Abstract

This paper presents a semi-automated approach to detecting coastal shoreline change with high spatial- and temporal-resolution using X-band synthetic aperture radar (SAR) data. The method was applied at the Sand Motor, a “mega-scale” beach nourishment project in the Netherlands. Natural processes, like waves, wind, and tides, gradually distribute the highly concentrated sand to adjacent beaches. Currently, various in-situ techniques are used to monitor the Sand Motor on a monthly basis. Meanwhile, the TerraSAR-X satellite collects two high-resolution (3 × 3 m), cloud-penetrating SAR images every 11 days. This study investigates whether shorelines detected in TerraSAR-X imagery are accurate enough to monitor the shoreline dynamics of a project like the Sand Motor. The study proposes and implements a semi-automated workflow to extract shorelines from all 182 available TerraSAR-X images acquired between 2011 and 2014. The shorelines are validated using bi-monthly RTK-GPS topographic surveys and nearby wave and tide measurements. A valid shoreline could be extracted from 54% of the images. The horizontal accuracy of these shorelines is approximately 50 m, which is sufficient to assess the larger scale shoreline dynamics of the Sand Motor. The accuracy is affected strongly by sea state and partly by acquisition geometry. We conclude that using frequent, high-resolution TerraSAR-X imagery is a valid option for assessing coastal dynamics on the order of tens of meters at approximately monthly intervals.

Highlights

  • As climate change and coastal development increase the risks associated with coastal hazards, like erosion and flooding, coastal communities are taking steps to adapt and improve their resilience.The suite of tools to address coastal hazards is broadening

  • This study proposes an efficient, semi-automated, and validated method to extract shorelines from a long time series of TerraSAR-X images to monitor the evolution of a large beach nourishment project

  • The criteria for a Good, or successful, detection are that the derived shoreline does not contain large spatial discontinuities and is close to the previously derived coastline

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Summary

Introduction

As climate change and coastal development increase the risks associated with coastal hazards, like erosion and flooding, coastal communities are taking steps to adapt and improve their resilience. The suite of tools to address coastal hazards is broadening. Conventional solutions, like seawalls, are increasingly being exchanged for more flexible and less environmentally detrimental solutions, such as beach nourishments. One example of such a project, which is used as a case study in this paper, is the “Sand Motor,”. A mega-scale beach nourishment project on the Dutch coast (Section 2.1). In order to understand how beach nourishment projects like the Sand Motor are evolving and performing, frequent monitoring

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