Scientific assessment of sustainable development potential (SDP) and analysis of spatial heterogeneity mechanisms of traditional villages are crucial for promoting the synergy between cultural heritage conservation and rural revitalization strategies. With an emphasis on traditional villages in the Cantonese region, this study develops a thorough evaluation methodology that combines spatial analysis and multi-criteria decision-making. It aims to (1) systematically reveal the spatial differentiation characteristics of sustainable development potential; (2) develop and validate a combined weighting method that effectively integrates both subjective and objective weights; and (3) identify key driving factors and their interaction mechanisms influencing the formation of this potential. To achieve these objectives, the research sequentially conducted the following steps: First, an evaluation indicator system encompassing socioeconomic, cultural, ecological, and infrastructural dimensions was developed. Second, the Analytic Hierarchy Process and the Entropy Weight Method were employed to calculate subjective and objective weights, respectively, followed by integration of these weights using a combined weighting model. Subsequently, the potential assessment results were incorporated into a Geographic Information System, and spatial autocorrelation analysis was applied to identify agglomeration patterns. Finally, the Geographical Detector model was utilized to quantitatively analyze the explanatory power of various influencing factors and their interactions on the spatial heterogeneity of potential. The main findings are as follows: First, the sustainable development potential of traditional Cantonese villages exhibits a significant “core–periphery” spatial structure, forming a high-potential corridor in the Zhongshan–Jiangmen–Foshan border area, while peripheral areas generally display “low–low” agglomeration characteristics. Second, the combined weighting model effectively reconciled 81.0% of case discrepancies, significantly improving assessment consistency (Kappa coefficient above 0.85). Third, we identified economic income (q = 0.661) and ecological baseline (q = 0.616) were identified as key driving factors. Interaction detection revealed that the interaction between economic income and transportation accessibility had the strongest explanatory power (q = 0.742), followed by the synergistic effect between ecological baseline and architectural heritage (q = 0.716), highlighting the characteristic of multi-factor synergistic driving. The quantitative and spatially explicit evaluation framework established in this study not only provides methodological innovation for research on the sustainable development of traditional villages but also offers a scientific basis for formulating regionally differentiated revitalization strategies. The research findings hold significant theoretical and practical importance for achieving a positive interaction between the conservation and development of traditional villages.

Soundscapes are one of the main means of creating a religious atmosphere in Han Chinese Buddhist temples, which are the most important religious sites in China. This paper selected several representative forest-type and urban-type Han Chinese Buddhist temples and employed a questionnaire and sound level measurement methods to conduct a comparative analysis of four aspects of acoustic environment evaluation, i.e., quietness, comfort, harmony, and sound preference, to identify and compare the characteristics of respondents’ soundscape evaluation in these two types of temples. The results showed that compared with urban-type temples, respondents found the acoustic environment in forest-type temples to be quieter, more comfortable and more harmonious with the religious atmosphere. The sound level, measured with the questionnaire and respondents’ social characteristics, such as age, occupation, level of education, purpose and frequency of visiting the temples, and attitude towards Buddhist thought, influenced their soundscape evaluation of urban-type and forest-type temples to different degrees. Among the various kinds of sounds in the temple, natural sounds, such as the sounds of flowing water, birds and insects, and rustling leaves, were preferred in forest-type temples, while Buddhism-related human-made sounds, including chanting and background music, were preferred in urban-type temples.

The Chinese Eastern Railway (CER) has been identified as a heritage site that has witnessed industrial and social developments and changes over the past 100 years. Many old infrastructures have transitioned from civil use to historical conservation, but the spatial distributions and driving forces of ecosystem service functions provided by local ecological infrastructures are still unclear. The green view index (GVI) is a flexible parameter that measures the ratio of pixels accounted for by greeneries to those in an intact street view image; hence, it is widely recognized as a reliable variable for assessing the magnitude of ecosystem services provided by ecological infrastructures at a regional scale. In this study, a total of 42 urban parks were selected from regions covered by CER routes and adjacent cities without its involvement. No difference in GVI was found among cities regardless of distance from CER routes, and the distance of a park to the nearest CER line was found to have only indirect and negative effects on GVI. Correlation analysis indicated that the logarithms of both green and blue space areas had positive relationships with GVI. Regression analysis indicated that the logarithm of the blue space area, together with elevation and longitude, had positive effects on GVI, while latitude resulted in a negative effect. Overall, low GVI values (~6.0%) in the parks of Tsitsihar resulted from the effect of high closeness with the CER route, and high GVI values (over ~40%) in the parks of Changchun were indicated by the joint characteristics of local landscape metrics.

This study proposes the Sponge City+ parametric design toolkit, which integrates low-impact development (LID) measures into urban design to support compliance checking, runoff risk analysis, and optimization of design alternatives. Compliance is evaluated using the annual runoff volume capture ratio (AVCR) calculated via the Volume Method, which is the core criterion in sponge city standards. The toolkit combines a measures database, runoff volume control functions, and runoff simulation functions to evaluate and compare design alternatives. Its applicability was tested through case studies of three university campuses in China. These cases were used to: (1) conduct a sensitivity analysis of the toolkit’s response to different LID strategies, ranking three typical LID measures (sunken green spaces > permeable pavements > green roofs) in terms of their contribution to runoff control; (2) perform multi-objective optimization considering cost, runoff control, and peak reduction, which, under ordinary PC computational capacity, efficiently identified 27 qualified solutions out of more than 5000 samples, thereby providing a broader set of design choices while ensuring compliance with runoff control requirements; and (3) demonstrate a design optimization process based on runoff visualization, where human–computer interaction helped avoid potential flood risks during the early design stage. This study demonstrates the potential of a parametric workflow to bridge disciplinary boundaries and support the achievement of global sustainability goals.

Traditional villages, as carriers of agricultural civilization and ecological wisdom, represent important sites for fostering new-quality productive forces. In the context of rapid urbanization, they function as key spaces for rural development while also confronting vulnerabilities such as spatial functional imbalance and ecological degradation. Within the production–living–ecology (PLE) spaces, dependence on labor-intensive and capital-intensive agricultural models often results in resource misallocation and systemic dysfunction. New-quality productive forces, driven by innovation and green transition, provide a fresh perspective for sustainable rural spatial restructuring. However, their micro-scale mechanisms within traditional villages remain underexplored. This study focuses on 22 nationally recognized traditional villages in Foshan, China. Based on land-use and socioeconomic data from 1993, 2003, 2013, and 2023, we applied land-use transition matrices, a coupling coordination degree model, and geographical detector analysis to examine the evolution of PLE spatial patterns and their driving mechanisms. The findings show that (1) spatially, the share of living space increased significantly, while ecological and agricultural production spaces continued to shrink, reflecting heightened competition among the three; (2) the overall coupling coordination degree exhibited a declining trend, indicating weakened synergy among PLE functions; (3) key drivers of system coordination include per capita disposable income of rural residents, agricultural labor productivity, regional technological innovation capacity, and forest coverage, underscoring the synergistic role of socioeconomic and ecological factors in new countryside development. This study elucidates the micro-spatial pathways through which new rural construction and conservation mechanisms operate, providing a reference for context-sensitive conservation and high-quality development of traditional villages in rapidly industrializing regions. The analytical framework can also be extended to other rural areas undergoing transition.

In the subtropical regions of southern China, springtime is often characterized by persistently high humidity, leading to frequent condensation on building envelopes and interior surfaces. Top-floor rooms are particularly vulnerable due to their direct exposure to outdoor conditions through walls and the roof, making condensation prevention a critical concern. This study is grounded in the residential habits and spatial preferences of southern Chinese residents and evaluates three roof configurations—standard, thickened, and green roofs—using EnergyPlus (v22.1.0) simulation software to analyze their effects on indoor relative humidity levels in top-floor spaces. The results demonstrate that green roof systems significantly reduce indoor relative humidity, especially in high-rise residential buildings. Taking a 30-story residential building as an example, with a conventional roof, the indoor relative humidity remains at 100% for extended periods during high-risk condensation intervals, resulting in surface condensation. In contrast, when a green roof with a soil depth of 70 cm and daylilies at a height of 100 cm is used, the peak indoor maximum relative humidity is reduced by 10–40%, and the duration of condensation decreases to zero. Among the factors involved in green roofs, including plant height, soil depth, and leaf area index (LAI), soil depth shows a significant negative correlation with the maximum indoor relative humidity (correlation coefficient r = −0.987, p < 0.01), while the LAI exhibits a positive correlation with the maximum indoor relative humidity (r = 0.180, p < 0.05). Selecting plant species with a low LAI and increasing soil depth are effective passive strategies for humidity control and condensation prevention. These findings establish a basis for optimizing building environmental models and propose passive design strategies to enhance overall performance. In addition, the study highlights how roof greening contributes to global sustainability goals, particularly SDG 3 (Good Health and Well-being), SDG 11 (Sustainable Cities and Communities), and SDG 13 (Climate Action), by improving indoor comfort, enhancing resilience, and reducing climate-related risks.