Rapid determination of soil unconfined compressive strength using reflectance spectroscopy

Abstract

Understanding the physical and especially mechanical properties of forest soils is very important in forest engineering operations including road construction and exploitation. Unconfined compressive strength (UCS) is one of the most important mechanical properties for evaluating the strength of adhesive soils in many engineering projects including forest roads. Measuring the USC of soil in the laboratory and in situ is difficult, time-consuming, and costly, so it is essential to explore a rapid, low-cost, and non-destructive method. The aim of this study was to estimate the UCS of forest roads using spectroscopy. The applied support vector machine (SVM) method determined the soil moisture classes (i.e., 14%, 25%, 31%, and 36%) with R2 of 0.98. Two methods of partial least squares regression (PLSR) and the normal difference index (NDI) were used to estimate the UCS at different moisture classes. The results showed that the NDI performed better than the PLSR to estimate the USC at four different moisture classes of 14% (R2 = 0.8, RMSE = 19.36, RPD = 2.61), 25% (R2 = 0.78, RMSE = 16.06, RPD = 1.64), 31% (R2 = 0.82, RMSE = 11.2, RPD = 2.28), and 36% (R2 = 0.83, RMSE = 7.49, RPD = 2.41). Also, a sampling interval method was applied to reduce spectral dimensionality and processing time. The sampling interval of 16 nm was selected using a genetic algorithm. Finally, the UCS was estimated at maximum soil moisture using the simple regression model (SRM) based on the results of NDI. Based on this current study, it has been found that using spectroscopy to estimate the UCS of soil could be considered an alternative method for developmental operations in identifying the UCS of soil due to the costly and time-consuming conventional laboratory methods.