A Method for Converting Satellite-Observed Thermal Infrared Radiance to Nadir Radiance: A Case Study in Desert Regions

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Authors: Zhengyang Wang, Jie Cheng, Weihan Liu
Cited by: 0
References: 70

Abstract

Surface emissivity is directional, for homogeneous surfaces, increasing View Zenith Angle (VZA) reduces surface emissivity while simultaneously extending the atmospheric path length. This combined effect changes the radiance detected by satellite sensors. In this study, simulation experiments were initially conducted, revealing that as the VZA increases, the decrease in emissivity retrieved by Temperature and Emissivity Separation (TES) algorithm is less pronounced than the actual decrease in surface emissivity. Concurrently, the retrieved Land Surface Temperature (LST) also decreases. Subsequently, two sites were selected in the Sahara Desert and the Taklamakan Desert. Using the Moderate Resolution Imaging Spectroradiometer (MODIS) radiance product (MYD21KM) and the TES-derived temperature and emissivity product (MYD21), the impact of VZA on TES-derived surface temperature and emissivity products was analyzed. Additionally, longwave radiation data and broadband emissivity were employed to calculate surface temperature. Based on this analysis, a ratio correction method was proposed to convert satellite-observed thermal infrared radiance to nadir radiance, taking desert regions as a case study. The results demonstrated that for MODIS band 29 (8.55 μm), when VZA = 48.5°, the bias improved from −1.49 to 0.64, and from −2.05 to 0.84, while the corresponding RMSE decreased from 1.51 to 0.89, and from 2.08 to 1.17 (10⁻⁷ W·cm⁻²·sr⁻¹·cm⁻¹) for Top-Of-Atmosphere (TOA) and Bottom-Of-Atmosphere (BOA) radiance, respectively. When VZA = 35.2°, the bias improved from −0.32 to 0.12, and from −0.14 to 0.15, and the RMSE decreased from 0.72 to 0.69, and from 0.95 to 0.90 (10⁻⁷ W·cm⁻²·sr⁻¹·cm⁻¹) for TOA and BOA radiance, respectively. The method proves to be more suitable when VZA > 40°.

Fields of Study & Subjects

Calibration and Measurement Techniques Atmospheric aerosols and clouds Remote Sensing in Agriculture

Publication details

Journal / source
IEEE Transactions on Geoscience and Remote Sensing
Volume
64
Pages
1–18
Publication date
1 January 2026
Language
EN