气候变化领域集成服务门户(CCPortal): Coastline Monitoring and Prediction Based on Long-Term Remote Sensing Data-A Case Study of the Eastern Coast of Laizhou Bay, China

CCPortal

DOI	10.3390/rs16010185
	Coastline Monitoring and Prediction Based on Long-Term Remote Sensing Data-A Case Study of the Eastern Coast of Laizhou Bay, China
	Mu, Ke; Tang, Cheng; Tosi, Luigi; Li, Yanfang; Zheng, Xiangyang; Donnici, Sandra; Sun, Jixiang; Liu, Jun; Gao, Xuelu
发表日期	2024
EISSN	2072-4292
起始页码	16
结束页码	1
卷号	16 期号:1
英文摘要	Monitoring 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.
英文关键词	spatiotemporal changes; coastal erosion; shoreline extraction; DSAS; Google Earth Engine; Laizhou Bay
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:001140714100001
来源期刊	REMOTE SENSING
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/305301
作者单位	Chinese Academy of Sciences; Yantai Institute of Coastal Zone Research, CAS; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; Consiglio Nazionale delle Ricerche (CNR); Istituto di Geoscienze e Georisorse (IGG-CNR); China Geological Survey
推荐引用方式 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],2024,16(1).
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).
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).