Using bi-directional soil spectral reflectance to model soil surface changes induced by rainfall and wind-tunnel abrasion

Abstract

To improve wind erosion model calculations across several spatial and temporal scales simultaneously, there is a requirement for a non-invasive approach that can be used rapidly to assess changes in the compositional and structural nature of a soil surface in time and space. Remote sensing allows consideration of the processes controlling erodibility on the same spatial continuum to avoid time-consuming and expensive fieldwork. Multi-angular spectral reflectance appears to provide a holistic framework for the measurement and calculation of soil surface characteristics remotely using ground-based radiometers and current and future generations of angular sensors on airborne and satellite platforms. To investigate the utility of this framework, a ground-based study was performed using three soils susceptible to wind erosion that were modified using rainfall simulation and wind tunnel abrasion experiments. Measurements of those changes were made and recorded using digital images. Multi-angular spectral measurements of reflectance were also made and inverted against a bi-directional soil spectral reflectance model. Comparison of the measurements and calculations showed good agreement with small errors in accuracy. Optimised values of the model parameters produced the single scattering albedo and a description of the reflectance scattering behaviour of the soil surfaces that included an estimate of roughness. The model parameters removed the effect of illumination and viewing geometry on the spectral reflectance. The combination of single-scattering albedo spectra and model parameters for each treatment provided information about the composition and structure of the soil surface changes. The main changes detected at the soil surface included the presence of a crust produced by rain-splash, the production of loose erodible material covering a rain crust and the selective erosion of the soil surface. Redundancy analysis showed that much of the variation in the values of the soil reflectance model parameters was explained by the scattering properties and the roughness parameter of the soil surfaces. Variation in the soil surface reflectance was not explained solely by soil type. Instead, low intensity rainfall combined with short and long duration abrasion explained a significant portion. These findings provide a source of considerable variation in experimental and operational spectral reflectance measurements that has perhaps hitherto been largely ignored. The results demonstrated the readily available information on the composition and structure of the soil surface without interfering with natural processes. The directional soil reflectance methodology appears to have potential for use in improving the understanding of erodibility and ultimately for identifying and quantifying soil erosion.