Spatial patterns of sandy beaches in China and risk analysis of human infrastructure squeeze based on multi-source data and ensemble learning

Abstract. Sandy beaches provide essential ecological and economic services, but their functions are increasingly threatened by human activities. Analyzing the spatial distribution of China's sandy beaches and the impacts of human activities offers valuable insights for coastal resource management and ecological protection. However, remote sensing technologies face challenges such as limited data sources and tidal influences, which affect recognition accuracy. Therefore, integrating multi-source remote sensing data and reducing the impact of tidal fluctuations to improve recognition accuracy remains a key challenge. This study proposes an innovative approach utilizing multi-source data and an ensemble learning model to identify sandy beaches in China (2016–2024). By integrating Sentinel-1/2 satellite data, terrain data, and nighttime light data, along with spectral, index, terrain, texture, and polarization features, sandy beaches were identified across multiple years, and the results were consolidated into a unique dataset to analyze spatial patterns and risks from human infrastructure squeeze. (1) High-precision classification identified 3347 sandy beaches in China, covering a total area of 320.50 km2. Guangdong had the largest number, area, and perimeter, while Hebei had the widest sandy beaches. (2) In Fujian, Guangdong, and Taiwan, the identified sandy beaches covered 54.57, 78.88, and 46.60 km2, with perimeters of 1435.89, 2849.39, and 1324.98 km, and widths of 54.91, 38.92, and 57.17 m, respectively. These results were significantly better than those from published datasets. (3) From 1990 to 2024, the area at risk from human infrastructure squeeze increased from 134.39 to 181.42 km2, a rise of 47.03 km2, with the most significant increase occurring between 1995 and 2000. Guangdong and Fujian showed growth rates of 0.38 and 0.32 km2 yr−1, respectively. This study provides an up-to-date dataset on China's sandy beaches. It assesses their spatial patterns and human impact risks, contributing to research and policy for the sustainable development of coastal zones (https://doi.org/10.5281/zenodo.15307240, Meng et al., 2025).

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Publication Details

Journal
Earth system science data
Published
2025-12-12
DOI
https://doi.org/10.5194/essd-17-7147-2025
Primary Topic
Coastal and Marine Dynamics
Type
article
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article

Spatial patterns of sandy beaches in China and risk analysis of human infrastructure squeeze based on multi-source data and ensemble learning

Zexing Tao, Quansheng Ge, Duanyang Xu, Jie Meng
Earth system science data
Coastal and Marine Dynamics
article

Spatial patterns of sandy beaches in China and risk analysis of human infrastructure squeeze based on multi-source data and ensemble learning

Zexing Tao, Quansheng Ge, Duanyang Xu, Jie Meng
article en

Abstract

Abstract. Sandy beaches provide essential ecological and economic services, but their functions are increasingly threatened by human activities. Analyzing the spatial distribution of China's sandy beaches and the impacts of human activities offers valuable insights for coastal resource management and ecological protection. However, remote sensing technologies face challenges such as limited data sources and tidal influences, which affect recognition accuracy. Therefore, integrating multi-source remote sensing data and reducing the impact of tidal fluctuations to improve recognition accuracy remains a key challenge. This study proposes an innovative approach utilizing multi-source data and an ensemble learning model to identify sandy beaches in China (2016–2024). By integrating Sentinel-1/2 satellite data, terrain data, and nighttime light data, along with spectral, index, terrain, texture, and polarization features, sandy beaches were identified across multiple years, and the results were consolidated into a unique dataset to analyze spatial patterns and risks from human infrastructure squeeze. (1) High-precision classification identified 3347 sandy beaches in China, covering a total area of 320.50 km2. Guangdong had the largest number, area, and perimeter, while Hebei had the widest sandy beaches. (2) In Fujian, Guangdong, and Taiwan, the identified sandy beaches covered 54.57, 78.88, and 46.60 km2, with perimeters of 1435.89, 2849.39, and 1324.98 km, and widths of 54.91, 38.92, and 57.17 m, respectively. These results were significantly better than those from published datasets. (3) From 1990 to 2024, the area at risk from human infrastructure squeeze increased from 134.39 to 181.42 km2, a rise of 47.03 km2, with the most significant increase occurring between 1995 and 2000. Guangdong and Fujian showed growth rates of 0.38 and 0.32 km2 yr−1, respectively. This study provides an up-to-date dataset on China's sandy beaches. It assesses their spatial patterns and human impact risks, contributing to research and policy for the sustainable development of coastal zones (https://doi.org/10.5281/zenodo.15307240, Meng et al., 2025).

Earth system science dataVol. 17(12)
Chinese Academy of Sciences (CN), Institute of Geographic Sciences and Natural Resources Research (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 56%
Coastal and Marine Dynamics
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