Urban forest dynamics can influence the provision of ecosystem services provision. Considerable research has been conducted to understand how these dynamics respond to urbanization, from individual patches to entire landscapes. However, most of these are cross-sectional studies based on landscape metrics, and research using a process-based perspective in this context is scarce. In this study, we present a “pattern-process” analytical framework to quantify the evolutionary behavior of urban forest patches. We combine this framework with land cover classification data based on high-resolution remote sensing images (< 1 m) from 2002, 2013, and 2019 to detect the dynamic characteristics of four processes of forest patches in Beijing urban areas. These dynamic characteristics include: size distribution, aggregation and fragmentation, transfer, and self-stabilization. The results showed that 1) the average size of the patches in the study area is increasing, and patches larger than 50 m² have a more positive influence on the process of patch structure evolution, 2) patch fragmentation shifts with the direction of urban sprawl, 3) transfer between urban forest and bare land is increasing, and 4) urban forest network construction positively enhances the stability of patches. This framework can provide a useful basis for understanding the spatial and temporal evolution of urban forest landscapes during urban development and contribute to the sustainable management of urban forests.