Unifying radiative transfer models in computer graphics and remote sensing, Part I: A survey

1Dartmouth College 2NASA Goddard Space Flight Center (GSFC) 3Columbia University 4University of Maryland Baltimore County

In Journal of Quantitative Spectroscopy and Radiative Transfer, 2024

Teaser
A forward model maps state space, the space of all possible geophysical parameters and geometry, to measurement space, the space of all possible measurements of radiance, mimicking the functionality of a real-world sensor. An inverse model maps measurement space to state space, producing useful data for further analysis by the scientific community. Image taken by MODIS-Aqua of the South Pacific near Tonga (2006).
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Abstract

The constellation of Earth-observing satellites continuously collects measurements of scattered radiance, which must be transformed into geophysical parameters in order to answer fundamental scientific questions about the Earth. Retrieval of these parameters requires highly flexible, accurate, and fast forward and inverse radiative transfer models. Existing forward models used by the remote sensing community are typically accurate and fast, but sacrifice flexibility by assuming the atmosphere or ocean is composed of plane-parallel layers. Monte Carlo forward models can handle more complex scenarios such as 3D spatial heterogeneity, but are relatively slower. We propose looking to the computer graphics community for inspiration to improve the statistical efficiency of Monte Carlo forward models and explore new approaches to inverse models for remote sensing. In Part 1 of this work, we examine the evolution of radiative transfer models in computer graphics and highlight recent advancements that have the potential to push forward models in remote sensing beyond their current periphery of realism.

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Acknowledgements

The authors thank Wenzel Jakob and the rest of the Mitsuba 3 development team for consultations on Mitsuba 3. We also thank Meng Gao for insightful discussions on radiative transfer codes. Funding: This work was supported by the National Aeronautics and Space Administration (NASA) [grant number 80NSSC22K1154]; the National Science Foundation (NSF) [grant number 1844538]; and a Neukom Institute CompX faculty grant.

Cite

Katherine Salesin, Kirk D. Knobelspiesse, Jacek Chowdhary, Peng-Wang Zhai, Wojciech Jarosz. Unifying radiative transfer models in computer graphics and remote sensing, Part I: A survey. Journal of Quantitative Spectroscopy and Radiative Transfer, 314, February 2024. 
@article{salesin24unifying1,
    author  = {Salesin, Katherine and Knobelspiesse, Kirk D. and Chowdhary, Jacek and Zhai, Peng-Wang and Jarosz,
               Wojciech},
    title   = {Unifying radiative transfer models in computer graphics and remote sensing, {Part I: A} survey},
    journal = {Journal of Quantitative Spectroscopy and Radiative Transfer},
    year    = {2024},
    month   = feb,
    doi     = {10/mbhx},
    volume  = {314},
    issn    = {0022-4073}
}