辐射传输：从唯象到第一性原理

吴自华; 秦其明

doi:10.11834/jrs.20222062

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辐射传输：从唯象到第一性原理
Radiative transfer： From phenomenology to first principles
2023年27卷第7期页码：1628-1641
收稿：2022-02-17，

纸质出版：2023-07-07
DOI： 10.11834/jrs.20222062
稿件说明：

移动端阅览

吴自华，秦其明.2023.辐射传输：从唯象到第一性原理.遥感学报，27（7）： 1628-1641 DOI： 10.11834/jrs.20222062.

Wu Z H and Qin Q M. 2023. Radiative transfer： From phenomenology to first principles. National Remote Sensing Bulletin， 27（7）：1628-1641 DOI： 10.11834/jrs.20222062.

摘要

在回顾经典辐射传输理论的发展历程的基础上，本文对辐射传输理论与经典电磁理论的联系方面的研究工作进行了系统综述：从19世纪80年代提出至今，辐射传输理论已经过了一百多年的发展，并在诸多领域，尤其是定量遥感中得到了广泛的应用。经典辐射传输理论是一种唯象的近似理论，虽然描述的是电磁辐射的传播过程，但却长期被视为与经典电磁学相独立的一座“孤岛”。为了建立起辐射传输理论和经典电磁学间的联系，从20世纪60年代开始，众多研究者从第一性原理（也即Maxwell方程组）出发，从理论推导、数值模拟和受控实验3个角度展开了一系列研究，据此进一步明确了辐射传输理论的适用范围和条件，并针对相干后向散射和密集介质等情形提出了一些改进的辐射传输方法。展望未来，这一探索仍将继续，并将促进辐射传输理论与电磁理论的进一步结合，从而更好地服务于定量遥感的应用需求。

Abstract

Radiative Transfer Theory (RTT) is one of the essential foundations in astrophysics

engineering thermophysics

computer graphics

biomedical imaging

and remote sensing. RTT is particularly widely used in the field of quantitative remote sensing. However

classical RTT is a phenomenological theory based on heuristic summarizations of experiments instead of being directly derived from the first principles. Given the ignorance of the wave property

RTT cannot explain interference and diffraction phenomena

e.g.

the well-known coherent backscattering.

The root of RTT dates back to the photometry study by Bouguer

Lambert

and Beer. Von Lommel and Chwolson are believed to propose the integral form of the Radiative Transfer Equation (RTE) for the first time in the 1880s. Afterward

many other scientists

including Schuster

Schwarzschild

Eddington

Milne

Gans

Sobolev

Chandrasekhar

Rozenberg

and Tsang

contributed to the establishment of RTT as a strict theory. However

classical RTT implicitly depends on the assumption of independent scattering

which fails when applied to dense matter. It requires the first-principle approach to bridge the gap between classical RTT and classical electromagnetics and extend the application of RTT. Three ways can be applied: (1) direct derivation

(2) numerical simulations

and (3) controlled experiments.Direct derivation of the RTE from first principles (i.e.

Maxwell equations) is the most fundamental approach. Mishchenko and his colleagues’ derivation is currently considered the most rigorous. This derivation is primarily based on previous research on multiple scattering of electromagnetic waves

to which Foldy

Lax

Twersky

and many others have made significant contributions. Mishchenko et al. managed to derive the RTE from Maxwell equations for both coherent and incoherent intensities under the condition of plane wave and discrete random media. The derivation proves that RTT is not a disconnected “island” from the “mainland” of classical electromagnetics.

Besides derivations

numerical simulations and controlled experiments help reveal the connection between RTT and numerically exacted computational electromagnetics. In these simulations and experiments

the RTT and electromagnetic computation results are compared under different conditions. Results show that RTT can yield satisfactory results when the volume percentage of scatterers is low. Some corrections

e.g.

the Percus-Yevick model

can be introduced to compensate for the errors of RTT when the density of scatterers further increases. Based on these studies

some efforts have been made to extend RTT to the case of dense matter. Notable achievements include the DMRT and the R

theories.

Although these studies are still limited to some ideal situations

they have provided some guidance for the mechanistic revision of RTT

thereby expanding the scope of its application. On the contrary

the combination of radiative transfer methods with computational electromagnetics becomes a research direction of interest

along with the development of computer performance and the improvement of relevant algorithms. At present

different methods are used in quantitative remote sensing for different wavebands and different research objects: for example

optical remote sensing and microwave remote sensing for vegetation or vegetation remote sensing and atmospheric remote sensing. Although the names of the methods used are “radiative transfer

” they are based on different assumptions and approximations. The combination of RTT and computational electromagnetics is a promising approach to unifying the remote sensing modeling and inversion studies of different wavelengths and objects.

关键词

Keywords

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