A General Approach to Enhance Short Wave Satellite Imagery by Removing Background Atmospheric Effects

Ronald Scheirer,Adam Dybbroe,Martin Raspaud

doi:10.3390/rs10040560

Ronald Scheirer, Adam Dybbroe + Show 1 more

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https://doi.org/10.3390/rs10040560

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Abstract

Atmospheric interaction distorts the surface signal received by a space-borne instrument. Images derived from visible channels appear often too bright and with reduced contrast. This hampers the use of RGB imagery otherwise useful in ocean color applications and in forecasting or operational disaster monitoring, for example forest fires. In order to correct for the dominant source of atmospheric noise, a simple, fast and flexible algorithm has been developed. The algorithm is implemented in Python and freely available in PySpectral which is part of the PyTroll family of open source packages, allowing easy access to powerful real-time image-processing tools. Pre-calculated look-up tables of top of atmosphere reflectance are derived by off-line calculations with RTM DISORT as part of the LibRadtran package. The approach is independent of platform and sensor bands, and allows it to be applied to any band in the visible spectral range. Due to the use of standard atmospheric profiles and standard aerosol loads, it is possible just to reduce the background disturbance. Thus signals from excess aerosols become more discernible. Examples of uncorrected and corrected satellite images demonstrate that this flexible real-time algorithm is a useful tool for atmospheric correction.

Highlights

Any satellite based Earth remote sensing application has to deal with the atmosphere
The main aim of the approach presented in this paper is to provide an easy to use tool that allows generating high contrast true color imagery by correcting for the most prominent atmospheric effects, i.e., scattering and absorption for both gaseous constituents as well as standard aerosols
The observations of two consecutive overpasses are separated in time by approximately 102 min

Summary

Introduction

Any satellite based Earth remote sensing application has to deal with the atmosphere. Either the atmosphere (and its constituents) itself is in the focus of the study or it is regarded as a source of perturbation The latter applies when the scope is observation of phenomena on the surface of the Earth. This resulted in around 2.3 million radiative transfer simulations.

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