The State of the World's Beaches

Abstract

Coastal zones constitute one of the most heavily populated and developed land zones in the world. Despite the utility and economic benefits that coasts provide, there is no reliable global-scale assessment of historical shoreline change trends. Here, via the use of freely available optical satellite images captured since 1984, in conjunction with sophisticated image interrogation and analysis methods, we present a global-scale assessment of the occurrence of sandy beaches and rates of shoreline change therein. Applying pixel-based supervised classification, we found that 31% of the world's ice-free shoreline are sandy. The application of an automated shoreline detection method to the sandy shorelines thus identified resulted in a global dataset of shoreline change rates for the 33 year period 1984-2016. Analysis of the satellite derived shoreline data indicates that 24% of the world's sandy beaches are eroding at rates exceeding 0.5 m/yr, while 28% are accreting and 48% are stable. The majority of the sandy shorelines in marine protected areas are eroding, raising cause for serious concern.

Figure 1

Global distribution of sandy shorelines; the coloured dots along the world’s shoreline represent the local percentage of sandy shorelines (yellow is sand, dark brown is non-sand). The subplot to the right presents the relative occurrence of sandy shorelines per degree latitude, where the dashed line shows the latitudinal distribution of sandy shorelines reported by Hayes. The lower subplot presents the relative occurrence of sandy shorelines per degree longitude. The curved, dashed grey lines in the main plot represent the boundaries of the ice-free shorelines considered in our analysis. The underlined percentages indicate the percentages of sandy shorelines averaged per continent. Map is created with Python 2.7.12 (https://www.python.org) using Cartopy (v0.15.1. Met Office UK. https://pypi.python.org/pypi/Cartopy/0.15.1) and Matplotlib.

Figure 2

Global hotspots of beach erosion and accretion; the red (green) circles indicate erosion (accretion) for the four relevant shoreline dynamic classifications (see legend). The bar plots to the right and at the bottom present the relative occurrence of eroding (accreting) sandy shorelines per degree latitude and longitude, respectively. The numbers presented in the main plot represent the average change rate for all sandy shorelines per continent. Map is created with Python 2.7.12 (https://www.python.org) using Cartopy (v0.15.1. Met Office UK. https://pypi.python.org/pypi/Cartopy/0.15.1) and Matplotlib.

Figure 3

Examples of the satellite derived shorelines for four selected cases of beach erosion and accretion due to human interventions. The left column presents two erosive cases while the right column shows two accretive cases. In each figure, the blue line indicates the oldest SDS shoreline while the red line is the most recent SDS shoreline. The graphs below indicate the shoreline positions over time at the white dashed transect for each case; the upper graphs correspond to the images on the upper row. The indicated change rates (m/yr) are obtained from fitting a line-of-best fit to the shoreline position data for each transect. Figure is created with Python 2.7.12 (https://www.python.org) using Matplotlib. Maps are created with QGIS version 2.18.3 (Open Source Geospatial Foundation Project, http://qgis.osgeo.org) using satellite images provided by Google Maps. Map data: Google, Terrametrics, CNES/Airbus, IGP/DGRF, and DigitalGlobe.

Figure 4

The procedure followed for deriving shoreline change trends for sandy shorelines using a global transect system. The figure is compiled using www.draw.io, while the maps in the figure are made using © Mapbox and © OpenStreetMap, available under the Open Database License (https://www.openstreetmap.org/copyright).

Figure 5

Observed trend rates (red dots) and satellite-derived trend rates of shoreline change (blue line) along Hatteras Island for the period 1989–2002. Figure is created with Python 2.7.12 (https://www.python.org).