Skip to content
BY-NC-ND 3.0 license Open Access Published by De Gruyter Open Access March 1, 2009

Determination of the separability of coastal community assemblages of the Al Wajh Barrier Reef, Red Sea, from hyperspectral data

Sarah Hamylton
From the journal Open Geosciences

Abstract

Remote sensing provides a practical means by which coral reefs and their associated communities are commonly mapped. The availability of spectral information is a key determinant of the detail discernable in the mapping process and consequent detail presented in output maps. Testament to this is the increasing utility of hyperspectral sensors, which typically yield datasets of higher resolution, spectrally continuous wavebands. Image classification algorithms distinguish between the different and unique reflectance characteristics of target features. While the availability of more wavebands provides the opportunity to apply analysis techniques that treat the data as spectrally continuous, such a large number of data dimensions also present a considerable computing burden. Through multiple discriminant function analysis, this paper identifies an optimal subset of wavelengths for resolving the reflectance of key terrestrial and marine coverages at the Al Wajh Barrier reef system, Saudi Arabia, Red Sea. The goal of such analysis is to facilitate the processing of high resolution, spectrally continuous remote sensing data of coastal landscapes.

[1] Green E.P., Mumby P.J., Edwards A.J., Clark C.D., Remote Sensing Handbook for Tropical Coastal Management, UNESCO Publishing, 2000 Search in Google Scholar

[2] Mather P.M., Computer Processing of Remotely Sensed Images: An Introduction, Third Edition, John Wiley & Sons, New York, 2004 Search in Google Scholar

[3] Kerekes J.P., Schott J.R. Hyperspectral Imaging Systems. In: Chang C. (Ed), Hyperspectral Data Exploitation: Theory and Applications, Wiley-Interscience, 2007 Search in Google Scholar

[4] Mumby P., Skirving W., Strong A.E., Hardy J.T., LeDrew E.F., Hochberg E. et al., Remote sensing of coral reefs and their physical environment, Mar. Pollution Bull. 2004, 48, 219–228 http://dx.doi.org/10.1016/j.marpolbul.2003.10.03110.1016/j.marpolbul.2003.10.031Search in Google Scholar

[5] Hochberg E.J., Atkinson M.J., Spectral Discrimination of coral reef benthic communities, Coral Reefs, 2000, 19, 164–171 http://dx.doi.org/10.1007/s00338000008710.1007/s003380000087Search in Google Scholar

[6] Hochberg E.J., Atkinson M.J., Andrefouet S., Spectral reflectance of coral reef bottom-types worldwide and implications for coral reef remote sensing, Remote Sens. Environ., 2004, 85, 159–173 http://dx.doi.org/10.1016/S0034-4257(02)00201-810.1016/S0034-4257(02)00201-8Search in Google Scholar

[7] Karpouzli A.E., Malthus T.J., Place C., Hyperspectral discrimination of coral reef benthic communities in the western Caribbean, Coral Reefs, 2004, 23, 141–151 http://dx.doi.org/10.1007/s00338-003-0363-910.1007/s00338-003-0363-9Search in Google Scholar

[8] Kutzer T., Dekker A.G., Skirving W., Modelling spectral discrimination of Great Barrier Reef benthic communities by remote sensing instruments, Limnol. Oceanogr., 2003, 3, 497–510 http://dx.doi.org/10.4319/lo.2003.48.1_part_2.049710.4319/lo.2003.48.1_part_2.0497Search in Google Scholar

[9] Tsai F., Philpot W., Derivative Analysis of Hyperspectral Data, Remote Sens. Environ., 1998, 66, 41–51 http://dx.doi.org/10.1016/S0034-4257(98)00032-710.1016/S0034-4257(98)00032-7Search in Google Scholar

[10] Klecka W. R., Discriminant Analysis, Sage Publications, Sage University Papers, 1980 10.4135/9781412983938Search in Google Scholar

[11] Rencher A.C., Methods of Multivariate Analysis, Wiley Series in Probability and Mathematical Statistics, John Wiley & Sons, New York, 1995 Search in Google Scholar

[12] Stroud K.A., Engineering Mathematics, Fourth Edition, MacMillan Press Ltd., 1995 Search in Google Scholar

[13] Mazel C.H., Coral Fluorescence Characteristics: excitation-emission spectra, fluorescence efficiencies and contribution to apparent reflectance, Proc. SPIE vol. 2963, Global Process Monitoring and Remote Sensing of the ocean and sea ice, 1996, 65–72 10.1117/12.266450Search in Google Scholar

[14] Mather P.M., Multiple Discriminant Analysis, Computer applications in the natural & social sciences, no. 6, Nottingham: Computer Applications, 1969 Search in Google Scholar

[15] Mather P.M., Computational Methods of Multivariate Analysis in Physical Geography, John Wiley & Sons, 1976 Search in Google Scholar

[16] Tukey J. The collected works of John W Tukey Vol. I. Time series: 1949–1964, Belmont, CA, 1984, 1962 Search in Google Scholar

[17] Friedman J.H., Regularized Discriminant Analysis, J. Am. Stat. Assoc., 1989, 84, 165–175 http://dx.doi.org/10.2307/228986010.2307/2289860Search in Google Scholar

[18] Lachenbruch P., Discriminant Analysis, New York, Hafner, 1975 Search in Google Scholar

Published Online: 2009-3-1
Published in Print: 2009-3-1

© 2009 Versita Warsaw

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Scroll Up Arrow