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Analysis and Prediction of Changes in Coastline Morphology in the Bohai Sea, China, Using Remote Sensing

1
School of Geology and Geomatics, Tianjin Chengjian University, Jinjing Road, Tianjin 300384, China
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College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
*
Author to whom correspondence should be addressed.
Academic Editor: Vincenzo Torretta
Sustainability 2017, 9(6), 900; https://doi.org/10.3390/su9060900
Received: 1 April 2017 / Revised: 22 May 2017 / Accepted: 22 May 2017 / Published: 29 May 2017
Coastline change reflects the dynamics of natural processes and human activity, and influences the ecology and environment of the coastal strip. This study researched the change in coastline and sea area of the Bohai Sea, China, over a 30-year period using Landsat TM and OLI remote sensing data. The total change in coastline length, sea area, and the centroid of the sea surface were quantified. Variations in the coastline morphology were measured using four shape indexes: fractal dimension, compact ratio, circularity, and square degree. Equations describing fit of the shape index, coastline length, and marine area were built. Then the marine area 10 years later was predicted using the model that had the highest prediction accuracy. The results showed that the highest prediction accuracy for the coastline length was obtained using a compound function. When a cubic function was used to predict the compact ratio, then the highest prediction accuracy was obtained using this compact ratio and a quadratic function to predict sea area. This study can provide theoretical support for the coastal development planning and ecological environment protection around the Bohai Sea. View Full-Text
Keywords: coastline change; shape index; fitting; prediction coastline change; shape index; fitting; prediction
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MDPI and ACS Style

Fu, Y.; Guo, Q.; Wu, X.; Fang, H.; Pan, Y. Analysis and Prediction of Changes in Coastline Morphology in the Bohai Sea, China, Using Remote Sensing. Sustainability 2017, 9, 900.

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