Spatial patterns of sandy beaches in China and risk analysis of human infrastructure squeeze based on multi-source data and ensemble learning
文献类型：期刊论文
| 作者 | Meng, Jie1,2; Xu, Duanyang2; Tao, Zexing2; Ge, Quansheng2 |
| 刊名 | EARTH SYSTEM SCIENCE DATA
 |
| 出版日期 | 2025-12-12 |
| 卷号 | 17期号:12页码:7147-7167 |
| ISSN号 | 1866-3508 |
| DOI | 10.5194/essd-17-7147-2025 |
| 产权排序 | 1 |
| 文献子类 | Article ; Data Paper |
| 英文摘要 | 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 km2yr-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 (10.5281/zenodo.15307240, Meng et al., 2025). |
| URL标识 | 查看原文 |
| WOS关键词 | CLIMATE-CHANGE ; COASTAL ; COASTLINE ; IMAGES ; SEGMENTATION ; EXTRACTION ; EVOLUTION ; IMPACTS |
| WOS研究方向 | Geology ; Meteorology & Atmospheric Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:001636587000001 |
| 出版者 | COPERNICUS GESELLSCHAFT MBH |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/219445]  |
| 专题 | 陆地表层格局与模拟院重点实验室_外文论文 |
| 通讯作者 | Xu, Duanyang |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Meng, Jie,Xu, Duanyang,Tao, Zexing,et al. Spatial patterns of sandy beaches in China and risk analysis of human infrastructure squeeze based on multi-source data and ensemble learning[J]. EARTH SYSTEM SCIENCE DATA,2025,17(12):7147-7167. |
| APA | Meng, Jie,Xu, Duanyang,Tao, Zexing,&Ge, Quansheng.(2025).Spatial patterns of sandy beaches in China and risk analysis of human infrastructure squeeze based on multi-source data and ensemble learning.EARTH SYSTEM SCIENCE DATA,17(12),7147-7167. |
| MLA | Meng, Jie,et al."Spatial patterns of sandy beaches in China and risk analysis of human infrastructure squeeze based on multi-source data and ensemble learning".EARTH SYSTEM SCIENCE DATA 17.12(2025):7147-7167. |
入库方式： OAI收割
来源：地理科学与资源研究所
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