Abstract

Kernel-driven models provide an effective way for correcting the thermal radiation directionality effect. Under a general kernel-driven modeling framework proposed by Cao et al. , by using three fixed-width hotspot kernels, and considering whether to combine two existing base shape kernels, this article proposed nine kernel-driven models with different coefficient requirements. Specifically, the three hotspot kernels are four-component kernel ( K GO4), three-component kernel ( K GO3), and sunlit soil kernel ( K GOg), and the two base shape kernels are temperature difference kernel ( K LSF) and emissivity kernel ( K Emi). Based on discrete anisotropic radiative transfer model, a comprehensive simulation data set, including three fraction of vegetation covers (FVC) and 36 component temperature profiles, was generated for evaluating the performances of novel models. First, the order of model performances was determined, and the result is basically independent of FVC and component temperature difference. In the case of five-parameter, four-parameter, three-parameter, and two-parameter, the best models are GO4_LSF model or GO4_Emi model, GO3_LSF model or GO3_Emi model, GOg_LSF model or GOg_Emi model, and GOg model, respectively. In addition, for three-parameter models, the comparison with two current linear kernel-driven models, i.e., LSF_Li model and Vinnikov model, was discussed in detail, and it is revealed that newly proposed GOg_LSF and GOg_Emi model in this article have a better performance.

Highlights

  • Land surface temperature (LST) is one of the most important variables for a variety of fields such as hydrological cycle, climate change, agriculture and meteorology [1, 2]

  • Lagouarde et al [12] presented an important anisotropy for Toulouse city based on observations from two airborne thermal infrared (TIR) cameras

  • The hotspot-emissivity model has been successfully used to generate new-version MSG LST product, which has an extra data layer of the expected LST deviation with respect to a reference view. Different from this modeling methodology, Cao et al [27] found that the thermal emission of a vegetated canopy is mostly driven by the geometric optical (GO) effect, and directional temperature can be treated as a sum of an isotropic kernel representing temperatures at nadir, a hotspot kernel with adjustable width expressing the temperature difference between sunlit and shaded components, a base shape kernel describing the temperature difference between vegetation and soil

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Summary

INTRODUCTION

Land surface temperature (LST) is one of the most important variables for a variety of fields such as hydrological cycle, climate change, agriculture and meteorology [1, 2]. The hotspot-emissivity model has been successfully used to generate new-version MSG LST product, which has an extra data layer of the expected LST deviation with respect to a reference view (https://landsaf.ipma.pt/en/products/landsurface-temperature/lst/) Different from this modeling methodology, Cao et al [27] found that the thermal emission of a vegetated canopy is mostly driven by the GO effect, and directional temperature can be treated as a sum of an isotropic kernel representing temperatures at nadir, a hotspot kernel with adjustable width expressing the temperature difference between sunlit and shaded components, a base shape kernel describing the temperature difference between vegetation and soil.

KERNEL-DRIVEN MODELS
Overall performances of new models
Sensitive analysis
COMPARISON WITH CURRENT MODEL
Reasons of the performance order
CONCLUSION
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