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

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 f...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Journal of quantitative spectroscopy & radiative transfer Ročník 314; s. 108847
Hlavní autoři: Salesin, Katherine, Knobelspiesse, Kirk D, Chowdhary, Jacek, Zhai, Peng-Wang, Jarosz, Wojciech
Médium: Journal Article
Jazyk:angličtina
Vydáno: Goddard Space Flight Center Elsevier 01.02.2024
Témata:
Computer Programming and Software
Earth Resources and Remote Sensing
Radiative Transfer
Atmospheric And Ocean Optics
Computer Graphics
Polarization
Remote Sensing
Monte Carlo
ISSN:0022-4073, 1879-1352
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí: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.
Bibliografie:GSFC
Goddard Space Flight Center
ISSN:0022-4073
1879-1352
DOI:10.1016/j.jqsrt.2023.108847