In the context of rapid urbanization, the scientific planning and development of ecological parks in small- to medium-sized cities are essential for enhancing the well-being of city dwellers and optimizing the ecological quality of urban environments. Traditional site suitability methods, however, are increasingly limited due to data resolution constraints and the challenges of balancing ecological protection, urban development, and socio-economic interests, which hardly provide insights for ecological park planning in small and medium-sized cities. This study addresses these limitations by employing a multi-source geographic big data framework, and applying it in Yongji City, Shanxi Province, by integrating remote sensing, Points of Interest, and land use data, a detailed 10m × 10m spatial grid was used for analysis. A comprehensive three-dimensional evaluation framework was developed, comprising ecological, infrastructural, and socio-economic factors, represented by 11 indicators. Points of Interest data have effectively assessed infrastructural configurations necessary for urban ecological parks, while remote sensing data provides critical insights into surface temperature and vegetation cover, which provide high-resolution indicators of environmental quality in urban and sub-urban regions. The site suitability analysis results reveal that hydrophilic landscapes, such as the Yellow River mudflats and Wuxing Lake wetlands, were identified as optimal areas for ecological park development due to their cooling effects and ecological benefits. Zone C, located southwest of Wuxing Lake, emerged as the ideal site due to its abundant natural assets and high accessibility, with a phased development strategy of other recommended sites based on their suitability. This research establishes a data-integrated framework that advances the methodology for urban ecological park planning in small- to medium-sized cities, providing both theoretical and practical insights that can inform similar projects in other urban contexts.