Using on‐nadir spectral reflectance to detect soil surface changes induced by simulated rainfall and wind tunnel abrasion

Abstract

The surface susceptibility to erosion (erodibility) is an important component of soil erosion models. Many studies of wind erosion have shown that even relatively small changes in surface conditions can have a considerable effect on the temporal and spatial variability of dust emissions. One of the main difficulties in measuring erodibility is that it is controlled by a number of highly variable soil factors. Collection of these data is often limited in scale because in situ measurements are labour-intensive and very time-consuming. To improve wind erosion model predictions over several spatial and temporal scales simultaneously, there is a requirement for a non-invasive approach that can be used to rapidly assess changes in the compositional and structural nature of a soil surface in time and space. Spectral reflectance of the soil surface appears to meet these desirable requirements and it is controlled by properties that affect the soil erodibility.Three soil surfaces were modified using rainfall simulation and wind tunnel abrasion experiments. Observations of those changes were made and recorded using digital images and on-nadir spectral reflectance. The results showed clear evidence of the information content in the spectral domain that was otherwise difficult to interpret given the complicated interrelationships between soil composition and structure. Changes detected at the soil surface included the presence of a crust produced by rainsplash, the production of loose erodible material covering a rain crust and the selective erosion of the soil surface. The effect of rainsplash and aeolian abrasion was different for each soil tested and crust abrasion was shown to decrease as rainfall intensity increased. The relative contributions of the eroded material from each soil surface to trapped mixtures of material assisted the erodibility assessment. Ordination analyses within each of two important soil types explained significant amounts of the variation in the reflectance of all wavebands by treatments of the soil and hence changes in the soil surface. The results show that soil surface conditions within a soil type are an underestimated source of variation in the characterization of soil surface erodibility and in the remote sensing of soil.

Spatial and temporal distribution of cyanobacterial soil crusts in the Kalahari: Implications for soil surface properties

“…Shao et al (1996) suggest one of the main limitations of contemporary wind erosion models is their inability to incorporate the evolution of surface soil conditions during wind erosion events. There is, therefore, a need to improve the information available on soil surface conditions, such as cohesive strength and roughness that affect erodibility to enable wind erosion models to be improved to incorporate the evolution of soil surface conditions (Sokolik and Toon, 1996;Shao and Leslie, 1997;Chappell et al, 2005). Similarly, improved assessments of erosivity of wind regimes and in particular how this is affected by spatial variations in the nature of vegetation cover at a landscape scale and soil surface roughness on a local scale remains an area of active research (Wiggs, 1997).…”

Assessment of Soil Degradation by Erosion Based on Analysis of Soil Properties Using Aerial Hyperspectral Images and Ancillary Data, Czech Republic

“…These methods are based on classification techniques or use different mathematical and statistical procedures to assess the correlation between erosion signs and their spectral reflectance [15,26,27]. Soil erosion and accumulation affect chemical and physical properties of upper layer of soils; thus, spectral reflectance is changed and eroded soils have different spectral response from non-eroded "healthy" soils [28][29][30][31][32][33][34].…”

An assessment of the bidirectional reflectance models basing on laboratory experiment of natural particulate surfaces

“…For particulate surfaces, such as soil or sand, spectral reflectance is somewhat sensitive as an indicator of the surface physical characteristics, e.g. grain size [2] and texture [3].…”