Environmental Risk Assessment of Wuhan Qingshan Industrial Park Based on Multi-Source Data Fusion and FAHP

School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan, Hubei, China

^* Corresponding author: 1873048330@qq.com

Abstract

With the rapid advancement of urban industrialization, environmental risks in regional industrial parks are becoming increasingly prominent. Qingshan District in Wuhan, a key industrial hub along the Yangtze River, faces serious ecological pressures due to high emission intensity and complex industrial structures. This study proposes a multi-source data fusion framework that integrates remote sensing, statistical yearbooks, and pollutant inventory estimation to build a comprehensive environmental risk evaluation index system. The fuzzy analytic hierarchy process (FAHP) is employed to assign weights through expert judgment, and fuzzy membership functions are used to determine risk levels across selected sub-regions. Results show that old industrial zones exhibit high environmental risk, while newly developed industrial parks have significantly lower risk due to improved infrastructure and eco-friendly design. The proposed framework proves to be practical and replicable for environmental governance in complex industrial urban areas. Additionally, this study highlights how fuzzy classification bridges the gap between categorical and continuous assessments, which is crucial for transitional risk zones where traditional models offer binary decisions. These findings have direct implications for targeted policymaking and zoning reform. We also emphasize the transferability of our framework to other high-density industrial cities globally. This enhances its suitability for high-density industrial cities seeking dynamic evaluation frameworks.