 96 soil samples using the HySpex sensor system, covering visible and near-infrared (VNIR; 400-1000 nm over 700 spectral bands) and short-wave infrared (SWIR; 960-2500 nm over 362 spectral bands) spectrums. We integrated Discrete and Continuous Wavelet Transforms (DWT and CWT), applying Biorthogonal, Daubechies, Complex Morlet, Morlet, and Mexican hat wavelets for enhanced SOC detection. Our results indicate a marked improvement in SOC estimation, particularly with Complex Morlet and Mexican hat wavelets in CWT. Complementary chemical analysis validated the SOC levels. Depth-wise, the 15-30 cm range in the SWIR region showed the highest SOC correlation. We identified key spectral ranges, including 400-580 nm and 680-910 nm in VNIR, and 1150-2500 nm in SWIR, as strongly correlated with SOC, substantiated by lab analysis.