Long-term spatiotemporal analysis of coastline morphological evolutions and their underlying mechanisms in the Pearl River Delta region of China

Abstract

The coastline, the important geographical components bordering the land and ocean, reflects abundant information on morphological evolutions. However, it undergoes continuous changing due to the compound effects of both natural and anthropogenic factors with varying intensities. Changes in the coastline are important indicators of coastal erosion, environmental changes in the coastal zone, and the rise and fall of ecosystems. The Pearl River Delta (PRD) region is rich in coastline resources, and the coastal evolution is extremely active with natural and human activities. In order to uncover the underlying mechanisms of the coastline evolutions in the PRD region, we quantitatively and qualitatively characterized the long-term alterations in coastline length, coastal development/decline, morphological structure, and the exploitation extent based on 9 satellite images of Landsat spanning from 1973 to 2021. Furthermore, we explored the driving factors of coastline change, with a view to providing some theoretical basis for the development, utilisation, protection and management of coastal resources and the sustainable development of the ecological environment in the PRD region. The findings reveal an outward expansion of coastline, resulting in a 587.49 km² increase of new land over the past 48 years. In addition, the total coastline length in this region has grown from 1477.93 to 1604.72 km, with artificial coastline contributing 61.55%, while the number of fractal dimensions suggest the further growth of coastline. Furthermore, the cause analysis identifies the morphological evolution in PRD as a multi-factor dynamic process following a “ternary-multivariate-single” pattern. Moreover, the population, GDP, precipitation, and sand transport are defined as the primary drivers, with socio-economic impacts overweighing natural conditions, and the interaction of any two drivers is greater than the effect of a single factor.