Zhigang Wu

The renewal of historic districts requires a balance between heritage conservation, spatial quality improvement, and contemporary urban use. Yet the links between perceptual experience and measurable spatial characteristics remain insufficiently clarified. Using the Yantai Mountain Historic District in Fuzhou, China, as an empirical case, this research develops an integrated evaluation framework that combines perceptual assessment, street-view image analysis, and interpretable machine learning. Street view images, field investigations, and questionnaires were used to construct a subjective-objective evaluation system. A total of 1408 sampling points were established, and 1272 valid street view images were collected. Perceptual scores were provided by 15 local residents and 15 professionals. Objective indicators, including enclosure, greenery, openness, motorization, and non-motorization, were extracted through semantic segmentation. Multiple linear regression and random forest models were then used to examine the relationships between spatial indicators and perceptual experience. The findings reveal nonlinear associations and multi-factor interactions between objective spatial characteristics and subjective perception. Safety and cultural perception scores are higher when the enclosure ranges from 0.30 to 0.60, and the non-motorization ranges from 0.10 to 0.30. Comfort and visual pleasantness scores are higher when non-motorization ranges from 0.10 to 0.20 and motorization from 0.05 to 0.15. SHAP analysis further indicates that openness and motorization primarily influence perceived safety, whereas non-motorization and enclosure contribute more strongly to cultural perception, comfort, and visual pleasantness. The proposed framework provides a quantitative and interpretable basis for refined spatial renewal in historic districts.

As a neighborhood-scale derivative of the Business Improvement District (BID) model, the Neighborhood Business Improvement District (NBID) represents a collaborative governance framework aimed at fostering spontaneous urban regeneration. Its successful establishment critically depends on building consensus among diverse stakeholders during the preparatory phase. This study addresses a significant gap by investigating the psychological mechanisms that shape stakeholders’ willingness to engage in NBIDs prior to their formation. Employing an exploratory sequential mixed-methods approach, we conducted semi-structured interviews in the Tiyuan North Community (Tianjin) and the Yulin East Road Community (Chengdu). Insights from the qualitative phase informed a subsequent quantitative survey administered to 215 stakeholders in Tianjin. Data were analyzed using regression analysis and Structural Equation Modeling (SEM). The results reveal that stakeholders’ performance expectations and collaborative willingness are significantly influenced by three core confidence factors: “Confidence in Authority Support (AS)” (particularly “Confidence in Council Representation”), “Confidence in Organization Capability (OC)” (especially “Confidence in Coordination Ability”), and “Confidence in Multi-party Collaboration.” Crucially, “Confidence in Enabling collaboration (MC_3)” itself acts as a key mediator, translating institutional trust into performance expectations. This study contributes a novel “Confidence–Expectation” framework to the literature on collective action and offers practical, context-sensitive insights for designing collaborative community governance structures aimed at sustainable urban regeneration in China and beyond.

Under the new normal of China’s development, urban construction has shifted from incremental expansion to the optimization of existing stock. As the focal point of urban stock, old communities have garnered increasingly in-depth research. Recent studies have extended their perspectives from physical spaces to the interactive relationship between “space and behavior”, while also emphasizing the integration of qualitative and quantitative analyses. However, existing research primarily focuses on the static characteristics of material spatial environments, neglecting the dynamic interplay between spatial attributes and social network relationships. This study takes the Cangxia Community in Fuzhou as a case study, employing social network analysis (SNA) to construct a dual-network model of resident behavior and public space. Through a three-level analysis of “overall–subgroup–single point”, the intrinsic relationship between “space and behavior” in old communities is revealed. The model demonstrates that resident behavior characteristics are positively correlated with public space attributes, namely, the better the spatial accessibility and visibility, the higher the frequency of resident behaviors. However, mismatched spatial nodes also exist, limiting the synergistic optimization of the dual-network model. This research aims to provide scientifically effective methods and paradigms for the renewal of old communities and the sustainable development of cities.

As modern society increasingly emphasizes quality of life, historic districts face the challenge of balancing the preservation of traditional culture with the integration of urban development. Many historic districts today struggle with low vitality and limited visitor engagement. By adopting sustainable development strategies, such as promoting tourism, these districts have the potential to enhance economic vitality. This study explores the spatial morphological characteristics of the ShuiXiLin Historic District (SHD) in Fuzhou, using spatial syntax theory and tools within the framework of sustainable urban renewal. The study proposes three strategies for the district: (1) enhancing connectivity positively influences the public experience within the SHD; (2) strengthening the district’s primary axis amplifies its influence across the area; (3) implementing protective reuse of historical buildings and improving service facilities can significantly enhance the district’s vitality. Through theoretical analysis and a review of existing research, this study proposes revitalization strategies aimed at formulating sustainable development plans for the district. These recommendations are intended to offer valuable insights for urban renewal projects and provide theoretical support for planning decisions related to the vitality of historic districts. This research illustrates the effective use of spatial syntax in historic districts, offering a robust method to evaluate and enhance the spatial structure and vitality of heritage areas. It supports sustainable development by integrating preservation with modern needs, ensuring a balance between conservation and urban growth.

As China’s urbanization progresses, the urban heat island (UHI) effect has become more pronounced, impacting the health of residents and the activity intentions of visitors within historic urban areas. This study focuses on the historic district of the Three Lanes and Seven Alleys Tourist Area (SFQX) in Fuzhou, where simulations were conducted on four representative streets across various times during a typical summer meteorological day. Typological methods were employed to simplify neighborhood modeling, and Phoenics software was utilized to simulate the neighborhood’s wind environment and the outdoor pedestrian thermal comfort index. Aspect ratio (AR), sky view factor (SVF), air velocity (Va), and universal thermal climate index (UTCI) values at specific locations were collected for statistical analysis. The findings reveal that: (1) the N–S orientation exhibits more significant correlations between Va, the UTCI, and street geometry compared to the E–W orientation; (2) the relationship between SVF and the UTCI fluctuates with time; (3) areas with higher AR values, such as medium and deep canyons, offer better thermal comfort for outdoor pedestrians; and (4) at 8:00, the UTCI and wind speed show minimal correlations with street geometry and direction, being predominantly influenced by objective climatic factors. These insights are expected to significantly inform the geometric design and planning of streets in Fuzhou’s historic districts, aiming to create more comfortable outdoor environments for inhabitants and visitors alike.

The building wind environment in coastal areas is highly complex and variable, particularly during winter when strong winds prevail. Understanding the influence of winter winds on human comfort and addressing health issues caused by wind noise in human settlements are very valuable research topics. This study focuses on developing strategies to optimize the wind environment in dormitory buildings located in the southern coastal area, where prolonged periods of strong winds have a significant impact. Specifically, we investigated the current wind in the teacher–student dormitory at Jinjiang Campus of Fuzhou University through questionnaire surveys and field measurements. Additionally, computational fluid dynamics (CFD) simulations were employed to evaluate different dormitory layouts. The research results indicate that it is preferable to position the dormitory areas downwind of large-scale buildings, adopt a staggered layout instead of a regular determinant layout to mitigate the narrow tube effect, avoid designing large-scale squares in the center of the dormitory areas, and enclose the dormitory groups with low-level corridors. These findings provide valuable guidance for the optimizing of winter windproof designs of university buildings located in the same climatic zone along the southeast coast.

The physical environment of urban public facilities is an important driver for public health and work efficiency. Unfortunately, citizens are exposed to negative physical environments because of inappropriate spatial forms in urban growth boundaries. This study aims to explore psychophysical drivers and their spatial distribution in campus city community life circles during the COVID-19 pandemic. Questionnaires and measuring equipment were used to gather psychophysical information in a 15 min campus city community life circle in Fuzhou, China. To this end, acoustic, light and thermal environments were used to map spatial distributions. We then explored relationships between spatial form and psychophysical parameters. The study results show that the distance to road (DTR), green area ratio (GR) and street width (SW) are all potential spatial drivers for psychophysical information. Furthermore, the acoustical, light and thermal environments provide interactions for the public understanding of the environment. These findings contribute to the understanding and evaluation of psychophysical drivers, spurring regional industry in community life circles and contributing to developing suitable plans and industrial distribution in urban areas.