Simultaneous retrieval of CO2 and aerosols in a plume from hyperspectral imagery: application to the characterization of forest fire smoke using AVIRIS data

Hyperspectral imagery is a widely used technique to study atmospheric composition. For several years, many methods have been developed to estimate the abundance of gases. However, existing methods do not simultaneously retrieve the properties of aerosols and often use standard aerosol models to describe the radiative impact of particles. This approach is not suited to the characterization of plumes, because plume particles may have a very different composition and size distribution from aerosols described by the standard models given by radiative transfer codes. This article presents a new method to simultaneously retrieve carbon dioxide (CO2) and aerosols inside a plume, combining an aerosol retrieval algorithm using visible and near-infrared (VNIR) wavelengths and a CO2 estimation algorithm using shortwave infrared (SWIR) wavelengths. The microphysical properties of the plume particles, obtained after aerosol retrieval, are used to calculate their optical properties in the SWIR. Then, a database of atmospheric terms is generated with the radiative transfer code, Moderate Resolution Atmospheric Transmission (MODTRAN). Finally, pixel radiances around the 2.0 μm absorption feature are used to retrieve the CO2 abundances. After conducting a signal sensitivity analysis, the method was applied to two airborne visible/infrared imaging spectrometer (AVIRIS) images acquired over areas of biomass burning. For the first image, in situ measurements were available. The results show that including the aerosol retrieval step before the CO2 estimation: (1) induces a better agreement between in situ measurements and retrieved CO2 abundances (the CO2 overestimation of about 15%, induced by neglecting aerosols has been corrected, especially for pixels where the plume is not very thick); (2) reduces the standard deviation of estimated CO2 abundance by a factor of four; and (3) causes the spatial distribution of retrieved concentrations to be coherent.

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

[2]  Daniel Schläpfer,et al.  Atmospheric Precorrected Differential Absorption Technique to Retrieve Columnar Water Vapor , 1998 .

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

[4]  R. Vautard,et al.  Atmospheric composition change – global and regional air quality , 2009 .

[5]  F. Volz Infrared optical constants of aerosols at some locations. , 1983, Applied optics.

[6]  P. Barber Absorption and scattering of light by small particles , 1984 .

[7]  R. Richter,et al.  Processing and Calibration Activities of the Future Hyperspectral Satellite Mission EnMAP , 2010 .

[8]  Stefan Reimann,et al.  Measuring atmospheric composition change , 2009 .

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

[10]  D. Marquardt An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .

[11]  H. Akimoto Global Air Quality and Pollution , 2003, Science.

[12]  J. Rubio,et al.  Spatial patterns of soil temperatures during experimental fires , 2004 .

[13]  COUPLING OXYGEN ABSORPTION AT 761.75 NM WITH SCATTERING BASED ON THE PRIMARY SCATTERING APPROXIMATION - POTENTIAL APPLICATION FOR CIRRUS CLOUD DETECTION OVER OCEAN - , 2005 .

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

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

[16]  L. Gómez-Chova,et al.  Coupled retrieval of aerosol optical thickness, columnar water vapor and surface reflectance maps from ENVISAT/MERIS data over land , 2008 .

[17]  John R. Schott,et al.  Identification and detection of gaseous effluents from hyperspectral imagery using invariant algorithms , 2004, SPIE Defense + Commercial Sensing.

[18]  Y. Yung,et al.  Atmospheric Radiation: Theoretical Basis , 1989 .

[19]  Philippe Gamet,et al.  HYPXIM — A hyperspectral satellite defined for science, security and defence users , 2011, 2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS).

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

[21]  Eyal Agassi,et al.  Detection of gaseous plumes in IR hyperspectral images using hierarchical clustering. , 2007, Applied optics.

[22]  R. Jenssen,et al.  1 THE HYMAP TM AIRBORNE HYPERSPECTRAL SENSOR : THE SYSTEM , CALIBRATION AND PERFORMANCE , 1998 .

[23]  J. Nichol,et al.  An operational MODIS aerosol retrieval algorithm at high spatial resolution, and its application over a complex urban region , 2011 .

[24]  Martin Chamberland,et al.  Algorithms for chemical detection, identification and quantification for thermal hyperspectral imagers , 2005, SPIE Optics East.

[25]  Véronique Carrère,et al.  Carbon dioxide of Pu`u`O`o volcanic plume at Kilauea retrieved by AVIRIS hyperspectral data , 2008 .

[26]  G. Rybicki Radiative transfer , 2019, Climate Change and Terrestrial Ecosystem Modeling.

[27]  Alexandre Alakian,et al.  Retrieval of microphysical and optical properties in aerosol plumes with hyperspectral imagery: L-APOM method , 2009 .

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

[29]  D. Tanré,et al.  Remote Sensing of Tropospheric Aerosols from Space: Past, Present, and Future. , 1999 .

[30]  Andrew K. Heidinger,et al.  Molecular Line Absorption in a Scattering Atmosphere. Part I: Theory , 2000 .

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

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

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

[34]  Lorraine Remer,et al.  The MODIS 2.1-μm channel-correlation with visible reflectance for use in remote sensing of aerosol , 1997, IEEE Trans. Geosci. Remote. Sens..

[35]  David W. Warren,et al.  LWIR/MWIR imaging hyperspectral sensor for airborne and ground-based remote sensing , 1996, Optics & Photonics.

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

[37]  P. Dennison Fire detection in imaging spectrometer data using atmospheric carbon dioxide absorption , 2006 .

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

[39]  C. Posse,et al.  Nonlinear Bayesian Algorithms for Gas Plume Detection and Estimation from Hyper-spectral Thermal Image Data , 2007, Sensors (Basel, Switzerland).