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Computational modeling of spectral and hyperspectral imagery can be performed using radiative flux calculations on highly resolved geometric models. Faceted geometry models are both memory intensive and computationally expensive but allow for a fine-grained approach to radiative modeling. Using high resolution faceted geometry, improved synthetic imagery can be generated from a ray casting sensor model. This paper describes the results of a distributed memory ray tracing architecture for processing high facet count geometry that is capable of modeling radiative flux for highly resolved landscapes. Monte Carlo integration of the radiative transfer equation is coupled with a soil heat transfer model to facilitate solving for temperatures. Ray tracing procedures then use material properties to communicate radiative flux back to a sensor model. Emitted radiation along with mid-wave radiation reflected from neighboring facets and reflected short-wave solar radiation is computed and returned for rays cast from a sensor model. Radiative results of a prototype rainforest have been acquired that demonstrate the modeling capability of the architecture for geometries exceeding 40 million facets. Images of individual spectral components visually validate the legitimacy of the flux simulation. This paper presents an architecture that has been developed with the potential to produce quality synthetic spectral data based on modeling of actual temperature and radiative flux.
Robert H. Hunter,Barry C. White,Reena R. Patel, andJerrell R. Ballard
"Modeling the radiative response of a high facet count rainforest for synthetic sensor imagery", Proc. SPIE 11727, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVII, 117270K (12 April 2021); https://doi.org/10.1117/12.2585983
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Robert H. Hunter, Barry C. White, Reena R. Patel, Jerrell R. Ballard, "Modeling the radiative response of a high facet count rainforest for synthetic sensor imagery," Proc. SPIE 11727, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVII, 117270K (12 April 2021); https://doi.org/10.1117/12.2585983