OSA's Digital Library

Applied Optics

Applied Optics


  • Editor: Joseph N. Mait
  • Vol. 50, Iss. 28 — Oct. 1, 2011
  • pp: 5408–5421

OSIS: remote sensing code for estimating aerosol optical properties in urban areas from very high spatial resolution images

Colin Thomas, Xavier Briottet, and Richard Santer  »View Author Affiliations

Applied Optics, Vol. 50, Issue 28, pp. 5408-5421 (2011)

View Full Text Article

Enhanced HTML    Acrobat PDF (1007 KB)

Browse Journals / Lookup Meetings

Browse by Journal and Year


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools



The achievement of new satellite or airborne remote sensing instruments enables the more precise study of cities with metric spatial resolutions. For studies such as the radiative characterization of urban features, knowledge of the atmosphere and particularly of aerosols is required to perform first an atmospheric compensation of the remote sensing images. However, to our knowledge, no efficient aerosol characterization technique adapted both to urban areas and to very high spatial resolution images has yet been developed. The goal of this paper is so to present a new code to characterize aerosol optical properties, OSIS, adapted to urban remote sensing images of metric spatial resolution acquired in the visible and near-IR spectral domains. First, a new aerosol characterization method based on the observation of shadow/sun transitions is presented, offering the advantage to avoid the assessment of target reflectances. Its principle and the modeling of the signal used to solve the retrieval equation are then detailed. Finally, a sensitivity study of OSIS from synthetic images simulated by the radiative transfer code AMARTIS v2 is also presented. This study has shown an intrinsic precision of this tool of Δ τ a = 0.1 . τ a ± ( 0.02 + 0.4 . τ a ) for retrieval of aerosol optical thicknesses. This study shows that OSIS is a powerful tool for aerosol characterization that has a precision similar to satellite products for the aerosol optical thicknesses retrieval and that can be applied to every very high spatial resolution instrument, multispectral or hyperspectral, airborne or satellite.

© 2011 Optical Society of America

OCIS Codes
(010.1100) Atmospheric and oceanic optics : Aerosol detection
(100.3190) Image processing : Inverse problems
(280.1100) Remote sensing and sensors : Aerosol detection

ToC Category:
Atmospheric and Oceanic Optics

Original Manuscript: April 26, 2011
Revised Manuscript: July 21, 2011
Manuscript Accepted: July 26, 2011
Published: September 22, 2011

Colin Thomas, Xavier Briottet, and Richard Santer, "OSIS: remote sensing code for estimating aerosol optical properties in urban areas from very high spatial resolution images," Appl. Opt. 50, 5408-5421 (2011)

Sort:  Author  |  Year  |  Journal  |  Reset  


  1. K. S. Krause, “Relative radiometric characterization and performance of the QuickBird high-resolution commercial imaging satellite,” Proc. SPIE 5542, 35–44 (2004). [CrossRef]
  2. G. Dial, H. Bowen, F. Gerlach, J. Grodecki, and R. Oleszczuk, “IKONOS satellite, imagery, and products,” Remote Sens. Environ. 88, 23–36 (2003). [CrossRef]
  3. Digital Globe, http://digitalglobe.com.
  4. GeoEye, http://geoeye.com.
  5. F. de Lussy, P. Kubik, D. Greslou, V. Pascal, P. Gigord, and J. P. Cantou, “PLEIADES-HR image system products and quality—PLEIADES-HR image system products and geometric accuracy,” Tech. Rep. (Centre National d'Etudes Spaciales, 2005).
  6. P. Déliot, J. Duffaut, and A. Lacan, “Characterization and calibration of a high resolution multi-spectral airborne digital camera,” Proc. SPIE 6031, 603104 (2006). [CrossRef]
  7. R. O. Green, M. L. Eastwood, C. H. Sarture, T. G. Chrien, M. Aronsson, B. J. Chippendale, J. A. Faust, B. E. Pavri, C. J. Chovit, M. Solis, M. R. Olah, and O. Williams, “Imaging spectroscopy and the airborne visible/infrared imaging spectrometer (AVIRIS),” Remote Sens. Environ. 65, 227–248 (1998). [CrossRef]
  8. A. Puissant and J. Hirsch, “Télédétection urbaine et résolution spatiale optimale: intérêt pour les utilisateurs et aide pour les classifications,” Revue Internationale de Géomatique 14, 403–415 (2004). [CrossRef]
  9. Q. Weng and D. A. Quattrocchi, Urban Remote Sensing (CRC Press, 2007).
  10. S. Lachérade, C. Miesch, D. Boldo, X. Briottet, C. Valorge, and H. Le Men, “ICARE: a physically-based model to correct atmospheric and geometric effects from high spatial and spectral remote sensing images over 3D urban areas,” Meteorol. Atmos. Phys. 102, 209–222 (2008). [CrossRef]
  11. M. D. King, Y. J. Kaufman, D. Tanré, and T. Nakajima, “Remote sensing of tropospheric aerosols from space: past, present and future,” Bull. Am. Meteorol. Soc. 80, 2229–2260(1999). [CrossRef]
  12. Y. J. Kaufman, D. Tanré, L. A. Remer, E. F. Vermote, A. Chu, and B. N. Holben, “Operational remote sensing of tropospheric aerosol over land from EOS-moderate resolution imaging spectroradiometre,” J. Geophys. Res. 102, 17051–17067 (1997). [CrossRef]
  13. Y. J. Kaufman, A. E. Wald, L. A. Remer, B. C. Gao, R. R. Li, and L. Flynn, “The MODIS 2.1 μm channel-correlation with visible reflectance for use in remote sensing of aerosol,” IEEE Trans. Geosci. Remote Sens. 35, 1286–1298 (1997). [CrossRef]
  14. B. N. Holben, E. Vermote, Y. J. Kaufman, D. Tanré, and V. Kalb, “Aerosol retrieval over land from AVHRR data—Application for atmospheric correction,” IEEE Trans. Geosci. Remote Sens. 30, 212–222 (1992). [CrossRef]
  15. D. Tanré, P. Y. Deschamps, C. Devaux, and M. Herman, “Estimation of Saharan aerosol optical thickness from blurring effects in thematic mapper data,” J. Geophys. Res. 93, 15955 (1988). [CrossRef]
  16. O. Hagolle, G. Dedieu, B. Mougenot, V. Debaecker, B. Duchemin, and A. Meygret, “Correction of aerosol effects on multi-temporal images acquired with constant viewing angles: application to Formosat-2 images,” Remote Sens. Environ. 112, 1689–1701 (2008). [CrossRef]
  17. J. P. Veefkind, G. deLeeuw, and P. A. Durkee, “Retrieval of aerosol optical depth over land using two-angle view satellite radiometry during TARFOX,” Geophys. Res. Lett. 25, 3135–3138 (1998). [CrossRef]
  18. J. V. Martonchik, D. J. Diner, R. Kahn, T. P. Ackerman, M. M. Verstraete, B. Pinty, and H. R. Gordon, “Techniques for the retrieval of aerosol properties over land and ocean using multiangle imaging,” IEEE Trans. Geosci. Remote Sens. 36, 1212–1227 (1998). [CrossRef]
  19. J. V. Martonchik, D. J. Diner, R. Kahn, and B. Gaitley, “Comparison of MISR and AERONET aerosol optical depths over desert sites,” J. Geophys. Res. 31, L16102(2004).
  20. D. A. Vincent, “Aerosol optical depth retrieval from high-resolution commercial satellite imagery over areas of high surface reflectance,” Ph.D. thesis (Naval Postgraduate School, 2006).
  21. C. Thomas, S. Doz, X. Briottet, R. Santer, D. Boldo, and S. Mathieu, “Remote sensing of aerosols in urban areas: sun/shadow retrieval procedure from airborne very high spatial resolution images,” in Proceedings of 2009 Joint Urban Remote Sensing Event (IEEE, 2009), pp. 1–6. [CrossRef]
  22. C. Thomas, “Caractérisation des aérosols atmosphériques en milieu urbain par télédétection à très haute résolution spatiale,” Ph.D. thesis (University of Toulouse, 2010).
  23. C. Miesch, X. Briottet, Y. H. Kerr, and F. Cabot, “Monte Carlo approach for solving the radiative transfer equation over mountainous and heterogeneous areas,” Appl. Opt. 38, 7419–7430 (1999). [CrossRef]
  24. C. Thomas, S. Doz, X. Briottet, Département Optique Théorique et Appliquée, Oera, Toulouse, France, and S. Lachérade are preparing a manuscript to be called, “AMARTIS v2: 3D radiative transfer code in the [0.4; 2.5 μm] spectral domain dedicated to urban areas.”
  25. S. Lachérade, C. Miesch, X. Briottet, and H. Le Men, “Spectral variability and bidirectional reflectance behaviour of urban materials at a 20 cm spatial resolution in the visible and near infrared wavelengths. A case study over Toulouse (France),” Int. J. Remote Sens. 26, 3859–3866 (2005). [CrossRef]
  26. M. Herold and D. Roberts, “Spectral characteristics of asphalt road aging and deterioration: implication for remote sensing applications,” Appl. Opt. 44, 4327–4334 (2005). [CrossRef] [PubMed]
  27. P. M. Dare, “Shadow analysis in high-resolution satellite imagery of urban areas,” Photog. Eng. Remote Sens. 71, 169–177(2005).
  28. E. F. Vermote, D. Tanré, J. L. Deuzé, M. Herman, and J. J. Morcrette, “Second simulation of the satellite signal in the solar spectrum, 6S: an overview,” IEEE Trans. Geosci. Remote Sens. 35, 675–686 (1997). [CrossRef]
  29. E. F. Vermote, D. Tanré, J. L. Deuze, M. Herman, and J. J. Morcrette, “Second simulation of the satellite signal in the solar spectrum (6S), 6S user’s guide version 2,” (NASA Goddard Space Flight Center, 1997).
  30. G. Thuillier, M. Hersé, P. C. Simon, D. Labs, H. Mandel, D. Gillotay, and T. Foujols, “The solar spectral irradiance from 200 to 2400 nm as measured by the SOLSPEC spectrometer from the ATLAS 1-2-3 and EURECA missions,” Sol. Phys. 214, 1–22 (2003). [CrossRef]
  31. A. Angström, “On the atmospheric transmission of sun radiation and on dust in the air,” Geograf. Ann. 11, 156–166 (1929). [CrossRef]
  32. C. Thomas, X. Briottet, R. Santer, and S. Lachérade, “Aerosols in urban areas: optical properties and impact on the signal incident to an airborne high-spatial resolution camera,” Proc. SPIE 7107, 71070O (2008). [CrossRef]
  33. B. N. Holben, T. F. Eck, I. Slutsker, D. Tanré, J. P. Buis, A. Setzer, E. Vermote, J. A. Reagan, Y. Kaufman, T. Nakajima, F. Lavenu, I. Jankowiak, and A. Smirnov, “AERONET—A federated instrument network and data archive for aerosol characterization,” Remote Sens. Environ. 66, 1–16 (1998). [CrossRef]
  34. L. C. Henyey, and J. L. Greenstein, “Diffuse radiation in the galaxy,” Astrophys. J. 93, 70–83 (1941). [CrossRef]
  35. R. Santer, “Atmospheric products over land for MERIS level 2,” Tech. Rep. ATBD 2.15 (European Space Agency, 2000), http://envisat.esa.int/instruments/meris/pdf.
  36. S. Doz, X. Briottet, S. Lache´rade, and D. Boldo, “Simulation over urban area: two case study,” in Proceedings of 2009 Joint Urban Remote Sensing Event (IEEE, 2009). [CrossRef]
  37. U. Heiden, K. Segl, S. Roessner, and H. Kaufmann, “Determination of robust spectral features for identification of urban surface materials in hyperspectral remote sensing data,” Remote Sens. Env. 111, 537–552 (2007). [CrossRef]
  38. M. Herold, D. A. Roberts, M. E. Gardner, and P. E. Dennison, “Spectrometry for urban area remote sensing—development and analysis of a spectral library from 350 to 2400 nm,” Remote Sens. Env. 91, 304–319 (2004). [CrossRef]
  39. C. O. Justice, J. R. G. Townshend, E. F. Vermote, E. Masuoka, R. E. Wolfe, N. Saleous, D. P. Roy, and J. T. Morisette, “An overview of MODIS Land data processing and product status,” Remote Sens. Environ. 83, 3–15 (2002). [CrossRef]
  40. M. Cook, B. Peterson, G. Dial, F. Gerlach, K. Hutchins, R. Kudola, and H. Bowen, “IKONOS technical performance assessment,” Proc. SPIE 4381, 94–108 (2001). [CrossRef]
  41. R. C. Levy, L. A. Remer, D. Tanré, S. Mattoo, and Y. J. Kaufman, “Algorithm for remote sensing of tropospheric aerosol from MODIS: collections 005 and 051: Revision 2,” Tech. Rep. (NASA, 2009).

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited