Objective Urbanization has caused significant habitat loss, threatening biodiversity and socio-ecological sustainability. Urban rewilding is increasingly seen as key to restoring natural processes and fostering self-sustaining urban ecosystems by reducing human interference or applying moderate restoration techniques to guide urban areas toward a more natural, uncultivated state. Despite its benefits, substantial gaps remain in identifying suitable areas for rewilding, understanding their spatial characteristics, and developing effective conservation strategies.

Methods This research introduces the concept of urban rewilding opportunity spaces (UROS) to identify and assess areas suitable for urban rewilding. UROS refers to urban spaces that either already possess wild characteristics in need of protection or have the potential to develop new urban wildness. A comprehensive quantitative and spatial analysis framework is developed to identify UROS within the Direct Administration Zone of Tianfu New Area. This framework integrates multi-source data, including data on land use, topography, population density, buildings, and roads, and employs advanced quantitative methods such as neural network, InVEST model, inverse distance weighting interpolation, and the entropy weight method. These methods are used to extract key influencing factors — spatial heterogeneity, biodiversity, human interference, which are critical for urban rewilding processes. The urban rewilding opportunity index (UROI) is calculated by weighting and summing relevant indicators, and the spatial distribution of UROS is mapped using ArcGIS 10.8.

Results The UROI is classified into five categories using the natural breaks classification method: High (UROI≥0.628), relatively high (0.628>UROI≥0.451), moderate (0.451>UROI≥0.302), relatively low (0.302>UROI≥0.145), and low (UROI<0.145). Areas with UROI≥0.302 are designated as UROS. Areas with high UROI value cover an area of approximately 48.48 km², representing 8.68% of the research area, with 1,932 patches smaller than or equal to 900 m² in area, accounting for 56.26% of these high-value spaces. Areas with relatively high UROI value cover an area of 75.25 km², or 13.47% of the research area, with 5,549 patches under 900 m² in area, comprising 55.54% of this category. Areas with moderate UROI value cover an area of 101.71 km², with 10,986 patches under 900 m² in area, making up 56.67% of this category. The findings indicate that over half of the UROS within the research area are small patches with an area less than or equal to 900 m². Areas with high UROI value are primarily located in regions with minimal human interference, high spatial heterogeneity, and significant spontaneous vegetation, such as Longquan Mountain, the Luxi River corridor, and the ecologically restored Xinglong Lake wetland. Moderate-value UROS, covering a larger area, are typically found at the edges of areas with high or relatively high UROI value or within urban built-up areas, including grasslands, forestlands, wetlands, long-term unused or abandoned lands, and farmlands with semi-natural habitats, which are more susceptible to human impact.

Conclusion This research establishes a quantitative framework to identify UROS and explores their distribution and ecological characteristics in Tianfu New Area. The findings underscore the need for systematic conservation of areas with high UROI value through the establishment of core protection zones, ecological buffer zones, and sustainable use zones. For areas with relatively high or moderate UROI value, enhancing habitat heterogeneity through targeted interventions is essential, while sustainable development should follow a “benign neglect” strategy to allow natural processes to dominate, thereby fostering biodiversity and ecosystem resilience. The research not only provides a scientific basis for identifying UROS but also offers theoretical support for further research on the dynamic balance and self-regulation mechanisms of urban ecosystems. Future research should delve deeper into the interactions between spatial heterogeneity, biodiversity, and human disturbance across various scales, and optimize the strategies for ecological design and management of urban rewilding processes to promote the sustainable development of urban ecosystems. Future research should examine the interactions between spatial heterogeneity, biodiversity, and human disturbance across scales, optimizing ecological design and management strategies for sustainable urban rewilding. Key focus areas include: 1) Simulation and prediction: Leverage 3S technologies, simulations, and field monitoring to model factors and processes affecting UROS. 2) Spontaneous plant dynamics: Monitor UROS evolution, focusing on spontaneous plant dynamics — key drivers of rewilding — at both population and community levels. 3) System dynamics modeling: Develop models to evaluate UROS responses to environmental pressures and management strategies, thereby uncovering mechanisms of wildness and biodiversity restoration.