The quality of outdoor space in residential areas is of great importance to residents. However, the existing studies predominately focus on a certain types of open space. In addition, there is lack of objective quantification. In this study, a novel approach is developed in order to quantify the quality of outdoor space based on the identification of value dimensions and the classification of the open spaces. Firstly, the residential outdoor space is divided into six types of open space. Secondly, the value weights of different open spaces are calculated through Structural Equation Modeling (SEM) and Analytic Hierarchy Process (AHP) based on the data from on-site and online questionnaire survey. Finally, the approach developed in this study was tested in high intensity residential areas. Results of this study helps to better understand the quality of outdoor space in high intensity residential development, hence provides useful inputs for the future planning of such developments.

This study is in order to implement the mandate of UNESCO (2003) on the documentation of architectural heritage of the modern period of the 19th-20th century, where in reality several typologies of architectural heritage are currently in a marginalized condition. As part of the history of modern architecture in Indonesia, transformator huisje (Dutch) or "gardu listrik" (Indonesian) which still exist today, are not widely known as buildings that have important values in the past. This study aims to reveal whether transformator huisje architecture is classified as Modern Heritage, by tracing its historical background. Architectural analysis of 61 transformator huisje was conducted to build a "genesis"—a scheme of origin—of transformator huisje which can explain how this type of architecture was formed in accordance with the values or principles of modern architecture. The study findings show that all design features of transformator huisje as buildings for machines are strong representations of Modern Architectural Heritage in Asia, especially the Dutch East Indies (Indonesia). In conclusion, with the finding that transformator huisje is categorized as Modern Architectural Heritage, a strategy is needed to maintain this type of architecture as evidence of modern civilization in Indonesia.

AI-driven interior design generation offers promising applications. However, current AI-based diffusion models struggle to generate indoor layouts in pixel-level alignment with the indoor structure. This study proposes a new stable diffusion-based interior design workflow with an Interior Design Control Network (IDCN). IDCN ensures that the batch-generated creative interior designs based on an input image of an unfurnished room match the indoor structure. Generating innovative designs and rendering images directly with the proposed method eliminates the tedious creative design and drawing work in traditional design practices. The results indicate that the proposed method with the new design approach achieves nearly real-time design generation and modification and significantly enhances design creativity and efficiency. Moreover, the proposed method can be generalized to other design generation tasks, thereby promoting the transformation toward intelligent design.

Trajectory data is commonly used in environmental behavior studies to explore the relation between the built environment of commercial streets and urban vitality. However, there is a lack of in-depth research on the combined effects of pedestrian mobility characteristics, which are crucial for the design and management of pedestrianized commercial streets, and built environment factors. By analyzing trajectory data from two similarly designed pedestrian commercial streetsd—Beijing's Sanlitun Taikoo Li South and Chengdu's Taikoo Li, the XGBoost model is utilized to conduct a quantitative analysis of the combined impact of built environment factors. The results indicate that, in terms of time, pedestrianized commercial streets exhibit the highest vitality on non-working day evenings. Spatially, the main streets show higher vitality than secondary streets. The contribution of each factor to the results is quantified using the average Shapley values, with the most influential environmental factors being the intensity of anchor stores (4.44%), the number of seating areas (3.08%), and the green view index (2.09%). The combination of anchor store intensity and green view index has the most pronounced cross-temporal and cross-regional effect, while the interaction of anchor store intensity, green view index, and street width collectively enhances street vitality.

How to create the scenery is the key issue in ancient towns. In this study, 50 photos were collected and distributed through the Internet. First, 456 online questionnaires with 25,080 data were got. Respondents' favoritism was affected by gender, age, region, profession, and education. Second, SAM computer model was applied to image recognition of Wuzhen style photos, analyzing their visual elements. Third, SPSS software was used to analyze the correlation between subjective beauty degree score and objective landscape elements. Based on the coupled quantitative analysis of AI visual recognition and beauty degree score, it is found that the landscape elements that tourists cared most about are: water bodies, ancient buildings and boats. The proportions of the best landscape elements for the spatial sense of the ancient town are the sky ranged from 26.4% to 38.2%, water body ranged from 19.7% to 34.3%, and buildings ranged from 10.4% to 38.2%. This study reveals the pattern of different types of tourists' evaluation of the landscape to summarize the landscape construction strategy of ancient towns in Jiangnan accordingly. The results are not only benefit to the cultural tourism of Wuzhen, but can also be applied to many ancient towns in Jiangnan.

This study aims to analyze the architectural characteristics of traditional castles in Al-Hejaz, KSA, with the goal of elucidating their historical significance, cultural value, and architectural importance. The research focuses on identifying the distinctive elements of these castles and their role in enhancing the understanding and appreciation of cultural heritage in Saudi Arabia, particularly by examining Shanqal Castle as a significant yet previously understudied example. The study seeks to comprehend both the architectural and historical features of traditional castles in the region. Moreover, it investigates the influence of social, economic, and environmental factors on these structures, providing a detailed examination of Shanqal Castle as a prominent representative of this architectural typology. The research methodology includes field studies and archaeological surveys of Shanqal Castle, utilizing technological tools such as 3D modeling and photogrammetry. Additionally, it employs an analytical-inductive approach to examining relevant sources and references, alongside descriptive methods to interpret the remaining ruins of the castle.

The paper has investigated a total of 32 cities from 27 prefectures, states, and counties in Henan, Shandong, Southern Zhili, and Northern Zhili that built embankments due to the Yellow River flooding in the Ming Dynasty. It highlights the river’s impact as the main driver for embankment construction, while also noting political influences on river regulation efforts. The construction of city embankments exhibits a consistent spatial and temporal distribution pattern that aligns with occurrences of river floods. The embankments are relatively low, wide and have a long slope. The materials for embankments were rammed earth generally. Various plants are planted to protect the embankments. City embankment is an important part of the flood control system in the Yellow River Floodplain, and part of urban forms. The scale is correlated positively based on the city level. The selection of sites for some cities with embankments is determined by flood avoidance strategies, consequently influencing the development pattern. The circular shape of city embankments is often influenced by both symbolic and practical considerations. The presence of large-scale water bodies surrounding cities reflects a combination of environmental changes and urban development.

Non-Traveling Pedestrian Traffic (NTPT) plays a pivotal role in promoting business development and resident activities within High-Speed Railway Station Areas (HSRSA). However, extracting NTPT from the substantial human flow in HSRSA is technically challenging, leading to an insufficient previous discourse on the subject. In this study, we developed a simulation model for NTPT based on spatial and functional data, complemented by an evaluation framework incorporating indicators such as completeness, hierarchy, and centrality. The feasibility of this model is heightened by its reduced reliance on the collection and processing of massive pedestrian flow data. Using the Yangtze River Delta in China as a case study, the model simulation results show that limitations in NTPT development in the HSRSAs primarily stem from the lack of links between nodes and deficiencies in guiding and reinforcing these links, in addition to the fact that high-speed rail passengers exert a pronounced negative impact on NTPT. This study illustrates that NTPT is a consequence of the comprehensive interplay of spatial planning, functional development, and management policies in HSRSA. The analytical framework developed in this study contributes to elucidating the multifactorial mechanisms influencing NTPT.

Contemporary intervention strategies in Latin America have been mainly based on adaptability and informal interconnection processes based on observing morphogenic evolution in informal settlements. These behaviours were first explored by John F.C. Turner in Peru in the 1960s and Jorge Mario Jáuregui since the 2000s, subsequently used as necessary project tools in planning informal contexts. However, empirical evidence reveals that both processes have been approached individually in the interventions, showing a disconnection in the scale produced and in their complementarity of action. The objective of the study is to identify factors that originate the connection and disconnection of the processes of adaptability and interconnection between the intervention and the informal settlement, establishing a hypothesis that the disconnection produced between both processes reduces the effectiveness of the intervention to the detriment of the informal settlement. As a method, variables involved in these processes are analysed in representative models from the United States, Chile, Brazil, Colombia, and South Africa from a formal (state and private programs) and informal (evolutionary phases) perspective. As a result, the research provides new insights into the insertion of adaptability and interconnectedness processes endowed with greater effectiveness in interventions on informal settlements.

In China, traditional village layouts are dynamic, harmoniously integrated with the natural environment, and rich in unique cultural characteristics. However, rapidly constructed villages often lack professional design, resulting in overly simple layouts and causing the villages to lose their traditional characteristics. Artificial intelligence holds the potential to alleviate this specific challenge. This study employs CGAN to generate comprehensive village layouts based on archetypal traditional villages, while also exploring parameters and network architectures to enhance result quality. The research address on traditional villages in southwestern Hubei, refining generative factors, introducing image-based geographic scales, and employing machine vision to address data scarcity. The key findings of this study includes: 1) The research explores a class of AI-generated evaluation metrics suitable for village layout generation. 2) It confirms that the combination of the Unet_256 generator with the LSGAN architecture yields the best results in image generation. 3) It is observed that the optimal generation results are achieved when the equivalent geographic scale of the image is 150 m × 150 m. The study validates that GANs can be effectively applied in the village layout, producing layout results that incorporate traditional local experiences. This provides a novel approach to village layout.

Recent advances in generative artificial intelligence (AI) technologies have been significantly driven by models such as generative adversarial networks (GANs), variational autoencoders (VAEs), and denoising diffusion probabilistic models (DDPMs). Although architects recognize the potential of generative AI in design, personal barriers often restrict their access to the latest technological developments, thereby causing the application of generative AI in architectural design to lag behind. Therefore, it is essential to comprehend the principles and advancements of generative AI models and analyze their relevance in architecture applications. This paper first provides an overview of generative AI technologies, with a focus on probabilistic diffusion models (DDPMs), 3D generative models, and foundation models, highlighting their recent developments and main application scenarios. Then, the paper explains how the abovementioned models could be utilized in architecture. We subdivide the architectural design process into six steps and review related research projects in each step from 2020 to the present. Lastly, this paper discusses potential future directions for applying generative AI in the architectural design steps. This research can help architects quickly understand the development and latest progress of generative AI and contribute to the further development of intelligent architecture.

Amid increasing global environmental concerns, the architectural industry is under increasing pressure to implement sustainable practices. Leadership in Energy and Environmental Design (LEED) certification has become a crucial benchmark for assessing green building practices. This study investigates the adoption and impact of LEED-certified projects within leading architectural firms from 2000 to 2023, utilizing a novel data mining framework to scan extensive datasets on LEED projects and firm operations. We introduce two key metrics: the Weighted LEED Achieved Score (WLAS) and the Green Impact Ratio (GIR), which evaluate the sustainability efforts of firms in relation to their market size and project scale. These metrics yield insights into how firms incorporate sustainability into their business and the environmental outcomes of their projects. Our research uncovers significant trends in LEED standard adoption, illustrating a strengthening commitment to sustainable buildings. The analysis underscores the strategic importance of these practices for securing a competitive edge and aligning with global sustainability objectives. This paper contributes to the sustainable architecture discourse by providing fresh insights into the integration and effectiveness of LEED certification among top firms and offering a comprehensive framework for evaluating the environmental and economic aspects of sustainability in architecture.

Despite the educational importance of visual communication skills in spatial design education, the patterns and characteristics of students' image recognition, as well as the underlying mechanisms and influencing factors, remain unknown. This study employs objective measurement through eye-tracking to investigate students' image recognition patterns in response to a range of spatial problems, including those specific to landscape architecture based on designers' plans and perspectives, as well as their overall learning capacity. The research compares eye movements as Landscape Architecture students explore different learning materials, considering spatial scale, dimensions, and degree of detail. Additionally, influential factors such as problem difficulty and students' ability levels are examined. Results reveal that students experience significantly less visual attention pressure in Landscape Architecture-specific Spatial Ability tests, suggesting that those at a rudimentary level easily access and accept spatial learning materials in this domain due to visual coherency and real-world spatial familiarity. Furthermore, spatial scale emerges as a significant factor affecting recognition patterns, indicating higher levels of visual attention required for large-scale spatial design drawings. The findings suggest that neurophysiological data, such as eye-tracking, is effective in understanding students' challenges and mental pressures in learning visual communication skills in Landscape Architecture education. This study's insights may assist Landscape Architecture educators in developing design studio projects and assignments that align with students' cognitive characteristics in image recognition.

China's aging population is a pressing issue, with the need for comfortable living environments for older adults being paramount to their health and well-being. A study was conducted in Dalian, China, involving physical environment measurements and surveys in nursing homes and residential buildings. The investigation focused on changing indoor thermal environments and older adults' subjective sensations. The study explored physical environment satisfaction and actual thermal comfort ranges in different aging modes and space characteristics. The results show that older people spend most time in bedrooms, and dissatisfaction with the thermal environment in winter and summer is high, reaching 42% and 74%, respectively. Residential buildings generally have higher indoor temperatures than nursing homes, with a mean PMV difference of 0.9 in winter. Furthermore, thermal comfort models show that the comfort zones for nursing homes are more comprehensive in winter but smaller in summer. This study provides valuable information for future research on thermal comfort of older adults in different aging modes, facilitating the creation of healthier indoor thermal environments.

The Huainan Salt Area was the most essential salt production and trade base in ancient China. The government had strict control over the essential tax source region and left behind numerous official documents. However, when comparing with the modern surveying maps, we found that the boundaries between salt districts were unclear, which was obviously contradictory to the principle of independence between salt districts in official documents. Therefore, this study used the 1920s' historical map of the Huainan Area to extract vector data such as the canal and road networks and the location of salt settlements, and then used space syntax to describe the transportation network morphology and settlement distribution structure to respond to the contradictions with higher precision. It was found that at a 2000 m × 2000 m raster resolution, the measurements of the canal network were well correlated (p = 0.645, r = 30,000) with the salt settlement distribution. Moreover, the canal network was closer to a network-like than a tree-like structure, and vertical linkage emerged. The "government-supervised and merchant-managed" policy implemented in the Qing dynasty played an essential role, and it caused a big difference in the understanding of the salt industry system between folks and officials.

Studies have shown that a well-designed urban environment can have the same stress-reducing capacity as the natural environment. This may provide an opportunity to improve population health. In this study, we used a combination of traditional interviews and biosensing techniques to simulate the effects of living streets on emotional states within the First Ring Road of Chengdu City, and then scientifically analyzed the health effects of street environments. Within the First Ring Road of Chengdu City, we extracted the characteristics of the street environment through real-life perception experiments, and extensively photographed and sampled the living streets in the main urban area of Chengdu City, and collected the Electroencephalogram (EEG) signals of the people when they viewed different street photographs, so as to analyze the correlation between the characteristics of the street environment and the mental health of the people. The results show that the environmental characteristics of living streets that affect people's psychological perception are: green looking ratio, motor vehicle presence rate, degree of walkability, environmental complexity, building enclosure, facility distribution rate, sky visibility, elevation permeability, slow-moving occurrences and color richness. Motor vehicle presence rate and environmental complexity had a significant positive correlation with boredom, elevation permeability had a significant positive correlation with engagement mood, green looking ratio and building enclosure had a significant positive correlation with interest mood, and environmental complexity had a significant negative correlation with interest mood.