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Abstract
Water depth estimation using optical remote sensing offers a reliable and efficient means of mapping coastal zones. Here, we aim to find a suitable model for fast and practical bathymetry of an estuary using Indian Remote Sensing Satellite (IRS) Linear Imaging Self Scanning Sensor (LISS-3) images. The study examines three different models; (1) least square regression model, (2) spectral band-ratio method and (3) multi-tidal bathymetry model. The findings are supported with in situ observed depth values and statistical estimates. Although the least square regression model has provided best results with root mean square error (RMSE) of 0.4 m, it requires a large number of observed data points for absolute depth estimation. Spectral band-ratio and multi-tidal model provides results with RMSEs 2.1 and 0.9 m, respectively. The present investigation demonstrates that multi-date imagery exploitation at disparate tide levels is the best estimation technique for recursive shallow water bathymetry where in situ observation is not possible.
Acknowledgements
The field work was supported by Project MAGIC (Coastal Morphodynamics and Geo-environmental Studies of Gahirmatha Coast) team of Defence Terrain Research Laboratory (DTRL), India. The authors would like to thank Dr MR Bhutiyani, Director DTRL for his continued encouragement during the investigation and permission to publish. We are immensely grateful to the Editors Dr. Rundquist and Dr. Lulla for their constructive review. We are also thankful to two anonymous reviewers for their helpful suggestions which greatly improved the quality of the paper.