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Does urban density always boost smart productivity? Based on panel data from 28 major Chinese cities (2011-2021), this study reveals an inverted U-shaped relationship between urban density and smart productivity. Using entropy weight method, we construct comprehensive indices to measure both urban density and smart productivity levels. Our findings demonstrate that urban density positively influences smart productivity up to a threshold of 0.497, beyond which the relationship becomes negative. The results from fixed effects modeling show that a 1% increase in urban density is associated with a 0.114% increase in smart productivity before reaching the threshold. Through mediation analysis, we find that urbanization level serves as a significant mediator, accounting for 49.1% of the total effect. Furthermore, heterogeneity analysis reveals distinct regional patterns: urban density exhibits stronger positive effects in western regions (coefficient = 0.181) compared to central regions (coefficient = 0.156), while showing negative impacts in eastern regions. These findings suggest that optimal urban density levels vary across regions, and cities should adopt differentiated development strategies accordingly. Our study contributes to the literature by quantifying the non-linear relationship between urban density and smart productivity, while providing empirical evidence for urban planning policies.

With the development of urban scale and economic growth, the challenges posed by limited resources and insufficient environmental carrying capacity become increasingly severe, making the sustainable improvement of production efficiency an urgent requirement. Based on panel data for cities in the Dianzhong Urban Agglomeration and the Chengdu–Chongqing Economic Circle in Southwest China (2012–2021), this study elucidates the positive effect of urban compactness on green total factor productivity (GTFP). By constructing a composite index to measure urban compactness and employing an SBM model to quantify GTFP, we find that a 1% increase in urban compactness leads to a 0.65% increase in GTFP. A mediating-effect analysis reveals that green technological innovation serves as a significant mediator, with a mediating effect value of 0.363. Heterogeneity analysis uncovers differing mechanisms of influence: urban compactness exerts a positive effect in regions with higher levels of economic development, while its impact is not significant in regions with lower economic development, indicating that the effect of compactness varies with economic context; the impact of urban compactness on GTFP is statistically insignificant in regions with higher tertiary sector shares (p > 0.1), whereas it exhibits a highly significant positive effect in regions with lower tertiary sector presence (β = 1.49, p < 0.01). These results collectively demonstrate that the influence of urban compactness on GTFP varies significantly with industrial structure composition. Threshold-effect analysis further shows that there is a threshold in the proportion of industrial output value, beyond which the influence of compactness on GTFP becomes even stronger. Our research quantitatively explores both linear and nonlinear relationships between urban compactness and GTFP, clarifying the linkage between urban spatial dynamics and green production efficiency, and provides empirical evidence and scholarly support for urban planning and economic development.

The terraced fields of Samaba in Honghe County are one of the key protected sites within the globally important agricultural heritage systems. This study focuses on the traditional courtyard dwellings of the Hani people in this area, proposing that their architectural practices reflect a profound and sustainable adaptation to the local environment and socio-agricultural systems. Through field investigations, architectural surveys, and in-depth interviews with Hani Bema (ritual specialists), artisans, and residents, this research analyzes the settlement characteristics and distribution of the area, the spatial features of traditional Hani courtyard dwellings, three typical floor plans, and the construction techniques of key components such as wooden structures, earthen walls, and roofs. The findings indicate that the use of local materials (e.g., wood, raw earth, stone) and their specific construction methods are inherently responsive to the regional climate, forming a sustainable residential model that spans material acquisition, construction, and maintenance. Crucially, the study reveals a strong isomorphic relationship between the material and energy cycles involved in Hani settlement construction and those of terrace farming activities. We argue that the sustainability of villages and architecture is essential for the sustainability of the entire terrace agricultural ecosystem. By elucidating the wisdom of Hani dwellings in terms of materials, construction, and maintenance, this study provides significant insights for discussions on sustainable vernacular architecture and offers valuable perspectives for its green renewal and contemporary adaptation.

Under the dual challenges of global energy crisis and climate change, the building sector, as a major carbon emitter consuming 33% of global primary energy, has seen its energy efficiency optimization become a critical pathway towards achieving carbon neutrality goals. The Window-to-Wall Ratio (WWR), serving as a core parameter in building envelope design, directly influences building energy consumption, with its optimized design playing a decisive role in balancing natural daylighting, ventilation efficiency, and thermal comfort. This study focuses on the traditional One-Seal dwellings (Yikeyin) in Kunming, China, establishing a dynamic wind field-thermal environment coupled analysis framework to investigate the impact mechanism of window dimensions (WWR and aspect ratio) on indoor thermal comfort under natural wind conditions in transitional climate zones. Utilizing the Grasshopper platform integrated with Ladybug, Honeybee, and Butterfly plugins, we developed parametric models incorporating Kunming’s Energy Plus Weather meteorological data. EnergyPlus and OpenFOAM were employed, respectively, for building heat-moisture balance calculations and Computational Fluid Dynamic (CFD) simulations, with particular emphasis on analyzing the effects of varying WWR (0.05–0.20) on temperature-humidity, air velocity, and ventilation efficiency during typical winter and summer weeks. Key findings include, (1) in summer, the baseline scenario with WWR = 0.1 achieves a dynamic thermal-humidity balance (20.89–24.27 °C, 65.35–74.22%) through a “air-permeable but non-ventilative” strategy, though wing rooms show humidity-heat accumulation risks; increasing WWR to 0.15–0.2 enhances ventilation efficiency (2–3 times higher air changes) but causes a 4.5% humidity surge; (2) winter conditions with WWR ≥ 0.15 reduce wing room temperatures to 17.32 °C, approaching cold thresholds, while WWR = 0.05 mitigates heat loss but exacerbates humidity accumulation; (3) a symmetrical layout structurally constrains central ventilation, maintaining main halls air changes below one Air Change per Hour (ACH). The study proposes an optimized WWR range of 0.1–0.15 combined with asymmetric window opening strategies, providing quantitative guidance for validating the scientific value of vernacular architectural wisdom in low-energy design.

In response to global climate change, harnessing the climate-adaptive wisdom of vernacular dwellings is crucial for sustainable architectural design. This study takes Haiyan Village in the Kunming plateau area as a case study, focusing on three typical vernacular dwelling types of Yikeyin—‘Half seal’, ‘One seal’, and ‘Two seals’. Using Ladybug and Honeybee within the Rhino Grasshopper platform, a quantitative comparative analysis was conducted to evaluate their natural ventilation efficiency (characterized by Air Changes per Hour, ACH) and indoor thermal comfort (characterized by Predicted Mean Vote, PMV, and Predicted Percentage of Dissatisfaction, PPD). The results indicate the following: (1) Throughout the year, the ‘Two seals’ dwelling type exhibits the most stable diurnal temperature variation, while the ‘Half seal’ dwelling type shows the greatest fluctuation in its diurnal temperature range. (2) The summer ACH values for ‘Half seal’, ‘One seal’, and ‘Two seals’ dwelling types are 3.8~4.5, 1.5~2.9, and 0.8~1.6, while the winter values are 1.9~2.6, 1.3~1.8, and 0.7~1.0. The ventilation efficiency in summer is generally higher than that in winter, and it shows a significant decreasing trend as building volume increases. (3) The summer PPD values for ‘Half seal’, ‘One seal’, and ‘Two seals’ dwelling types are 12%, 18%, and 35%, while the winter values are 22%, 15%, and 12%. (4) The ‘One seal’ dwelling type exhibits good ventilation and thermal comfort throughout the year. The ‘Half seal’ demonstrates the best ventilation and thermal comfort in summer but poorer thermal comfort in winter. The ‘Two seals‘ dwelling type achieves the best thermal comfort in winter, but lower ventilation efficiency, while in summer, both thermal comfort and ventilation are poor. This study not only addresses the gap in the quantitative assessment of climate adaptability in vernacular dwellings but also provides critical data support and a theoretical basis for the scientific preservation, adaptive renewal, and sustainable inheritance of vernacular architecture in the context of climate change.

As an integral component of humanity’s cultural heritage, traditional villages universally confront challenges such as population loss and cultural discontinuity amid rapid urbanization. Cluster-based protection models have increasingly become the international consensus for addressing the survival crisis of such settlements. This study selects the Central Yunnan region of Southwest China—characterized by its complex geography and multi-ethnic habitation—as the research area. Employing ArcGIS spatial analysis techniques alongside clustering algorithms, we examine the spatial distribution characteristics and clustering patterns of 251 traditional villages within this region. The findings are as follows. In terms of spatial distribution, traditional villages in Central Yunnan are unevenly dispersed, predominantly aggregating on mid-elevation gentle slopes; their locations are chiefly influenced by rivers and historical courier routes, albeit with only indirect dependence on waterways. Regarding single-cluster attributes, the spatial and geomorphological features exhibit a composite “band-and-group” pattern shaped by river valleys; culturally, two dominant modes emerge—“ancient-route-dependent” and “ethnic-symbiosis”—reflecting an economy-driven cultural mechanism alongside latent marginalization risks. Concerning construction characteristics, the “Qionglong-Ganlan” and Han-style “One-seal” residential features stand out, illustrating both adaptation to mountainous environments and the cumulative effects of historical culture. Based on these insights, we propose a three-tiered clustering classification framework—“comprehensive-element coordination”, “feature-led”, and “potential-cultivation”—to inform the development of contiguous and typological protection strategies for traditional villages in highland, multi-ethnic regions.

As climate challenges intensify, architectural design must reconcile energy efficiency with environmental adaptation. This study investigates how two skywell geometries in Kunming’s traditional One-Seal dwellings (Yikeyin) optimize seasonal thermal and ventilation performance. Combining field analysis and simulations, a comparative analysis of skywell depth-to-width ratios reveals that larger proportions enhance summer airflow but exacerbate winter heat loss, while smaller ratios stabilize winter conditions. Vertical thermal stratification highlights distinct microclimates across floors, with skywells exhibiting pronounced seasonal fluctuations. The findings affirm the climate-responsive intelligence embedded in vernacular architecture, demonstrating its relevance for contemporary sustainable design. By bridging traditional wisdom and modern green building practices, this work advances strategies for climate-resilient architecture and rural habitat enhancement, prioritizing both ecological balance and human comfort.

Urban rail transit systems significantly influence land use patterns in newly developed areas, yet their impact on spatial organization and functional characteristics remains understudied. This research examines Wuhan Metro Line 11, analyzing land use within an 800 m radius of stations using Point of Interest data, ArcGIS spatial analysis, and locational entropy methods. The study reveals three station types, i.e., single-function, mixed-function, and underdeveloped, each exhibiting distinct spatial differentiation patterns. On this basis, a novel “core-diffusion” model emerges, with the highest density of functional elements observed at approximately 600 m from station centers, challenging conventional proximity assumptions. Three spatial organization modes are identified: single-core independent in two-level axis, single-core continuous in single-level axis, and double-core continuous in two-level axis. These findings contribute to the Transit-Oriented Development literature, offering sustainable insights into optimizing land use around metro stations in rapidly urbanizing contexts. This study also provides a methodological framework applicable to similar urban environments, enhancing the understanding of the complex relationships between metro development and surrounding land use patterns. These results have significant implications for urban planning and policy-making, particularly in emerging economies seeking to balance transit efficiency with sustainable urban growth.

Coverage path planning (CPP) of multiple Dubins robots has been extensively applied in aerial monitoring, marine exploration, and search and rescue. Existing multi-robot coverage path planning (MCPP) research use exact or heuristic algorithms to address coverage applications. However, several exact algorithms always provide precise area division rather than coverage paths, and heuristic methods face the challenge of balancing accuracy and complexity. This paper focuses on the Dubins MCPP problem of known environments. Firstly, we present an exact Dubins multi-robot coverage path planning (EDM) algorithm based on mixed linear integer programming (MILP). The EDM algorithm searches the entire solution space to obtain the shortest Dubins coverage path. Secondly, a heuristic approximate credit-based Dubins multi-robot coverage path planning (CDM) algorithm is presented, which utilizes the credit model to balance tasks among robots and a tree partition strategy to reduce complexity. Comparison experiments with other exact and approximate algorithms demonstrate that EDM provides the least coverage time in small scenes, and CDM produces a shorter coverage time and less computation time in large scenes. Feasibility experiments demonstrate the applicability of EDM and CDM to a high-fidelity fixed-wing unmanned aerial vehicle (UAV) model.