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A Simple, Fully Automated Shoreline Detection Algorithm for High-Resolution Multi-Spectral Imagery by Hazem Usama Abdelhady; Cary David Troy; Ayman Habib; Raja Manish is a Environmental Science article available to read on EtoBox.

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This paper develops and validates a new fully automated procedure for shoreline delineation from high-resolution multispectral satellite images. The model is based on a new water–land index, the Direct Difference Water Index (DDWI). A new technique based on the buffer overlay method is also presented to determine the shoreline changes from different satellite images and obtain a time series for the shoreline changes. The shoreline detection model was applied to imagery from multiple satellites and validated to have sub-pixel accuracy using beach survey data that were collected from the Lake Michigan (USA) shoreline using a novel backpack-based LiDAR system. The model was also applied to 132 satellite images of a Lake Michigan beach over a three-year period and detected the shoreline accurately, with a >99% success rate. The model out-performed other existing shoreline detection algorithms based on different water indices and clustering techniques. The resolution shoreline position timeseries is the first satellite image-extracted dataset of its kind in terms of its high spatial and temporal resolution, and paves the road to obtaining other high-temporal-resolution datasets to refin

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Author

Hazem Usama Abdelhady; Cary David Troy; Ayman Habib; Raja Manish

Publisher

MDPI AG

Published

2022

Language

EN

Field

Environmental Science (Physical Sciences)