Please note: The master’s thesis presentation will be given online.
Mark Iwanchyshyn, Master’s candidate
David R. Cheriton School of Computer Science
Sand-textured soils are found in a wide range of landscapes, from dune fields to coastal areas. The quantification of light penetration through these soils, particularly considering possible variations in the presence of water in their pore space, is of considerable interest not only for remote sensing applications, but also for agricultural, ecological and geophysical studies. Despite its relevance, however, the literature on this topic is still scarce. Moreover, the available light penetration (transmittance) datasets for these soils are affected by experimental and modeling limitations. These include, for instance, the use of samples with morphological and mineralogical characteristics markedly different from those of naturally occurring sand-textured soils.
In the investigation described in this thesis, we demonstrate the importance of properly accounting for the iron oxide contents and grain (particle) distributions of these soils in applied research initiatives linked to their spectral responses, notably in the 400 to 1000 nm region of the light spectrum. In order to overcome the limitations outlined above and strengthen the current knowledge in this area, we employed a predictive simulation platform supported by measured data. This platform has as its central component a first-principles light transport model for particulate materials whose implementation has been substantially enhanced during this work. Thus, using this platform, we were able to perform controlled in silico experiments on selected representative samples of these soils by systematically varying their water content, their thickness and the angle of light incidence. Our findings provide an original multi-faceted assessment, both in terms of spectral and angular dependencies, of the light transmission profiles of dry and wet sand-textured soils.
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