Retrieval of microphysical and optical properties in aerosol plumes with hyperspectral imagery: L-APOM method

This paper presents the retrieval method L-APOM which aims at characterizing the microphysical and optical properties of aerosol plumes from hyperspectral images with high spatial resolution. The inversion process is divided into three steps: estimation of the ground reflectance below the plume, characterization of the standard atmosphere (gases and background aerosols) and estimation of the plume aerosols properties. As using spectral information only is not sufficient to insure uniqueness of solutions, original constraints are added by assuming slow spatial variations of particles properties within the plume. The whole inversion process is validated on a large set of simulated images and reveals to remain accurate even in the worst cases of noise: relative estimation errors of aerosol properties remain between 10% and 20% in most cases. L-APOM is applied on a real AVIRIS hyperspectral image of a biomass burning plume for which in situ measurements are available. Retrieved properties appear globally consistent with measurements.

[1]  O. Boucher,et al.  Global estimate of aerosol direct radiative forcing from satellite measurements , 2005, Nature.

[2]  O. Boucher,et al.  A satellite view of aerosols in the climate system , 2002, Nature.

[3]  G. Mie.  Beiträge zur Optik trüber Medien, speziell kolloidaler Metallösungen , 1908 .

[4]  J. Roger,et al.  A study of the mixing state of black carbon in urban zone , 2004 .

[5]  M. Jacobson,et al.  Strong radiative heating due to the mixing state of black carbon in atmospheric aerosols , 2022 .

[6]  Zhanqing Li,et al.  Retrieval of Optical Depth for Heavy Smoke Aerosol Plumes: Uncertainties and Sensitivities to the Optical Properties , 2002 .

[7]  Y. Kaufman,et al.  Passive remote sensing of tropospheric aerosol and atmospheric , 1997 .

[8]  T. Eck,et al.  A review of biomass burning emissions part III: intensive optical properties of biomass burning particles , 2004 .

[9]  D. Blake,et al.  Physical, chemical, and optical properties of regional hazes dominated by smoke in Brazil , 1998 .

[10]  Thomas Trautmann,et al.  Simulation of a biomass-burning plume: Comparison of model results with observations , 2002 .

[11]  Oleg Dubovik,et al.  Microphysical and optical properties of aerosol particles in urban zone during ESCOMPTE , 2003 .

[12]  D. C. Robertson,et al.  MODTRAN cloud and multiple scattering upgrades with application to AVIRIS , 1998 .

[13]  Jessica A. Faust,et al.  Imaging Spectroscopy and the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) , 1998 .

[14]  Daniel Schlaepfer,et al.  Aerosol mapping over rugged heterogeneous terrain with imaging spectrometer data , 2002, SPIE Optics + Photonics.

[15]  S. Quegan,et al.  Ionospheric structure produced during a rapid polar cap expansion , 1997 .

[16]  K. Stamnes,et al.  Numerically stable algorithm for discrete-ordinate-method radiative transfer in multiple scattering and emitting layered media. , 1988, Applied optics.

[17]  Yoram J. Kaufman,et al.  Information on aerosol size distribution contained in solar reflected spectral radiances , 1996 .

[18]  Rodolphe Marion,et al.  Measuring trace gases in plumes from hyperspectral remotely sensed data , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[19]  Rodolphe Marion,et al.  Atmospheric correction of hyperspectral data over dark surfaces via simulated annealing , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[20]  D. Tanré,et al.  Remote sensing of aerosol properties over oceans using the MODIS/EOS spectral radiances , 1997 .

[21]  S. Gassó,et al.  Comparison of Columnar Aerosol Optical Properties Measured by the MODIS Airborne Simulator with In Situ Measurements , 1998 .

[22]  Joel S. Levine,et al.  Biomass burning and global change , 2008 .

[23]  Alexandre Alakian,et al.  Remote sensing of aerosol plumes: a semianalytical model. , 2008, Applied optics.