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Impact of Atmospheric Correction on Land-use Classification and Water Demand for the Aral Sea Basin

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Abstract

The Aral Sea, once the fourth largest inland sea in surface area in the world, is located at the border between Kazakhstan and Uzbekistan. Water was taken out from two major rivers to expand the area of irrigated land, resulting in desertification of the sea. The drying part of the sea remained heavily salted after water evaporation, causing salt and dust storms and therefore Aeolian deposition of these components on plants, affecting agricultural productivity and quality. Atmospheric effects in the interpretation of time series images of land characteristics are used to estimate currently cultivated areas being irrigated in the Syrdarya flood plain, to determine water demand. This paper examines differences between single and time series land classification, and the effects of atmospheric correction. Ground-truth data from a fieldtrip in Kazakhstan are presented.

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References

  1. Ahern FJ., Goodnenough D.G., Jain SC., and Rao VR. “Use of clear lakes as standard reflectors for atmospheric measurements”. In: Arbor Ann (ed). Proc. 11th International Symposium on Remote Sensing of Environment, MI, USA, (1977) 731–755.

  2. Campbell JB. (ed). “Introduction to Remote Sensing” Second edition, Taylor and Francis, London. (1996).

    Google Scholar 

  3. Chavez PS. “An improved dark-object subtraction technique for atmospheric scattering correction of multi-spectral data”. Remote Sensing of Environment, 24 (1988) 458–479.

    Article  Google Scholar 

  4. Chavez PS. “Image-Based Atmospheric Corrections-Revised and Improved”. Photogrammetric Engineering and Remote Sensing, 62(9) (1996) 1025–1036.

    Google Scholar 

  5. Crane RB. “Pre-processing techniques to reduce atmospheric and sensor variability in multi-spectral scanner data”. In: Ann Arbor (ed). Proceedings of the 7th International Symposium on Remote Sensing of Environment, University of Michigan, (1971) 1345.

  6. Crippen RE. (1987) “The regression intersection method of adjusting image data for band rationing”. International Journal of Remote Sensing, 8(2) (1987) 137–155.

    Article  Google Scholar 

  7. Electro Optical Industries, Inc., (2000). http://www.electro_optical.com

  8. Hadjimitsis DG. “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 (1999).

    Google Scholar 

  9. Mather PM. “Computer Processing of Remotely-Sensed Images”. Wiley J (1999) 75–87

  10. Micklin PP. “Introductory remarks on the Aral issue”. In: Micklin PP and Williams WD (ed). The Aral Sea Basin, NATO ASI Series, Partnership Sub-Series, 2. Environment, Springer-Verlag, Berlin, 12 (1996) 3–8.

    Chapter  Google Scholar 

  11. Milton EJ. “A portable multiband radiometer for ground data collection in remote sensing”. International Journal on Remote Sensing, 1 (1980) 153–165.

    Article  Google Scholar 

  12. Razakov RM. and Kosnazarov KA. “Dust and salt transfer from the exposed bed of the Aral Sea and measures to decrease its environmental impact”. In: Micklin PP and Williams WD (ed). The Aral Sea Basin, NATO ASI Series, Partnership Sub-Series, 2. Environment, Springer-Verlag, Berlin, 12 (1996) 95–102.

    Chapter  Google Scholar 

  13. Ressl R. http://www.dfd.dlr.de/app/land/aralsee/chronology.html, The Aral Sea Homepage, (1996).

  14. Schowegert RA. (ed). “Techniques for image processing and classification in remote sensing”. Orlando London: Academic Press (1983).

    Google Scholar 

  15. Schweizer D. “Earth’s Radiation Budget (Transfer of Radiation through Atmosphere, Shortwave)”, (1999). http://www.crseo.ucsb.edu/esrg/dianesdir/lectures/earthradbudget/sl026.htm

  16. Tanton T. Personal Communication, Department of Civil and Environmental Engineering. University of Southampton, UK, (2001).

    Google Scholar 

  17. The Remote Sensing Society, Window on the world CD-Rom, (2000).

  18. Tsytsenko KV. and Sumarokova VV. “Change of rivers’ flow in the Aral Sea basin (in connection with the problem of quantitative assessment and consideration of environmental after-effects)”. In Glantz M. (ed). Creeping Environmental Problems and Sustainable Development in the Aral Sea Basin, (1998) 191–203.

  19. US Geological Survey. Provided “quick-look” images, (2001).

  20. Willardson LS. “Conjunctive water management for the Aral Sea Basin”. In Bos M.G. (ED). The Inter-Relationship Between Irrigation, Drainage and the Environment in the Aral Sea Basin, NATO ASI Series, (Kluwer Academic Publishers, Netherlands), (1996) 143–152.

    Chapter  Google Scholar 

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Perdikou, P.N., Clayton, C.R.I. & Hadjimitsis, D.G. Impact of Atmospheric Correction on Land-use Classification and Water Demand for the Aral Sea Basin. OPSEARCH 38, 550–566 (2001). https://doi.org/10.1007/BF03398659

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