Spatiotemporal Evolution Analysis of Coastline Based on the Location Type Model: A Case Study of Huizhou

Coastlines possess significant ecological and resource values, which are intricately associated with marine ecological civilization, the marine green economy, and coastal human well-being. Comprehending the spatiotemporal variations and driving mechanisms of coastlines is of great significance for their effective protection, rational utilization, and sustainable development. Traditional coastline quantitative analysis methods mostly interpret coastal characteristics from a single dimension and struggle to hard to effectively couple the intrinsic relationships among coastline spatial variation, attribute succession, and driving mechanisms. Therefore, this study constructs a coastline location and type (CLT) model. The model classifies coastline evolution into four typical patterns, namely stable location with stable type, stable location with transformed type, changed location with stable type, and changed location with transformed type. Furthermore, the coastline disturbance index (CDI) is proposed to identify the dominant influencing factors triggering coastline spatial displacement and type transformation at the regional scale. Taking Huizhou as the study area, we employed ArcGIS to extract the coastline vectors of Huizhou in 1973, 1988, 2004, and 2019 based on multi-source remote sensing and unmanned aerial vehicle (UAV) images. Based on the analytical results obtained from the CLT model, the primary conclusions of this study are summarized as follows: During the study period, the total coastline length increased continuously from 248.68 km to 260.81 km, while artificial coastline length increased and natural coastline length declined. Meanwhile, the CDI showed a sustained upward trend, rising from 16.90% to 41.95%. This phenomenon was primarily driven by land reclamation and aquaculture enclosures, accompanied by distinct regional disparities. Specifically, land reclamation gradually became the dominant influencing factor after 1988. This study provides an integrated analytical framework for the multi-dimensional (including location, type and driving factor) quantitative investigation of coastal spatiotemporal evolution.