Water quality and spatial dynamics: A GIS-enhanced multi-scale study of Guangdong's port and shipping service industry

Abstract

This study conducts a quantitative, multi-scale analysis of the spatial distribution and agglomeration of the port and shipping service industry in Guangdong Province, China. Using ArcGIS 10.8, spatial metrics are calculated at scales from 2 to 30 km to identify clustering and distribution patterns. Spatial autocorrelation analysis, based on Moran’s Index values (ranging from 0.35 in 2000 to 0.75 in 2021), reveals an intensification of clustering, with primary concentrations around Guangzhou, Shenzhen, and Zhuhai. The Nearest Neighbor Index (NNI), decreasing from 0.52 to 0.21 over the study period, further confirms an increasingly clustered distribution. Standard Deviation Ellipse (SDE) analysis captures the geographic orientation shift toward the Pearl River Delta, indicating a 30 % reduction in spatial dispersion. Environmental variables, including seawater quality (q-value increase from 10.5 % to 15 %), inorganic nitrogen levels (from 12 % to 17.5 %), and suspended particulate matter (from 12.5 % to 17 %), show statistically significant impacts on clustering patterns, contributing to a 25 % increase in port activity concentration in environmentally favorable areas. These findings emphasize the critical influence of environmental conditions on spatial agglomeration and underscore the need for targeted management policies to support the sustainable growth of Guangdong’s port and shipping industry.

Keywords

• Port and shipping service industry
• Multi-scale
• Spatial distribution
• Spatial agglomeration
• Guangdong province