EventsInternational Conference on Advanced Remote Sensing (ICARS 2025)
Published
This submission belongs to the session S1. Hyperspectral Remote Sensing and Imaging Spectroscopy of the event International Conference on Advanced Remote Sensing (ICARS 2025)
Published date
25 Mar, 2025
Academic Editor
author-avatarFabio Tosti
Citation
Liu Xu, Fast and Accurate Radiative Transfer Model for Hyperspectral Remote Sensing Applications, in Proceedings of International Conference on Advanced Remote Sensing (ICARS 2025), Barcelona, 26 March–28 March 2025, MDPI: Basel, Switzerland
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Fast and Accurate Radiative Transfer Model for Hyperspectral Remote Sensing Applications

1. NASA Langley Research Center, USA
Abstract

A Principal Component-based Radiative Transfer Model (PCRTM), which can calculate TOA radiance or reflectance spectra from 50 cm-1 to 40,000 cm-1 (200 mm to 0.25 mm) was developed. It demonstrated very good accuracy relative to reference Line-by-Line radiative transfer models and saves orders of magnitude in computational time. The PCRTM performs radiative transfer calculation in a limited number of monochromatic wavelengths, which avoids the approximation assumptions that are made in the correlated-K method. The PCRTM model was developed for hyperspectral sensors such as AIRS, CrIS, IASI, NAST-I, SHIS, FIRST, and CLARREO-IR in the thermal IR spectral region and CLARREO-Solar, CPF, TEMPO, EMIT, OMI, and SCIAMACHY in the solar spectral region. The PCRTM's accuracy was demonstrated via RTM intercomparisons and with real satellite observations from AIRS, CrIS, IASI, SCIAMACHY, EMIT, etc. The PCRTM has been used in many satellite remote sensing applications. Examples include forward modeling in Level-2 and Level-3 retrieval algorithms, high-fidelity satellite instrument simulators and instrument performance trade studies, spectral and radiometric accuracy characterizations of satellite Level-1 data, tools for inter-satellite calibrations, tools for satellite RTM lookup table generations, and tools for generating physically based training datasets for Artificial Intelligence (AI) algorithms.

Keywords
radiative transfer model
forward model
PCRTM
hyper spectral remote sensors
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