Analysis of coastline changes under the impact of human activities during 1985-2020 in Tianjin, China

PLoS One. 2023 Nov 16;18(11):e0289969. doi: 10.1371/journal.pone.0289969. eCollection 2023.

Abstract

The accurate evaluation of shoreline movement is a crucial aspect for managing highly dynamic coasts. This study employed Landsat TM and OLI data through the Digital Shoreline Analysis System model to quantify changes in the spatiotemporal distribution of Tianjin's coastline from 1985 to 2020. The results showed that the coastline length (CL) increased by 178 km and 151% over the past 36 years, with an average increase of 5.1 km/a. Accretion and erosion processes along the entire coast were observed at rates of 83.9% and 16.1%, respectively. Notably, the Tianjin Port Area and Nangang Industrial Zone showed remarkable changes in the shoreline in 2009. Night lights (NL) were used to display the intensity of human activity in this area, and the spatial heterogeneity of night light intensity was significant. Compared to the total night light (TNL) in 1985, it increased by 116% in 2020. The relationship between TNL and CL was then established and displayed a significant positive correlation (r = 0.91). With the increasing total night light, the growth of the CL presented changes with an initial slow increase, then rapid increase, and finally slow increase. In the second phase of TNL, the CL experienced a considerable increase due to anthropogenic activities such as land reclamation and port construction, fueled primarily by government policies during the period of 2005-2013. Subsequently, there was little change in the coastline. These findings provide valuable insights into spatiotemporal coastline monitoring programs and sustainable coastal management.

MeSH terms

  • China
  • Environmental Monitoring* / methods
  • Human Activities*
  • Humans

Grants and funding

This work was supported by the National Key Research and Development Program of China (Grant No. 2022YFE0104500) and Research Funds for Central Universities (Grant No. TKS20230502, TKS20220402 and TKS20220601). The funders had roles in the study design and data collection.