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Parametric 3D Atmospheric Reconstruction in Highly Variable Terrain with Recycled Monte Carlo Paths and an Adapted Bayesian Inference EngineWe describe a method for accelerating a 3D Monte Carlo forward radiative transfer model to the point where it can be used in a new kind of Bayesian retrieval framework. The remote sensing challenge is to detect and quantify a chemical effluent of a known absorbing gas produced by an industrial facility in a deep valley. The available data is a single low resolution noisy image of the scene in the near IR at an absorbing wavelength for the gas of interest. The detected sunlight has been multiply reflected by the variable terrain and/or scattered by an aerosol that is assumed partially known and partially unknown. We thus introduce a new class of remote sensing algorithms best described as "multi-pixel" techniques that call necessarily for a 3D radaitive transfer model (but demonstrated here in 2D); they can be added to conventional ones that exploit typically multi- or hyper-spectral data, sometimes with multi-angle capability, with or without information about polarization. The novel Bayesian inference methodology uses adaptively, with efficiency in mind, the fact that a Monte Carlo forward model has a known and controllable uncertainty depending on the number of sun-to-detector paths used.
Document ID
20150005625
Acquisition Source
Jet Propulsion Laboratory
Document Type
Conference Paper
External Source(s)
Authors
Langmore, Ian
(Columbia Univ. New York, NY, United States)
Davis, Anthony B.
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Bal, Guillaume
(Columbia Univ. New York, NY, United States)
Marzouk, Youssef M.
(Massachusetts Inst. of Tech. Cambridge, MA, United States)
Date Acquired
April 13, 2015
Publication Date
August 6, 2012
Subject Category
Fluid Mechanics And Thermodynamics
Instrumentation And Photography
Earth Resources And Remote Sensing
Statistics And Probability
Meeting Information
Meeting: International Radiation Symposium 2012 (IRS2012)
Location: Berlin
Country: Germany
Start Date: August 6, 2012
End Date: August 10, 2012
Sponsors: European Space Agency, Deutsches Zentrum fuer Luft- und Raumfahrt (DLR), Freie Univ.
Funding Number(s)
CONTRACT_GRANT: NSF-DMS-0804696
CONTRACT_GRANT: DE-FG52-08NA28779
Distribution Limits
Public
Copyright
Other
Keywords
Monte Carlo
remote sensting
3-D radiative transfer
multi-pixel techniques
Bayesian methods

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