Retrieving visibility values using satellite remote sensing data

Physics and Chemistry of the Earth

Volumn 35, Issue 1-2, 2010, Pages 121-124

  Hadjimitsis, Diofantos G ^a   Clayton, Chris ^b   Toulios, Leonidas ^c  

^a CYPRUS UNIVERSITY OF TECHNOLOGY   (Cyprus)

^b UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

^c INSTITUTE OF TECHNOLOGY OF AGRICULTURAL PRODUCTS   (Greece)

Author keywords

Aerosol optical thickness; Atmospheric correction; Darkest pixel; Satellite remote sensing; Visibility

Indexed keywords

AEROSOL OPTICAL THICKNESS; AIRPORT STATION; ATMOSPHERIC CONDITIONS; ATMOSPHERIC CORRECTION; ATMOSPHERIC CORRECTION ALGORITHM; ATMOSPHERIC CORRECTIONS; CORRELATION COEFFICIENT; CORRELATION VALUE; IMAGE DATES; LANDSAT TM IMAGES; LANDSAT-5; METEOROLOGICAL PARAMETERS; METEOROLOGICAL STATION; MULTI-TEMPORAL IMAGE; RADIATIVE TRANSFER CALCULATIONS; REGRESSION MODEL; SATELLITE IMAGE DATAS; SATELLITE IMAGES; SATELLITE REMOTE SENSING; SATELLITE REMOTE SENSING DATA;

AIRPORTS; ALGORITHMS; ATMOSPHERIC AEROSOLS; ATMOSPHERICS; METEOROLOGY; PIXELS; REGRESSION ANALYSIS; REMOTE SENSING; SATELLITES;

VISIBILITY;

AEROSOL PROPERTY; ALGORITHM; ATMOSPHERIC CORRECTION; CORRELATION; LANDSAT THEMATIC MAPPER; NUMERICAL MODEL; OPTICAL DEPTH; PIXEL; RADIATIVE TRANSFER; REMOTE SENSING; SATELLITE DATA; SATELLITE IMAGERY; VISIBILITY;

CYPRUS; ENGLAND; HEATHROW AIRPORT; HILLINGDON; LONDON [ENGLAND]; PAPHOS; UNITED KINGDOM;

EID: 77951223039     PISSN: 14747065     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.pce.2010.03.002     Document Type: Article

References (27)

1. Ahern, F.J., Goodenough, D.G., Jain, S.C., Rao, V.R., 1979, Use of clear lakes as standard reflectors for atmospheric measurements. In: Proceedings of the 11th International Symposium on Remote Sensing of Environment, Ann Arbor MI, USA, pp. 731-755.
2. Arino, O., Vermote, E., Spaventa, V., 1997. Operational Atmospheric Correction of Landsat TM Imagery, Earth Observation Quarterly 56.
3. Bowker, D.E., Davis, R.E., 1987. Effects of aerosols and surface shadowing on bi-directional reflectance measurements of deserts. NASA Technical Paper 2765.
4. Campbell J.B. Evaluation of the dark-object subtraction technique for adjustment of multi-spectral remote sensing data. SPIE 1819 (1993) 176-187
5. Chavez, P.S., 1975. Atmospheric, solar, and M.T.F. Corrections for ERTS digital imagery. In: Proceedings of American Society and Photogrammetry, pp. 69-69a.
6. Chavez P.S. An improved dark-object subtraction technique for atmospheric scattering correction of multi-spectral data. Remote Sensing of the Environment 24 (1988) 458-479
7. Elterman, L., 1970. Vertical attenuation model with eight surface meteorological ranges 2 to 13 kilometres. Air Force Cambridge Research Laboratories AFCRL-70-0200.
8. Forster B.C. Derivation of atmospheric correction procedures for Landsat MSS with particular reference to urban data. International Journal of Remote Sensing 5 5 (1984) 799-817
9. Hadjimitsis, D.G., 1999. The application of atmospheric correction algorithms in the satellite remote sensing of reservoirs. PhD Thesis, University of Surrey, School of Engineering in the Environment, Department of Civil Engineering, Guildford, UK.
10. Hadjimitsis D.G. Description of a new method for retrieving the aerosol optical thickness from satellite remotely sensed imagery using the maximum contrast value principle and the darkest pixel approach. Transactions in GIS Journal 5 12 (2008) 633-644
11. Hadjimitsis, D.G., Clayton, C.R.I., 2004. Determination of the aerosol optical thickness and assessment of atmospheric conditions using satellite image-based processing algorithm and radiative transfer theory. In: Proceedings 7th Pan-hellenic (International) Conference of Meteorology, Climatology and Atmospheric Physics, University of Cyprus, Nicosia-Cyprus.
12. Hadjimitsis, D.G., Clayton, C.R.I., 2006. Detecting air pollution from space using image-based method. In: International Conference: Protection and Restoration of the Environment VIII, Crete, July 2006, organized by the Technical University of Crete, Stevens Institute of Technology, p. 313.
13. Hadjimitsis, D.G., Clayton, C.R.I. Hope, V.S., 2000, The Importance of Accounting for Atmospheric Effects in Satellite Remote Sensing: A Case Study from the Lower Thames Valley Area-UK, Space and Robotics 2000, February 2000, New Mexico, USA, sponsored by the ASCE and co-sponsored by NASA and SANDIA National Laboratories, pp. 194-201.
14. Hadjimitsis D.G., Retalis A., and Clayton C.R.I. The assessment of atmospheric pollution using satellite remote sensing technology in large cities in the vicinity of airports, water, air & soil pollution: focus. An International Journal of Environmental Pollution 2 5-6 (2002) 631-640
15. Hadjimitsis, D.G., Clayton, C.R.I., Retalis, A., 2003. Darkest pixel atmospheric correction algorithm: a revised procedure for environmental applications of satellite remotely sensed imagery. In: Proceedings 10th International Symposium on Remote Sensing, 8-12/9/2003, Barcelona-Spain, organised by NASA, SPIE Conference, vol. 5239, pp. 464-471.
16. Hadjimitsis D.G., Clayton C.R.I., and Hope V.S. An assessment of the effectiveness of atmospheric correction algorithms through the remote sensing of some reservoirs. International Journal of Remote Sensing 25 18 (2004) 3651-3674
17. Hadjimitsis, D.G., Themistokleous, K., Vryonides, P., Toulios, L. Clayton, C.R.I., 2007. Satellite-derived determination of aerosol optical thickness for air pollution monitoring: a simplified algorithm, In: Ranjeet, S. Sokhi, Marina Neophytou (Eds.), Proceedings of the 6th International Conference on Urban Air Quality, Limassol, Cyprus, 27-29 March 2007, University of Hertfordshire and University of Cyprus, pp. 143 (CD: ISBN 978-1-905313-46-4).
18. Hill J., and Sturm B. Radiometric correction of multi-temporal thematic mapper data for use in agricultural land cover classification and vegetation monitoring. International Journal of Remote Sensing 12 7 (1993) 1471-1491
19. Jensen, J.R., 2000. Introductory Digital Image Processing. Prentice Hall: New Jersey.
20. Kaufman Y.J. The atmospheric effect on remote sensing and its correction. In: Asrar G. (Ed). Theory and Applications of Optical Remote Sensing (1989), John Wiley, New York
21. Kneizys, F.X., Shettle, E.P., Abreu, L.W., Chetwynd, J.H., Anderson, G.P., Gallery, W.O., Selby, J.E.A. Clough, S.A., 1988. User's guide to LOWTRAN 7, Air Force Geophysics Laboratory, Hanscom AFB Environmental Research Report ERP No. 1010.
22. Mather P. Computer Processing of Remotely-Sensed Images (2001), John Wiley & Sons, Chichester, UK
23. Putsay M. A simple atmospheric correction method for the short wave satellite images. International Journal of Remote Sensing. 13 8 (1992) 1549-1558
24. Tanre D., Herman M., and Deschamps P.Y. Influence of the background contribution upon Space measurements of ground reflectance. Applied Optics 20 (1981) 3673-3684
25. Teillet P.M., and Fedosejevs. On the dark target approach to atmospheric correction of remotely sensed data. Canadian Journal of Remote Sensing 21 4 (1995) 375-381
26. Turner, R.E., Spencer, M.M., 1972. Atmospheric model for correction of spacecraft data. In: Proceedings of the Eighth International Symposium on Remote Sensing of the Environment, II, Michigan: Ann Arbor, pp. 895-934.
27. Vermote E.F., Tanre D., Deuze J.L., Herman M., and Morcrette J.J. Second simulation of the satellite signal in the solar spectrum 6S: an overview. IEE Transactions on Geo-science and Remote Sensing 35 3 (1997) 895-934