Traditional vs. Machine-Learning Methods for Forecasting Sandy Shoreline Evolution Using Historic Satellite-Derived Shorelines

Traditional vs. Machine-Learning Methods for Forecasting Sandy Shoreline Evolution Using Historic Satellite-Derived Shorelines

Forecasting shoreline evolution for sandy coasts is important for sustainable coastal management, given the present-day increasing anthropogenic pressures and a changing future climate. Here, we evaluate eight different time-series forecasting methods for predicting future shorelines derived from hi...

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Bibliographic Details
Main Authors: Floris Calkoen, Arjen Luijendijk, Cristian Rodriguez Rivero, Etienne Kras, Fedor Baart
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Remote Sensing
Subjects:
forecasting shorelines
shoreline-trajectories
sandy beaches
coastal engineering
coastal oceanography
time-series forecasting
Online Access:https://www.mdpi.com/2072-4292/13/5/934

Internet

https://www.mdpi.com/2072-4292/13/5/934

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