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(Impact of tourism in coastal areas: Need of sustainable tourism strategy)
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==Impact of tourism in coastal areas: Need of sustainable tourism strategy==
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==Bathymetry from inverse wave refraction==
  
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[[Image:tourism_fig2.jpg|thumb|350px|right|Tourists sunbathing on a beach used by loggerhead turtles (Caretta caretta) for Nnesting, some with beach umbrellas which can hurt turtle nests. Zákinthos, Greece. © WWF-Canon / Michel GUNTHER]]
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[[Image:01_echosoundings_enc.jpg|thumb|350px|right|Bathymetry of area of investigation acquired by multibeam echosounder.]]
  
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Since the 1992 Earth Summit in Rio de Janeiro, there is increasing awareness of the importance of sustainable forms of tourism. Although tourism, one of the world largest industries, was not the subject of a chapter in Agenda 21, the Programme for the further implementation of Agenda 21, adopted by the General Assembly at its nineteenth special session in 1997, included sustainable tourism as one of its sectoral themes. Furthermore in 1996, The World Tourism Organization jointly with the tourism private sector issued an Agenda 21 for the Travel and Tourism Industry, with 19 specific areas of action recommended to governments and private operators towards sustainability in tourism.
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The determination of the [[bathymetry]] in coastal environments by utilizing the ocean wave-shoaling photographic imagery, and the observed reduction of ocean wave phase speed with decreased water depth, is used since the WW-II (Williams 1946)<ref>Williams, W.W. 1946, The determination of gradients of enemy-held beaches. Geographical Journal 107, 76–93.</ref>. The last decade, with the expansion of different ground based instrumentations, mainly radar and video imagery, for the observation of the sea surface and the exponential increase of the computational power, several methodologies for the [[bathymetry]] reckoning have been published, e.g. Bell 1999<ref> P. Bell 1999, Shallow water bathymetry derived from an analysis of x-band radar images of waves, Coastal Engineering 3-4, pp. 513-527.</ref>, Seemann et al. 1999<ref>Seemann J., C. Senet, H. Dankert, Hatten, H., Ziemer, F. 1999, Radar image sequence analysis of inhomogeneous water surfaces, in proc. of the SPIE'99 Conference - Applications of Digital Image Processing XXII. vol. 3808, pp. 536-546.</ref>, Stockdon and Holman 2000<ref>Stockdon, H.F., Holman, R.A. 2000, Estimation of wave phase speed and nearshore bathymetry from video imagery. Journal of Geophysical Research 105 (C9), pp. 22015–22033.</ref>, Dankert 2003<ref>Dankert, H. 2003, Retrieval of Surface-Current Fields and Bathymetries using Radar-Image Se-quences, International Geoscience and Remote Sensing Symposium, Toulouse, France.</ref>, Bell et al. 2004<ref name="bell">Bell, P., J. Williams, S. Clark, B. Morris and A. Vila-Concejo 2004, Nested Radar Systems for Remote Coastal Observations, Journal of Coastal Research SI39, pp. 483-487.</ref>, Catalan and Haller 2008<ref>Catalan, P.A. and Haller, M.C., 2008, Remote sensing of breaking wave phase speeds with ap-plication to non-linear depth inversions. Coastal Engineering, 55(1), pp. 93-111.</ref>, Senet et al. 2008<ref name="sen">Senet, C. M., J. Seemann, S. Flampouris, F. Ziemer 2008, Determination of Bathymetric and Current Maps by the Method DiSC Based on the Analysis of Nautical X–Band Radar-Image Se-quences of the Sea Surface, IEEE Transaction on Geoscience and Remote Sensing 46(7), pp.1-9.</ref>. The core of the previously mentioned methods is the inversion of the wave characteristics by assuming the validity of linear or non-linear models for the propagation of the wavefield over uneven sea bottom.
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In the present investigation, twelve hourly radar datasets acquired during storm conditions are analyzed by two methods: The non-linear method of Bell et al. 2004<ref name="bell"/> (henceforth BW04), which is based on the inversion of the non-linear [[Dispersion (waves)|wave dispersion]] equation of Hedges (1976)<ref>Hedges, T.S. 1976, An empirical modification to linear wave theory, Proc. Inst. Civ. Eng., 61, pp. 575-579.</ref> and the Dispersive Surface Classificator (henceforth DiSC08), Senet et al. 2008<ref name="sen"/>, which is based on the inversion of the linear wave theory. The results are validated as bathymetric retrieving instruments and the two wave propagation theories are compared about their sensitivity to the local bathymetric relief. The two methods are compared under the assumption of fundamentally similar implemented algorithms.

Revision as of 00:19, 8 December 2008

Bathymetry from inverse wave refraction

Bathymetry of area of investigation acquired by multibeam echosounder.

The determination of the bathymetry in coastal environments by utilizing the ocean wave-shoaling photographic imagery, and the observed reduction of ocean wave phase speed with decreased water depth, is used since the WW-II (Williams 1946)[1]. The last decade, with the expansion of different ground based instrumentations, mainly radar and video imagery, for the observation of the sea surface and the exponential increase of the computational power, several methodologies for the bathymetry reckoning have been published, e.g. Bell 1999[2], Seemann et al. 1999[3], Stockdon and Holman 2000[4], Dankert 2003[5], Bell et al. 2004[6], Catalan and Haller 2008[7], Senet et al. 2008[8]. The core of the previously mentioned methods is the inversion of the wave characteristics by assuming the validity of linear or non-linear models for the propagation of the wavefield over uneven sea bottom.

In the present investigation, twelve hourly radar datasets acquired during storm conditions are analyzed by two methods: The non-linear method of Bell et al. 2004[6] (henceforth BW04), which is based on the inversion of the non-linear wave dispersion equation of Hedges (1976)[9] and the Dispersive Surface Classificator (henceforth DiSC08), Senet et al. 2008[8], which is based on the inversion of the linear wave theory. The results are validated as bathymetric retrieving instruments and the two wave propagation theories are compared about their sensitivity to the local bathymetric relief. The two methods are compared under the assumption of fundamentally similar implemented algorithms.
  1. ↑ Williams, W.W. 1946, The determination of gradients of enemy-held beaches. Geographical Journal 107, 76–93.
  2. ↑ P. Bell 1999, Shallow water bathymetry derived from an analysis of x-band radar images of waves, Coastal Engineering 3-4, pp. 513-527.
  3. ↑ Seemann J., C. Senet, H. Dankert, Hatten, H., Ziemer, F. 1999, Radar image sequence analysis of inhomogeneous water surfaces, in proc. of the SPIE'99 Conference - Applications of Digital Image Processing XXII. vol. 3808, pp. 536-546.
  4. ↑ Stockdon, H.F., Holman, R.A. 2000, Estimation of wave phase speed and nearshore bathymetry from video imagery. Journal of Geophysical Research 105 (C9), pp. 22015–22033.
  5. ↑ Dankert, H. 2003, Retrieval of Surface-Current Fields and Bathymetries using Radar-Image Se-quences, International Geoscience and Remote Sensing Symposium, Toulouse, France.
  6. ↑ 6.0 6.1 Bell, P., J. Williams, S. Clark, B. Morris and A. Vila-Concejo 2004, Nested Radar Systems for Remote Coastal Observations, Journal of Coastal Research SI39, pp. 483-487.
  7. ↑ Catalan, P.A. and Haller, M.C., 2008, Remote sensing of breaking wave phase speeds with ap-plication to non-linear depth inversions. Coastal Engineering, 55(1), pp. 93-111.
  8. ↑ 8.0 8.1 Senet, C. M., J. Seemann, S. Flampouris, F. Ziemer 2008, Determination of Bathymetric and Current Maps by the Method DiSC Based on the Analysis of Nautical X–Band Radar-Image Se-quences of the Sea Surface, IEEE Transaction on Geoscience and Remote Sensing 46(7), pp.1-9.
  9. ↑ Hedges, T.S. 1976, An empirical modification to linear wave theory, Proc. Inst. Civ. Eng., 61, pp. 575-579.
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