Soil signature simulation of complex mixtures and particle size distributions

Tyler Carson; Charles M. Bachmann; Carl Salvaggio

doi:10.1117/1.OE.54.9.094103

10 September 2015 Soil signature simulation of complex mixtures and particle size distributions

Tyler Carson, Charles M. Bachmann, Carl Salvaggio

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Optical Engineering, Vol. 54, Issue 9, 094103 (September 2015). https://doi.org/10.1117/1.OE.54.9.094103

Abstract

Soil reflectance signatures were modeled using the digital imaging and remote sensing image generation model and Blender three-dimensional (3-D) graphic design software. Using these tools, the geometry, radiometry, and chemistry of quartz and magnetite were exploited to model the presence of particle size and porosity effects in the visible and the shortwave infrared spectrum. Using the physics engines within the Blender 3-D graphic design software, physical representations of granular soil scenes were created. Each scene characterized a specific particle distribution and density. Chemical and optical properties of pure quartz and magnetite were assigned to particles in the scene based on particle size. This work presents a model to describe an observed phase-angle dependence of beach sand density. Bidirectional reflectance signatures were simulated for targets of varying size distribution and density. This model provides validation for a phenomenological trade space between density and particle size distribution in complex, heterogeneous soil mixtures. It also confirms the suggestion that directional reflectance signatures can be defined by intimate mixtures that depend on pore spacing. The study demonstrated that by combining realistic target geometry and spectral measurements of pure quartz and magnetite, effects of soil particle size and density could be modeled without functional data fitting or rigorous analysis of material dynamics. This research does not use traditional function-based models for simulation. The combination of realistic geometry, physically viable particle structure, and first-principles ray-tracing enables the ability to represent signature changes that have been observed in experimental observations.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Tyler Carson, Charles M. Bachmann, and Carl Salvaggio "Soil signature simulation of complex mixtures and particle size distributions," Optical Engineering 54(9), 094103 (10 September 2015). https://doi.org/10.1117/1.OE.54.9.094103

Published: 10 September 2015

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