Spatio-temporal changes in China's mainland shorelines over 30 years using Landsat time series data (1990–2019)
Gang Yang,Ke Huang,Lin Zhu,Weiwei Sun,Chao Chen,Xiangchao Meng,Lihua Wang,and Yong Ge
Gang Yang
Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, China
State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Ke Huang
Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China
Lin Zhu
Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, China
Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, China
Chao Chen
School of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou 215009, China
Xiangchao Meng
Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China
Lihua Wang
Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, China
Yong Ge
State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
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Total article views: 3,408 (including HTML, PDF, and XML)
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Total article views: 2,301 (including HTML, PDF, and XML)
Thereof 2,262 with geography defined
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Total article views: 1,107 (including HTML, PDF, and XML)
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Continuous monitoring of shoreline dynamics is critical to understanding the drivers of shoreline change and evolution. This study uses long-term sequences of Landsat Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Operational Land Imager (OLI) images to analyze the spatio-temporal evolution characteristics of the coastlines of Hainan, mainland China, Taiwan, and other countries from 1990 to 2019.
Continuous monitoring of shoreline dynamics is critical to understanding the drivers of...
