Preprints
https://doi.org/10.5194/essd-2024-123
https://doi.org/10.5194/essd-2024-123
14 May 2024
 | 14 May 2024
Status: this preprint is currently under review for the journal ESSD.

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

Abstract. Continuous monitoring of shoreline dynamics is essential to understanding the drivers of shoreline changes and evolution. A long-term shoreline dataset can describe the dynamic changes in the spatio-temporal dimension and provide information on the influence of anthropogenic activities and natural factors on coastal areas. This study, conducted on the Google Earth Engine platform, analyzed the spatio-temporal evolution characteristics of China’s shorelines, including those of Hainan and Taiwan, from 1990 to 2019 using long time series of Landsat TM/ETM+/OLI images. First, we constructed a time series of the Modified Normalized Difference Water Index (MNDWI) with high-quality reconstruction by the harmonic analysis of time series (HANTS) algorithm. Second, the Otsu algorithm was used to separate land and water of coastal areas based on MNDWI value at high tide levels. Finally, a 30-year shoreline dataset was generated and a shoreline change analysis was conducted to characterize length change, area change, and rate of change. We concluded the following: (1) China’s shoreline has shown an increasing trend in the past 30 years, with varying growth patterns across regions; the total shoreline length increased from 24905.55 km in 1990 to 25391.34 km in 2019, with a total increase greater than 485.78 km, a rate of increase of 1.95 %, and an average annual increasing rate of 0.07 %; (3) the most visible expansion has taken place in Tianjin, Hangzhou Bay, and Zhuhai for the three economically developed regions of the Bohai Bay-Yellow River Estuary Zone (BHBYREZ), the Yangtze River Estuary-Hangzhou Bay Zone (YRE-HZBZ) and the Pearl River Estuary Zone (PREZ), respectively. The statistics of shoreline change rate for the three economically developed regions show that the average end point rates (EPR) were 43.59 m/a, 39.10 m/a, and 13.42 m/a, and the average linear regression rates (LRR) were 57.40 m/a, 43.85 m/a, and 10.11 m/a, respectively. This study presents an innovative and up-to-date dataset and comprehensive information on the status of China’s shoreline from 1990 to 2019, contributing to related research and policy implementation, especially in support of sustainable development.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Gang Yang, Ke Huang, Lin Zhu, Weiwei Sun, Chao Chen, Xiangchao Meng, Lihua Wang, and Yong Ge

Status: open (until 04 Jul 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Gang Yang, Ke Huang, Lin Zhu, Weiwei Sun, Chao Chen, Xiangchao Meng, Lihua Wang, and Yong Ge
Gang Yang, Ke Huang, Lin Zhu, Weiwei Sun, Chao Chen, Xiangchao Meng, Lihua Wang, and Yong Ge

Viewed

Total article views: 198 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
149 38 11 198 11 9 9
  • HTML: 149
  • PDF: 38
  • XML: 11
  • Total: 198
  • Supplement: 11
  • BibTeX: 9
  • EndNote: 9
Views and downloads (calculated since 14 May 2024)
Cumulative views and downloads (calculated since 14 May 2024)

Viewed (geographical distribution)

Total article views: 195 (including HTML, PDF, and XML) Thereof 195 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 31 May 2024
Download
Short summary
Continuous monitoring of shoreline dynamics is critical to understanding the drivers of shoreline change and evolution. This study uses long-term sequences of Landsat TM/ETM+/OLI images to analyze the spatiotemporal evolution characteristics of the coastlines of China's Hainan, Taiwan and other countries from 1990 to 2019.
Altmetrics