Statistics – Methodology
Scientific paper
Aug 2005
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005spie.5890..248a&link_type=abstract
Atmospheric and Environmental Remote Sensing Data Processing and Utilization: Numerical Atmospheric Prediction and Environmental
Statistics
Methodology
1
Scientific paper
Tracking the Aerosol Optical Depth (AOD) is of particular importance in monitoring aerosol contributions to global radiative forcing. Until now, the two standard techniques used for retrieving AOD were; (i) sun photometry, and (ii) satellite-based approaches, such as based DDV (Dense Dark Vegetation) inversion algorithms. These methods are only available for use during daylight time since they are based on direct or indirect observation of sunlight. Few attempts have been made to measure AOD behaviour at night. One such method uses spectrally-calibrated stars as reference targets but the number of available stars is limited. This is especially true for urban sites where artificial lighting hides most of these stars. In this research, we attempt to provide an alternate method, one which exploits artificial sky glow or light pollution. This methodology links a 3D light pollution model with in situ light pollution measurements. The basic idea is to adjust an AOD value into the model in order to fit measured light pollution. This method requires an accurate model that includes spatial heterogeneity in lighting angular geometry, in lighting spectral dependence, in ground spectral reflectance and in topography. This model, named ILLUMINA, computes 1st and 2nd order molecular and aerosol scattering, as well as aerosol absorption. These model features represent major improvements to previous light pollution models. Therefore, new possibilities for light pollution studies will arise, many of which are of particular interest to the astronomical community. In this paper we will present a first sensitive study applied to the ILLUMINA model.
Aube Martin
Franchomme-Fosse L.
Houle V.
Robert-Staehler P.
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