A reverse ray-tracing method for modelling the net radiative flux in leaf-resolving plant canopy simulations

Brian N. Bailey

Ecological Modelling, 2018, vol. 368, issue C, 233-245

Abstract: Radiation is a direct or indirect driver of essentially all biophysical processes in plant systems, and is commonly described through the use of models because of its complex distributions in time and space. Detailed radiation transfer models that represent plant-scale heterogeneity have high computational resource requirements, thus severely limiting the size of problems that can be feasibly considered, while simplified models that can represent entire canopies usually neglect heterogeneity across a wide range of scales. This work develops new methods for computing radiation absorption, transmission, scattering, and emission using ray-tracing approaches that can explicitly represent scales ranging from leaves to canopies. This work focuses on developing a new “reverse” ray-tracing method for describing radiation emission and scattering that ensures all geometric elements (e.g., leaves, branches) are adequately sampled, which guarantees that modelled radiative fluxes are bounded within a reasonable range of values regardless of the number of rays used. This is a critical property when complex model geometries are used, which can be subject to severe sampling errors even when very large ray counts are used. The presented model uses graphics processing units (GPUs) along with highly optimized software to efficiently perform ray-object intersection tests in parallel. This allowed for the simulation of >500 fully resolved trees on a desktop computer in under five minutes.

Keywords: Functional-structural plant model; Graphics processing units; Radiation model; Ray-tracing (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:368:y:2018:i:c:p:233-245

DOI: 10.1016/j.ecolmodel.2017.11.022

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