Coastline Monitoring and Prediction Based on Long-Term Remote Sensing Data-A Case Study of the Eastern Coast of Laizhou Bay, China
Mu, Ke1,2,3; Tang, Cheng1,2; Tosi, Luigi4; Li, Yanfang1,2; Zheng, Xiangyang1,2; Donnici, Sandra4; Sun, Jixiang1,2,3; Liu, Jun5; Gao, Xuelu1,2
Source PublicationREMOTE SENSING
Keywordspatiotemporal changes coastal erosion shoreline extraction DSAS Google Earth Engine Laizhou Bay
Corresponding AuthorTang, Cheng(
AbstractMonitoring shoreline movements is essential for understanding the impact of anthropogenic activities and climate change on the coastal zone dynamics. The use of remote sensing allows for large-scale spatial and temporal studies to better comprehend current trends. This study used Landsat 5 (TM), Landsat 8 (OLI), and Sentinel-2 (MSI) remote sensing images, together with the Otsu algorithm, marching squares algorithm, and tidal correction algorithm, to extract and correct the coastline positions of the east coast of Laizhou Bay in China from 1984 to 2022. The results indicate that 89.63% of the extracted shoreline segments have an error less than 30 m compared to the manually drawn coastline. The total length of the coastline increased from 166.90 km to 364.20 km, throughout the observation period, with a length change intensity (LCI) of 3.11% due to the development of coastal protection and engineering structures for human activities. The anthropization led to a decrease in the natural coastline from 83.33% to 13.89% and a continuous increase in the diversity and human use of the coastline. In particular, the index of coastline diversity (ICTD) and the index of coastline utilization degree (ICUD) increased from 0.39 to 0.79, and from 153.30 to 390.37, respectively. Over 70% of the sandy beaches experienced erosional processes. The shoreline erosion calculated using the end point rate (EPR) and the linear regression rate (LRR) is 79.54% and 85.58%, respectively. The fractal dimension of the coastline shows an increasing trend and is positively correlated with human activities. Coastline changes are primarily attributed to interventions such as land reclamation, aquaculture development, and port construction resulting in the creation of 10,000.20 hectares of new coastal areas. Finally, the use of Kalman filtering for the first time made it possible to predict that approximately 84.58% of the sandy coastline will be eroded to varying degrees by 2032. The research results can provide valuable reference for the scientific planning and rational utilization of resources on the eastern coast of Laizhou Bay.
Funding OrganizationNational Natural Science Foundation of China ; National Research Council of Italy ; Chinese Academy of Sciences, Project Coastal system changes over the Anthropocene: Natural vs Induced drivers
Indexed BySCI
WOS Research AreaEnvironmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:001140714100001
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Document Type期刊论文
Corresponding AuthorTang, Cheng
Affiliation1.Chinese Acad Sci, Yantai Inst Coastal Zone Res, CAS Key Lab Coastal Environm Proc & Ecol Remediat, Yantai 264003, Peoples R China
2.Shandong Key Lab Coastal Environm Proc, Yantai 264003, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.CNR, Inst Geosci & Earth Resources, I-35131 Padua, Italy
5.China Geol Survey, Yantai Ctr Coastal Zone Geol Survey, Yantai 264001, Peoples R China
Recommended Citation
GB/T 7714
Mu, Ke,Tang, Cheng,Tosi, Luigi,et al. Coastline Monitoring and Prediction Based on Long-Term Remote Sensing Data-A Case Study of the Eastern Coast of Laizhou Bay, China[J]. REMOTE SENSING,2024,16(1):21.
APA Mu, Ke.,Tang, Cheng.,Tosi, Luigi.,Li, Yanfang.,Zheng, Xiangyang.,...&Gao, Xuelu.(2024).Coastline Monitoring and Prediction Based on Long-Term Remote Sensing Data-A Case Study of the Eastern Coast of Laizhou Bay, China.REMOTE SENSING,16(1),21.
MLA Mu, Ke,et al."Coastline Monitoring and Prediction Based on Long-Term Remote Sensing Data-A Case Study of the Eastern Coast of Laizhou Bay, China".REMOTE SENSING 16.1(2024):21.
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