Abstract

Satellite remote sensing is a valuable tool for coastal management, enabling the possibility to repeatedly observe nearshore sandbars. However, a lack of methodological approaches for sandbar detection prevents the wider use of satellite data in sandbar studies. In this paper, a novel fully automated approach to extract nearshore sandbars in high–medium-resolution satellite imagery using a GIS-based algorithm is proposed. The method is composed of a multi-step workflow providing a wide range of data with morphological nearshore characteristics, which include nearshore local relief, extracted sandbars, their crests and shoreline. The proposed processing chain involves a combination of spectral indices, ISODATA unsupervised classification, multi-scale Relative Bathymetric Position Index (RBPI), criteria-based selection operations, spatial statistics and filtering. The algorithm has been tested with 145 dates of PlanetScope and RapidEye imagery using a case study of the complex multiple sandbar system on the Curonian Spit coast, Baltic Sea. The comparison of results against 4 years of in situ bathymetric surveys shows a strong agreement between measured and derived sandbar crest positions (R2 = 0.999 and 0.997) with an average RMSE of 5.8 and 7 m for PlanetScope and RapidEye sensors, respectively. The accuracy of the proposed approach implies its feasibility to study inter-annual and seasonal sandbar behaviour and short-term changes related to high-impact events. Algorithm-provided outputs enable the possibility to evaluate a range of sandbar characteristics such as distance from shoreline, length, width, count or shape at a relevant spatiotemporal scale. The design of the method determines its compatibility with most sandbar morphologies and suitability to other sandy nearshores. Tests of the described technique with Sentinel-2 MSI and Landsat-8 OLI data show that it can be applied to publicly available medium resolution satellite imagery of other sensors.

Highlights

  • Nearshore sandbars are elongated sandy ridges acting as natural barriers that safeguard subaerial beaches in many coastal environments [1,2]

  • The proposed method has been tested with 42 RapidEye and 103 PlanetScope images proposed method has been testedand with

  • As research of nearshore sandbars is often limited by the data availability [61], the present study intends to develop an algorithm suitable to gather this data from satellite imagery using Geographic Information System (GIS) techniques

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Summary

Introduction

Nearshore sandbars are elongated sandy ridges acting as natural barriers that safeguard subaerial beaches in many coastal environments [1,2]. These morphological features are deposited by waves and nearshore currents; they form in shallow waters up to 10 m depth along a wide range of environmental settings, from non-tidal to macrotidal regimes [1,3,4,5]. Sedimentary and morphological connections exist between the evolution of subaerial coast and nearshore sandbars [13,14]. Because of such links and the complexity

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