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Using remote sensing techniques to interpret geomorphological features along the east coast of the Red Sea, at Yanbu, Saudi Arabia

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Abstract

Yanbu is the second largest port and population settlement on the Saudi Arabian Red Sea coast. With the increasing development of its nearby coast, the geomorphological characteristics of the region must be studied in detail in order to inform future developments of the region. This study examines the region’s suitability for future development. A high-resolution map of the coastal area under study was drawn by analysing Shuttle Radar Topography Mission-Digital Elevation Model (SRTM-DEM) data and Advanced Spaceborne Thermal Emission and Reflection Radiometer-Digital Elevation Model (ASTER-DEM) data, using remote sensing images from Landsat satellites. Landsat ETM+ images taken in 2000 and 2015, alongside remote sensing analyses, field observations, and geological mapping, were used to describe the geomorphological and topographical characteristics of the Yanbu coast. Both principal component analysis (PCA) and false colour composite (FCC) were the most effective remote sensing techniques for mapping the geomorphological characteristics of the coastal plain. The true colour of the combination bands 3, 2, and 1 was the best at showing the areas and features of coral reefs. Thus, the main geomorphological units in the study area were identified, including wadi systems, dunes, alluvial fans and fan deltas, fluvial terraces, sabkhas, coral reefs, platform reefs, islands, sharms, and sea heads.

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Acknowledgements

This research has been sponsored by a grant from Taibah University, Department of Geology and Geography, Yanbu Branch. The study has been carried out under a supported research project No. 7035, 2015 (08/02/1436).

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Correspondence to Iyad Ahmed Abboud.

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Responsible Editor: Biswajeet Pradhan

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Abboud, I.A., Nofal, R.A.E. Using remote sensing techniques to interpret geomorphological features along the east coast of the Red Sea, at Yanbu, Saudi Arabia. Arab J Geosci 13, 652 (2020). https://doi.org/10.1007/s12517-020-05635-w

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