A general framework of kernel-driven modeling in the thermal infrared domain

Biao Cao,Jean-Louis Roujean,Jean-Philippe Gastellu-Etchegorry,Qinhuo Liu,Yongming Du,Jean-Pierre Lagouarde,Huaguo Huang,Hua Li,Zunjian Bian,Tian Hu,Boxiong Qin,Xueting Ran,Qing Xiao

doi:10.1016/j.rse.2020.112157

Abstract

Radiometric measurements in the Thermal Infrared (TIR) domain exhibit an angular variation over most surface types, known as the Thermal Radiation Directionality (TRD) phenomenon. A primary objective of the ongoing development of TRD physical models is to perform a correction of the angular effects to obtain comparable land surface temperature products. In practice, it is advised to handle only the models having a limited number of input parameters for the purpose of operational applications. The use of semi-empirical kernel-driven models (KDMs) appears to be a good tradeoff between physical accuracy and computational efficiency as it was already demonstrated through a broad usage in the optical domain. It remains that the existing state-of-the-art 3-parameter TIR KDMs (RossThick-LiSparseR, LiStrahlerFriedl-LiDenseR, Vinnikov, and RoujeanLagouarde) underestimate the hotspot phenomenon, especially for continuous canopies marked by a narrow peak. In this study, a new general framework of TIR kernel-driven modeling is proposed to overcome such issue. It is a linear combination of three kernels (including a base shape kernel, a hotspot kernel with adjustable width and an isotropic kernel) with the ability to simulate the bowl, dome and bell shapes in the solar principal plane. Four specific 4-parameter models (Vinnikov-RoujeanLagouarde, LiStrahlerFriedl-RoujeanLagouarde, Vinnikov-Chen, and LiStrahlerFriedl-Chen, named “base shape kernel - hotspot kernel”) within the new framework were studied to assess their abilities to mimic the patterns of the directional brightness temperature for both continuous and discrete vegetation canopies. These four 4-parameter KDMs and four 3-parameter KDMs were comprehensively evaluated with 306 groups of simulated multi-angle datasets generated by a modernized analytical 4-stream radiative transfer model based on the Scattering by Arbitrarily Inclined Leaves (4SAIL), and a Discrete Anisotropic Radiative Transfer (DART) model considering different solar zenith angles (SZA), canopy architectures and component temperatures, and 2 groups of airborne measured multi-angle datasets over continuous maize and discrete pine forest. Results show that the four 4-parameter KDMs behave better than the four existing 3-parameter KDMs over continuous canopies (e.g. R2 increases from 0.661~0.970 to 0.940~0.997 and RMSE decreases from 0.17~0.71 to 0.07~0.16 when SZA = 30°) and discrete canopies (e.g. R2 increases from 0.791~0.989 to 0.976~0.996 and RMSE decreases from 0.10~0.84 to 0.08~0.21 when SZA = 30°). The new general framework with four parameters (three kernel coefficients and an adjustable hotspot width) improves the fitting ability significantly, compared to the four existing three-parameter KDMs, given the addition of one more degree of freedom. Results show that the coefficients of the base shape kernel, hotspot kernel and isotropic kernel are related to the temperature difference between leaf and background, temperature difference between sunlit component and shaded component, and the nadir brightness temperature, respectively. However, the estimated hotspot width depends on vegetation structure. The new kernel-driven modeling framework has the potential to be a tool for angular correction of multi-angle satellite observations and angular optimization of future multi-angle TIR sensors.

Highlights

Land surface temperature (LST) is an Essential Climate Variable (ECV) for regional and global applications of surface energy budget and water balance (Anderson et al, 2008; Hu et al, 2020)
The thermal radiation direc tionality (TRD) effect has been a major concern in the field of thermal infrared (TIR) remote sensing since 1962 (Monteith and Szeicz, 1962) because it can lead to a 10 K difference of directional brightness tem perature (DBT) or LST in different viewing directions from multi-scale observations (Cao et al, 2019b; Coll et al, 2019; Trigo et al, 2008)
The statistical results of three solar zenith angles (SZA) values show almost the same tendency and only the results of SZA = 30◦ are discussed in detail while the results of SZA = 10◦ and 50◦ are given in Appendix II

Summary

Introduction

Land surface temperature (LST) is an Essential Climate Variable (ECV) for regional and global applications of surface energy budget and water balance (Anderson et al, 2008; Hu et al, 2020). Numerous models have been developed to simulate the DBT patterns over different Earth targets for removing the directionality effect of satellite LST products (Jacob et al, 2008) The underlying surfaces, such as vegetation (Bian et al, 2017, 2018b; Cao et al, 2018; Du et al, 2007; Huang et al, 2011; Liu et al, 2007, 2019; Pinheiro et al, 2006; Verhoef et al, 2007), bare soil (Ermida et al, 2020; García-Santos et al, 2012; Sobrino and Cuenca, 1999), urban (Fontanilles et al, 2008; GastelluEtchegorry, 2008; Lagouarde et al, 2010; Soux et al, 2004), snow and water (Cheng et al, 2010; Hori et al, 2013), and mixed pixels (Bian et al, 2018a; Cao et al, 2015) have been widely discussed in the context of TIR physical modeling. The angular normalized LST (i.e. nadir LST) can be retrieved from the nadir DBT (DBTnadir,est) using the single channel method (Qin et al, 2001), split window method (Sobrino and Romaguera, 2004; Yu et al, 2009) or temperature and emissivity separation (TES) method (Gillespie et al, 1998; Li et al, 2020)

Methods

Results

Discussion

Conclusion