Spatio-temporal changes in China's mainland shorelines over 30 years using Landsat time series data (1990–2019)

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 (GEE) platform, analyzed the spatio-temporal evolution characteristics of China's shorelines, including those of Hainan and Taiwan, from 1990 to 2019 using a long time series of Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Operational Land Imager (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 the 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 24 905.55 km in 1990 to 25 391.34 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 %. (2) 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 (BHB-YREZ), the Yangtze River estuary–Hangzhou Bay zone (YRE-HZBZ), and the Pearl River estuary zone (PREZ), respectively. (3) The statistics of shoreline change rate for the three economically developed regions show that the average end point rates (EPRs) were 43.59, 39.10, and 13.42 m yr−1, and the average linear regression rates (LRRs) were 57.40, 43.85, and 10.11 m yr−1, 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 (https://doi.org/10.57760/sciencedb.16228, Yang et al., 2024).

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Publication Details

Journal
Earth system science data
Published
2024-11-20
DOI
https://doi.org/10.5194/essd-16-5311-2024
Citations
9
Primary Topic
Coastal wetland ecosystem dynamics
Type
article
Field-Weighted Citation Impact
4.13

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article

Spatio-temporal changes in China's mainland shorelines over 30 years using Landsat time series data (1990–2019)

Xiangchao Meng, Ke Huang, Weiwei Sun, Gang Yang et al.
9 citations
Earth system science data
Coastal wetland ecosystem dynamics
4.13
article

Spatio-temporal changes in China's mainland shorelines over 30 years using Landsat time series data (1990–2019)

Xiangchao Meng, Ke Huang, Weiwei Sun, Gang Yang, Lihua Wang, Chao Chen, Lin Zhu, Yong Ge
article en
9 citations

Abstract

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 (GEE) platform, analyzed the spatio-temporal evolution characteristics of China's shorelines, including those of Hainan and Taiwan, from 1990 to 2019 using a long time series of Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Operational Land Imager (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 the 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 24 905.55 km in 1990 to 25 391.34 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 %. (2) 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 (BHB-YREZ), the Yangtze River estuary–Hangzhou Bay zone (YRE-HZBZ), and the Pearl River estuary zone (PREZ), respectively. (3) The statistics of shoreline change rate for the three economically developed regions show that the average end point rates (EPRs) were 43.59, 39.10, and 13.42 m yr−1, and the average linear regression rates (LRRs) were 57.40, 43.85, and 10.11 m yr−1, 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 (https://doi.org/10.57760/sciencedb.16228, Yang et al., 2024).

Earth system science dataVol. 16(11)
Ningbo University (CN), Chinese Academy of Sciences (CN), Suzhou University of Science and Technology (CN), Institute of Geographic Sciences and Natural Resources Research (CN)
National Natural Science Foundation of China, Science and Technology Innovation 2025 Major Project of Ningbo
Life below water
Openalex Percentile: Top 6%
Coastal wetland ecosystem dynamics
4.13
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