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.

The issues related to soil environmental contamination caused by heavy metals have garnered increasing attention. In particular, the soil pollution risk in the eastern coastal regions of China has attracted widespread concern. This study surveyed heavy metals in the soils near the Jiahe River Basin of Yantai City in Shandong Province, China. A total of 213 soils were sampled and analyzed for 12 items: Cr, Hg, As, Pb, Cd, Cu, Ni, Zn, Co, V, Mn, and pH. The 11 heavy metals were evaluated using the national standard GB15618-2018, with three risk levels of background, screening, and intervention, and using pollution indices, including the contamination factor (C_f), ecological risk factor (Er), enrichment factor (EF), and index of geo-accumulation (I_geo), with different respective risk levels. The results indicate a strong consistency between the evaluations both for the index I_geo and for GB15618-2018 on five metals (i.e., Cr, Hg, As, Pb, and Cd). Therefore, the index I_geo may serve as a supplementary indicator for assessing the pollution risks of heavy metals in agricultural soils regarding samples of Cu, Ni, and Zn that exceed the screening values in GB15618-2018, as well as for Co, V, and Mn, which have not yet been established in GB15618-2018. According to the three-level classification of risk in GB15618-2018, the seven commonly used levels of the index I_geo are also incorporated into the three levels of background, screening, and intervention. The overall pollution risk of 11 heavy metals in the soils of the Jiahe River Basin of Yantai City belongs to the background level. Specifically, Hg and Pb in the total area are classified at the background level. Manganese, V, Co, Zn, Ni, and Cr are recognized at the screening level sporadically, while Cu, As, and Cd are found at the screening level in small areas. No areas within the region are classified at the intervention level.