Data-driven urban Development Prospects Based Research

Abstract

This study evaluates the future development prospects of Changchun and Hohhot through a data-driven approach, focusing on key factors such as housing prices, service levels, urban resilience, and sustainable development. The research integrates advanced modeling techniques including multiple linear regression, random forest, and XGBoost to analyze various urban indicators. In housing, the models identify price fluctuation factors and estimate housing stock using indirect metrics, with gradient boosting regression emerging as the most effective model. Changchun is found to excel in retail, finance, and lifestyle services, while Hohhot excels in public infrastructure, though both cities require balanced development to address disparities in facility distribution. Urban resilience is assessed by examining response capabilities to extreme weather and emergencies, with targeted investments suggested to enhance resilience and service accessibility. Sustainable development strategies for both cities are proposed, with Changchun focusing on green transportation and mixed-use developments, and Hohhot emphasizing healthcare and tourism infrastructure. Both cities are encouraged to adopt smart city technologies to optimize resource allocation. The study concludes that tailored development strategies, informed by data-driven insights, are crucial for achieving balanced, resilient, and sustainable urban growth, with practical recommendations for policymakers to improve service equity and foster long-term urban vitality.