Abstract
Many techniques are available for detection of shorelines from multispectral satellite imagery, but the choice of a certain technique for a particular study area can be tough. Hence, for the first time in literature, an inter-comparison of the most widely used shoreline mapping techniques such as Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), Improved Band Ratio (IBR) Method, and Automatic Water Extraction Index (AWEI) has been done along four different coastal stretches of India using multitemporal Landsat data. The obtained results have been validated with the high-resolution images of Cartosat-2 (panchromatic) and multispectral images from Google Earth. Performance of the above indices has been analyzed based on the statistics, such as overall accuracy, kappa coefficient, user’s accuracy, producer’s accuracy, and the average deviation from the reference line. It is observed that the performance of NDWI and IBR techniques are dependent on the physical characteristics of the sites, and therefore, it varies from one site to another. Results indicate that unlike these two indices, the AWEI algorithm performs consistently well followed by MNDWI irrespective of the land cover types.
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Acknowledgments
The authors would like to thank the anonymous reviewers for their constructive comments. Authors sincerely thank the United States Geologic Survey and Google Earth for providing the images free of cost.
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Highlights
• Comprehensive inter-comparison of the most widely used remote sensing-based simple and robust shoreline mapping techniques
• A first of its kind inter-comparison study for shoreline mapping at various coastal stretches of India
• Automated Otsu clustering technique for NDWI and MNDWI indices to avoid subjectivity
An erratum to this article is available at http://dx.doi.org/10.1007/s10661-017-6046-8.
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Sunder, S., Ramsankaran, R. & Ramakrishnan, B. Inter-comparison of remote sensing sensing-based shoreline mapping techniques at different coastal stretches of India. Environ Monit Assess 189, 290 (2017). https://doi.org/10.1007/s10661-017-5996-1
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DOI: https://doi.org/10.1007/s10661-017-5996-1