Integrating Point of Interest and BERT to identify potentially contaminating Enterprises in Datong City

Abstract. Effective management of environmental safety risks in brownfield redevelopment relies on accurate identification of contaminated enterprises. A key challenge is the rapid acquisition of data on these enterprises. This study proposes a method leveraging Point of Interest (POI) data and a BERT-based prediction model to identify potentially contaminated enterprises. The method was applied to Datong, a major industrial and mining city in China. The method successfully identified 329 potentially contaminated enterprises across 23 types of polluting industries. Notably, enterprises in the mining and washing sectors of bituminous and anthracite coal represented 26.2% of the total identified, reflecting Datong’s coal-centric industrial nature. The proposed method efficiently identifies potentially contaminated enterprises, supporting targeted environmental risk management and brownfield redevelopment. Integrating it with regulatory frameworks can enhance compliance monitoring and inform decision-making for sustainable urban development.