Dr. Eric Vermote

 
Education

PhD  Atmospheric Optics, University of Lille, France, 1990
Engineer Degree, Ecoles des Hautes Etudes Industrielles, Lille, France, 1987

Research Projects

• MODIS/NPP VIIRS surface and top of the atmosphere reflectances evaluation, maintenance, validation and refinement

  • The purpose of this project is to correct remotely sensed data for the effects of the atmosphere (gases, aerosols). The surface reflectance product is used in the generation of several land products: Vegetation Indices, BRDF, Land Cover, Snow Cover, Thermal Anomalies, and LAI/FPAR.

  Web-enabled Landsat data (WELD) – a consistent seamless near real time MODIS-Landsat data fusion for the terrestrial user community

  • The purpose of this project is to improve the consistency and quality of ETM+ SLC-off data through a fusion of various MODIS products, thereby generating “seamless” radiometrically consistent mosaiced data sets.

  A 0.05 degree global climate/interdisciplinary long term data set from AVHRR, MODIS and VIIRS instruments

  • The LTDR (Land Long Term Data Record) project produces consistent AVHRR and MODIS data for climate studies. The purpose of this project is to include within this data set the daily surface reflectance and NDVI products at the resolution of 0.05

  A Terrestrial Surface Climate Data Record for Global Change Studies

  • The purpose of this research is to use state of the art methods to develop a global long term dataset to study land surface changes. The data set will be based on several different satellites starting in the early 1980’s to the present. The dynamic data continuity between satellites addresses instrument calibration as well as different instrument sensing characteristics. The data set will enable to study of impacts and feedbacks of climate on land surface and vegetation properties.

  Recent Papers

  
  Roy, D.P., Ju, J., Kline, K., Scaramuzza, P.L., Kovalskyy, V., Hansen, M.C., Loveland,T.R., Vermote, E.F., Zhang, C., 2010, Web-enabled Landsat Data (WELD): Landsat ETM+ Composited Mosaics of the Conterminous United States, Remote Sensing of Environment, 114: 35-49.
  

  Cao, C., E. Vermote, and X. Xiong (2009), Using AVHRR lunar observations for NDVI long-term climate change detection, J. Geophys. Res., 11410.1029/2009jd012179.
   

  Vermote, E., E. Ellicott, O. Dubovik, T. Lapyonok, M. Chin, L. Giglio, and G. J. Roberts (2009), An approach to estimate global biomass burning emissions of organic and black carbon from MODIS fire radiative power, J. Geophys. Res., 11410.1029/2008jd011188.
   

  Ellicott, E., E. Vermote, L. Giglio, and G. Roberts (2009), Estimating biomass consumed from fire using MODIS FRE, Geophys. Res. Lett., 36, L13401, doi:10.1029/2009GL038581.
  

  Huang, C., S. Goward, J. Masek, F. Gao, E. Vermote, N. Thomas, K. Schleeweis, R. Kennedy, Z. Zhu, J. Eidenshink, and J. Townshend (2009), Development of time series stacks of Landsat images for reconstructing forest disturbance history, International Journal of Digital Earth, 2(3), 195-218.
   

  Hutchison, K. D., R. L. Mahoney, E. F. Vermote, T. J. Kopp, J. M. Jackson, A. Sei, and B. D. Iisager (2009), A Geometry-Based Approach to Identifying Cloud Shadows in the VIIRS Cloud Mask Algorithm for NPOESS, journal of Atmospheric and Oceanic Technology, 26(7), 1388-1397
  

  Eck, T. F., B. N. Holben, J. S. Reid, A. Sinyuk, E. J. Hyer, N. T. O'Neill, G. E. Shaw, J. R. Vande Castle, F. S. Chapin, O. Dubovik, A. Smirnov, E. Vermote, J. S. Schafer, D. Giles, I. Slutsker, M. Sorokine, and W. W. Newcomb (2009), Optical properties of boreal region biomass burning aerosols in central Alaska and seasonal variation of aerosol optical depth at an Arctic coastal site, J. Geophys. Res., 114
  

  E. Vermote, C. Justice, F.M. Bréon, (2009) “Toward Towards a generalized approach for correction of the BRDF effect in MODIS directional reflectances”, in IEEE Transactions in Geoscience and Remote Sensing, 47,3,898-908.
  

  Ellicott, E., Vermote, E., Petitcolin, F. and Hook, S.J. (2009) Validation of a New Parametric Model for Atmospheric Correction of Thermal Infrared Data. Geoscience and Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing,,47, 295-311.
  

  Nagol, J.R., Vermote, E.F. and Prince, S.D. (2009) Effects of atmospheric variation on AVHRR NDVI data. Remote Sensing of Environment,113, 392-397..

• Link to Dr. Eric Vermote's Current CV