Objective In the context of the “Healthy China 2030” strategy and the post-pandemic era, high-density cities face the dual challenges of limited green space and increasing psychological stress. Community green spaces, as the most accessible natural environments for daily use, serve as critical public health resources for mental restoration. However, existing biophilic design assessment tools often lack sufficient quantitative precision, fail to adapt to local contexts, and are poorly integrated into planning workflows. This study aims to develop the Biophilic Design Quantitative Evaluation System (BDQES), a systematic, quantifiable, and actionable framework tailored for high-density urban communities in China, thereby bridging the gap between abstract biophilic theories and localized design practice.

Methods Guided by the principles of being perceptible, quantifiable, and actionable, the BDQES was developed through a interdisciplinary literature review and deconstruction of existing biophilic assessment tools. Drawing upon theoretical frameworks Attention Restoration Theory and Prospect-Refuge Theory, an initial pool of indicators was compiled and subsequently refined to ensure applicability to high-density environments. The resulting hierarchical system comprises five primary indicators (Environmental Naturalness, Environmental Comfort, Element Richness, Site Openness, and Human Perception), 17 secondary indicators, and 42 tertiary indicators. Each tertiary indicator is provided with clearly defined operational definitions, specific quantification methods, and referenced thresholds derived from empirical studies. A three-stage empirical validation approach was designed and conducted. Initially, an on-site expert evaluation was carried out at the Hongxu Habitat Garden in Shanghai, a representative high-density community renewal project. Fifteen experts from professional backgrounds, including urban planning, ecology, and environmental psychology, independently evaluated the site using the newly developed BDQES. Following this, a large-scale online experiment was conducted with 123 participants. Nine key visual biophilic elements were manipulated into low, medium, and high exposure levels using processed images, and participants rated their perceived restorativeness using the Perceived Restorativeness Scale (PRS). A field study was conducted to verify the system’s applicability in real-world scenarios. The BDQES was first used to quantitatively evaluate five distinct scenes within the habitat garden. 97 residents were recruited to experience these scenes and report their psychological restoration and emotional states using the PRS and the Positive and Negative Affect Schedule (PANAS). The consistency between the system’s objective evaluation results and the residents’ subjective psychological feedback served as the ultimate validation of the system’s effectiveness.

Results The study yielded findings across all validation stages. The expert evaluation demonstrated strong inter-rater reliability, with an Intraclass Correlation Coefficient (ICC) of 0.917. The online experiment revealed patterns regarding how different element exposure levels affect restoration. Distinct trends were observed: monotonically increasing trends in restorative benefits were found alongside the enhancement of the green view ratio, visible water surface, and spatial curvature, indicating that higher exposure to these elements consistently enhances restorative benefits. Conversely, monotonically decreasing trends were found as spatial depth, aspect ratio (D/H), and openness increased, suggesting that excessive depth or openness in high-density settings may induce a sense of oppression or a lack of safety, thereby diminishing restorative effects. More complexly, non-monotonic fluctuating trends were identified for biodiversity, color combinations, and sky view. Specifically, biodiversity and color combinations exhibited peak characteristics at moderate exposure levels, while sky view showed valley characteristics at moderate levels, collectively indicating the existence of an "optimal balance" for complexity-related elements that prevents both monotony and cognitive overload. Finally, the offline field study confirmed a high degree of consistency between the BDQES evaluation and residents’ actual restorative benefits. Scenes rated higher by the BDQES, which were characterized by higher naturalness and appropriate richness, elicited significantly higher PRS scores compared to lower-rated scenes.

Conclusion This study translates biophilic design principles into a quantifiable and empirically validated spatial indicator system. The BDQES provides an evidence-based framework for diagnosing and optimizing green spaces in high-density contexts. Furthermore, the dose−response relationships identified in this study offer preliminary quantitative design guidelines, suggesting that designers should prioritize maximizing certain natural features while carefully managing spatial scale and seeking an optimal balance for environmental complexity. While the current version of the BDQES employs equal weighting, future research will focus on developing a weighted system and conducting immersive validation using Virtual Reality. Overall, this system facilitates a paradigm shift from intuitive, experience-driven design to precise, evidence-based practice, ultimately supporting the creation of healthier, more restorative urban environments.