The goals of this study are to propose a method to minimize the waste of buildings’ exterior walls and to respond to practical technical reports on disaster resistance and reductions in resource extraction. This study’s scientific value is its testing of new nearly zero-waste materials and their construction methods for external walls. Four cases using a bamboo and pozzolana wall construction method between 2016 and 2021 in Southern Taiwan were examined. The results show that the materials can be decomposed on site to achieve the goal of nearly zero waste. Steel structures and exterior walls can provide toughness and breathability to resist earthquakes and hot and humid climates. Traditional construction techniques contain elements of technological change and can transcend outdated regulations. The exterior wall materials in this study can replace the local high-carbon-emitting mining industry and are a feasible way to actively respond to net-zero emissions.

The purpose of this study was to explain how the heterogeneous elements embedded in the Jimei Peninsula affect the transformation of the production landscape into a consumption landscape and the connection between urban governance and economic transformation. The study took a qualitative approach, utilizing historical literature analysis, a field investigation, and in-depth interviews to explore the driving forces and impacts of coastal-zone functional transformation. A total of 26 residents were interviewed individually or collectively, the current situation in the coastal zone with a length of about 16.1 km was recorded in detail, and all the collected elements were divided into six landscape categories for analysis. The results indicate that urban positioning, economic development, policies, and residents are the main factors driving the continuous advancement of the Jimei Peninsula zone. The coast has completed the functional transformation from meeting the residents’ survival needs to tourists’ sightseeing needs. The traditional fishing culture in this area is slowly disappearing with the tide of time, and navigation technology is being passed down through the Jimei School Village. This study reveals the dynamic process of the transformation of coastal functions in representative coastal tourism cities in China, bringing attention to coastal ecology and local fishing culture, and raising people’s awareness of cautious coastal development and sustainable blue-economy development.

Evaluating pedestrian comfort in high-density cities requires methods integrating subjective experience with urban morphology. This study develops an integrated framework combining pairwise comparison scoring, semantic segmentation (DeepLabv3+), ensemble learning (Random Forest), and SHAP-based interpretability. EfficientNet-B7 is used to expand pairwise datasets and derive continuous comfort scores across Macau’s street network. Four experiential street types are identified: historical–cultural districts, urban lifestyle areas, natural corridors, and leisure zones. SHAP analysis illustrates stable associations between predicted comfort scores and multi-layered spatial configurations, including cultural legibility and sequencing in historic cores, moderate greenery with functional anchoring in residential areas, and scene coherence in tourism zones. Semantic features serve as effective morphological proxies within the modeling framework. Methodologically, the framework demonstrates how explainable machine learning can be applied to dense Asian cities under observational conditions. Design implications emphasize interface continuity, microclimate adaptation, and functional enrichment, suggesting that pedestrian comfort is closely related to coherent spatial–experiential structures rather than isolated environmental upgrades.

Urban nighttime lightscapes shape the tourist experience, urban image, and commercial identity, yet existing evaluation methods trade off objective measurement, real-scene coverage, and the interpretation of subjective perception. This study examines the nighttime facades of six representative commercial complexes in Macao and constructs a multisource computational framework for nighttime lightscape perception evaluation. Objective features such as luminance, color, light-element composition, and visual saliency are extracted from 1800 user-generated content (UGC) images; affect, atmosphere, aesthetics, comfort, and behavioral intention are measured through 300 online questionnaires; and affective responses expressed in natural language are characterized using 6208 Chinese and English public reviews. A structural equation model (SEM) shows that all six categories of subjective psychological perception—atmosphere, aesthetics, pleasure, comfort, arousal, and dominance—exert significant positive effects on behavioral intention, with atmosphere, aesthetics, and pleasure being the most prominent. Cross-source ranking comparisons further show that the objective light-element proportion is strongly consistent with predicted visual attention, whereas greater attention capture does not necessarily translate into higher aesthetic, comfort, or behavioral-intention ratings. At the case level, Grand Lisboa and Wynn Palace exemplify two contrasting nightscape configurations based on iconic light elements and holistic illumination, respectively. This study thus provides a reproducible data pipeline for commercial nightscape lighting evaluation and offers an analytical perspective for nighttime destination management that jointly weighs visual evidence and human-centered perception.