Estimation of Soil Organic Matter Content Based on Regional Feature Bands

摘要

To estimate soil organic matter (SOM) content using hyper-spectral data, regional feature bands and principle component regression (PCR) were built a model of SOM. The results showed that the coefficients of determination (R~2) of PCR model based on the regional feature bands were 0.650 for calibration set and 0.628 for validation set, respectively. The Root Mean Square Error (RMSE) values were 2.641 g/kg and 2.852 g/kg, respectively. The PCR models based on the significant bands had better estimation accuracy, but its total correlation coefficient(R = 0.770) between predicted SOM and measured SOM was lower than of model based on the regional feature bands (R = 0.803). Therefore, the PCR model based on regional feature bands provides a better estimation result than model based on significant bands.