2003Unpublished venueRequires access

The couple-inversion of atmospheric profile and surface temperature and emissivity from MODIS data

Liangfu Chen, Qin-Hou Liu, Zhao-Liang Li, Xiru Xu

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Abstract

A couple-inversion algorithm that retrieves geophysical parameters from MODIS measurements was developed. The retrieved geophysical parameters include atmospheric temperature-humidity profiles, pixel-averaged surface temperature and emissivity within the thermal infrared regions (6/spl sim/16 /spl mu/m). The Modtran atmospheric radiative transfer code was used to simulate the measured radiances and atmospheric transmittance. Then the genetic algorithm was employed to generate a regularization solution that updates the first-guesses of atmospheric temperature, water-vapor profiles, surface skin temperature and emissivity. The algorithm proposed in this paper was first tested with simulated data.

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What this paper is about

A couple-inversion algorithm that retrieves geophysical parameters from MODIS measurements was developed. The retrieved geophysical parameters include atmospheric temperature-humidity profiles, pixel-averaged surface temperature and emissivity within the thermal infrared regions (6/spl sim/16 /spl mu/m). The Modtran atmospheric radiative transfer code was used to simulate the measured radiances and atmospheric transmittance. Then the genetic algorithm was employed to generate a regularization solution that updates the first-guesses of atmospheric temperature, water-vapor profiles, surface skin temperature and emissivity. The algorithm proposed in this paper was first tested with simulated data.

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Available abstract

A couple-inversion algorithm that retrieves geophysical parameters from MODIS measurements was developed. The retrieved geophysical parameters include atmospheric temperature-humidity profiles, pixel-averaged surface temperature and emissivity within the thermal infrared regions (6/spl sim/16 /spl mu/m). The Modtran atmospheric radiative transfer code was used to simulate the measured radiances and atmospheric transmittance. Then the genetic algorithm was employed to generate a regularization solution that updates the first-guesses of atmospheric temperature, water-vapor profiles, surface skin temperature and emissivity. The algorithm proposed in this paper was first tested with simulated data.

Key concepts: MODTRAN, Emissivity, Atmospheric correction, Remote sensing, Radiative transfer, Infrared window, Atmospheric temperature, Environmental science

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