Abstract
Image transformation techniques such as Principal Component Analysis, Minimum Noise Fraction and Independent Component Analysis were used for extracting information from the satellite image in various fields, but its application in landform mapping seems to be very less. The objective of the study is to demonstrate the viability of less explored image transformation techniques for delineating coastal dune complex and associated features using European satellite Sentinel 2 multispectral data. Based on the difference in lithology and vegetation cover the study sites has been chosen to extract coastal dune complex features such as dune ridges, dune with or without vegetation, swale with or without vegetation and water. Overall results of ICA shows enhanced visualization followed by PCA in bringing up the fine variations, identifying micro landforms within the dune complex from the optimum band combinations. Thus, sentinel data coupled with advanced image processing technique like ICA could identify maximum information about the boundaries and micro landform within the coastal sand dune complex in a cost-effective manner. However, in areas with dense vegetation cover none of these techniques has given good results in identifying the boundary or in identifying the micro landforms.
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Acknowledgements
The authors acknowledge Department of Science and Technology-Science and Engineering Research Board (DST-SERB) for the financial support given to do the project work (EMR/2016/007891) and the ESA Copernicus for providing satellite data.
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Durai, P., Radhakrishnan, N.P., Sarunjith, K.J. et al. Evaluation of various image transformation techniques for the delineation of coastal sand dune features in Tamil Nadu, South India. Earth Sci Inform 14, 883–892 (2021). https://doi.org/10.1007/s12145-021-00588-4
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DOI: https://doi.org/10.1007/s12145-021-00588-4