Using Shanghai as a case study, this paper develops a multi-source fusion and interpretable machine learning framework. Sentiment indices were extracted from Weibo check-ins with ERNIE 3.0, street-view elements were identified using Mask2Former, and urban indicators like the Normalized Difference Vegetation Index, floor area ratio, and road network density were integrated. The coupling between residents’ sentiments and streetscape features during heatwaves was analyzed with Extreme Gradient Boosting, SHapley Additive exPlanations, and GeoSHAPLEY. Results show that (1) the average sentiment index is 0.583, indicating a generally positive tendency, with sentiments clustered spatially, and negative patches in central areas, while positive sentiments are concentrated in waterfronts and green zones. (2) SHapley Additive exPlanations analysis identifies NDVI (0.024), visual entropy (0.022), FAR (0.021), road network density (0.020), and aquatic rate (0.020) as key factors. Partial dependence results show that NDVI enhances sentiment at low-to-medium ranges but declines at higher levels; aquatic rate improves sentiment at 0.08–0.10; openness above 0.32 improves sentiment; and both visual entropy and color complexity show a U-shaped relationship. (3) GeoSHAPLEY shows pronounced spatial heterogeneity: waterfronts and the southwestern corridor have positive effects from water–green resources; high FAR and paved surfaces in the urban area exert negative influences; and orderly interfaces in the vitality corridor generate positive impacts. Overall, moderate greenery, visible water, openness, medium-density road networks, and orderly visual patterns mitigate negative sentiments during heatwaves, while excessive density and hard surfaces intensify stress. Based on these findings, this study proposes strategies: reducing density and impervious surfaces in the urban area, enhancing greenery and quality in waterfront and peripheral areas, and optimizing urban–rural interfaces. These insights support heat-adaptive and sustainable street design and spatial governance.

Urbanisation is a significant driver of global climate change. It increases global temperatures, impacting the health of residents. To date, research on urban heat environments has focused on society or ecology, overlooking the value of integrating the two factors. The research objective is to integrate socio-ecological benefits, explore the construction methods of ecological-cooling networks, and provide reasonable guidance for urban climate planning, thus contributing to the alleviation of urban heat risks and improving thermal comfort. Using Fuzhou as an example, an environmental risk framework was used to construct an urban heat environment risk assessment strategy based on hazards (thermal comfort), exposure (human-development footprint), and vulnerability (natural geographic conditions). The source area was identified based on evaluation results, an ecological network was constructed using circuit theory, and key nodes were identified. Results showed that in 2005 and 2020, 3% and 12% of areas in Fuzhou had higher thermal environmental risks, the proportion of low-risk areas was 43% and 28%, respectively. In sum, 54 ecological source locations, 124 ecological corridors, 76 ecological pinch points, 110 obstacle points, and 12 stepping stones were identified during the construction of corridors in 2020. Compared with 2005, the source area has decreased by 1622.46 km² and the average length of the corridor has also decreased by 4.69 km.

Fujian Tulous in China are important international architectural heritage sites that reflect precious human cultural heritage. Currently, only a small number of Tulou buildings have been listed as world cultural heritage sites, resulting in a lack of attention and financial support for most Tulou buildings. Thus, it is difficult to effectively renovate and repair Tulou buildings to adapt to modern life, and therefore they are facing the severe challenge of abandonment and desolation. Due to the special conditions of Tulou buildings, there are significant limitations in renovation and repair work, with a number of problems such as the lack of innovative renovations. Therefore, through a problem model analysis of a design system for Tulou renovations, in this study, we adopt the methods of divergent tree, conjugate pair, correlative net, implied system, and split-merge chain analyses in extenics to carry out extension transformation and solve the problem and we verify its feasibility using the example of the Tulou renovation projects in Lantian Village, Longyan City. We explore an innovative methodology for scientific renovation of Tulou buildings, and we establish a design system for Tulou building renovations that enriches and supplements original renovation methods; thus, we provide a basis for the repair and reuse of Tulou buildings, to extend their service life and to realize the sustainable development of Tulou buildings. The research results show that extenics can be implemented in innovative renovations of Tulou buildings, and it is concluded that the essence of achieving sustainable renewal in Tulou building renovations is to solve contradictory problems, including contradictions in conditions, objectives, and design. This study verifies the possibility of applying extenics in the design of Tulou building renovations, makes corresponding contributions to the application of extension methods in the renovation and renewal of Tulou buildings, and also contributes to the renovation, renewal, and protection of other types of architectural heritage sites.

Rapid urbanisation has exacerbated habitat fragmentation and degradation, necessitating urgent improvements to urban habitat quality. However, most current studies lack an analysis of spatial differences in local ecological quality, particularly a systematic exploration of how different urban spatial characteristics drive such differences. Based on this, we use Shanghai as an example, employing the InVEST model to assess habitat quality, and utilise CatBoost machine learning models and the SHAP model to reveal the specific spatial distribution characteristics of the habitat quality spatial differences from a morphological perspective, as well as its response to changes in urban spatial form factors. The results indicate that (1) urban habitat quality exhibits significant spatial differences, with quality differences persisting even within regions of the same habitat grade, demonstrating complex spatial characteristics; (2) density-related indicators such as building density and population density have a significant negative impact on the habitat quality spatial difference value, while configuration-related indicators such as the water ratio and Normalised Difference Vegetation Index have a significant positive effect, with Population Density contributing the most among all variables (20.74%); and (3) the variables exhibit significant nonlinearity and threshold effects. For example, when building density exceeds 0.05, the positive impact becomes a negative impact. The interactions between variables further reveal the multi-dimensional coupling mechanisms underlying habitat quality performance. This study contributes to a deeper understanding of the spatial differences of urban habitat quality, providing scientific support for urban ecological zoning management, the optimised allocation of green space resources, and differentiated spatial governance while offering methodological and decision-making references for the construction of high-quality ecological cities.

The Biophilic Quality Matrix (BQM) evaluates natural-element criteria in relation to intervention scales. This study applied its published 10 × 10 structure to examine document-supported biophilic integration in three completed Singapore hospital environments. Twenty-five trained raters independently assessed case-specific public documentation, organized under a common template, for all 100 C × S cells. Median ratings yielded hospital-specific BQM profiles for the three cases, and cross-hospital screening identified 67 shared candidate cells. Rater-level bootstrap analysis retained 47 high-stability cells at an inclusion-frequency cutoff of 0.95, and the study-defined high-priority rule further retained 18 cells with a median of 4 in at least two hospitals. Exploratory semantic organization of the retained cells distinguished criterion-anchored groups centered on plants, ecological systems, sunlight, and earthly materials from scale-anchored groups centered on direct use and on sensory perception and variability. The retained relationships were then traced across the three hospitals to documented spatial configurations, including pond–courtyard–bridge systems, water-and-plant respite gardens, planted terraces and roof gardens, landscape-facing building interfaces, and landscaped routes across the hospital campus. These spatial comparisons support candidate design interpretations for precedent analysis. The findings describe what the reviewed records support and do not establish measured environmental performance, realized user experience, restorative effects, or clinical outcomes.

An age-friendly built environment surrounding healthcare facilities can support older adults’ healthcare use and everyday activities. Existing studies have paid limited attention to the built environment surrounding healthcare facilities as an integrated setting. This study developed a healthcare-facility-centered framework to assess the age-friendly built environment in Fuzhou, China. Using GIS-based spatial analysis and multisource data, 3781 healthcare facilities were assessed across six dimensions: greenness exposure, health services, daily living services, social and leisure opportunities, healthcare accessibility, and functional mix. Questionnaire responses from 94 older-adult cases, including self-reports and caregiver-proxy reports, were used to derive dimension weights using the Entropy Weight Method (EWM). Three main findings emerged: (1) Higher-level healthcare facilities and more favorable integrated scores were concentrated in central urban areas, although spatial patterns varied across dimensions, particularly for greenness exposure, healthcare accessibility, and functional mix; (2) Level 3 healthcare facilities (L3HFs) had the highest median integrated score (0.613), compared with 0.345 for ungraded healthcare facilities (UHFs); and (3) 55.3% of respondents reported combining healthcare visits with shopping or leisure activities, while daily living services received the highest weight (26.4%). The uneven distribution of questionnaire responses across administrative areas may limit the representativeness of the perception-based assessment. The proposed framework can inform targeted improvements around healthcare facilities and support age-friendly planning in other cities.