Search Results (514)

While extensive research has examined the contribution of urban parks to well-being, empirical evidence on the role of cultural attributes in historical urban parks and their impact on visitors’ well-being remains limited. This study explores the impact of physical characteristics of historical urban parks on well-being from the perspective of human settlement environment. Quantitative data were collected from 11 urban parks in Wuhan, China, combining online crowdsourcing for physical characteristic assessments and questionnaire surveys for psychological evaluations. Machine learning techniques, spatial analysis, and statistical methods including multistep regression and Bootstrap sampling were employed to test our hypotheses. Our results demonstrate that objective physical features—including park area, green coverage rate, green space shape index, and the proportion of heritage landmarks—positively influence well-being, whereas road density exhibits a negative association. Cultural perception and place attachment serve as significant mediators between physical characteristics and well-being outcomes, with the proportion of heritage landmarks influencing well-being through a dual mediation path. Additionally, we found interaction effects between physical and psychological factors, with education level moderating the relationship between cultural perception and well-being. These findings advance environmental psychology theory by elucidating how historical elements foster unique pathways to well-being, distinct from those offered by conventional green spaces. Our research provides evidence-based guidance for historical urban park design and renovation in the context of urban renewal, where balancing preservation and modernization presents significant challenges. Full article

In the context of rural revitalization, scientific and efficient improvement of the human settlement environment is of great practical significance to improve the quality of life of farmers as well as to promote modern rural construction. To understand the research status and trends of human settlement environment improvement, the paper visually analyzed the relevant literature from 2012 to 2022 based on CNKI and the Web of Science database with the help of CiteSpace software(developed by Chaomei Chen, Drexel University, Philadelphia, PA, USA) (v6.2.r2). The results show the following: (1) the research literature on human settlement environment improvement has undergone three stages of slow growth, steady growth, and explosive growth; (2) many countries and institutions have published research on the improvement of human settlement environment, forming a close cooperative relationship; (3) three research hotspots have been formed: the concept and classification of the human settlement environment, the improvement path of the human settlement environment, and the evaluation method of the human settlement environment; and (4) waste management and green space are the frontier issues in the field of human settlement environment improvement. The subsequent research on the improvement of human settlement environments should strengthen the breadth and depth of research, improve the evaluation index system, innovate research methods, and build interdisciplinary integration, to provide a perfect research paradigm for research on the improvement of human settlement environments in the future. Full article

With the progression of global urbanization, UGS greenery plays an increasingly important role in encouraging engagement in various health-related activities among sedentary residents, and its quality improvement is widely recognized as a promising strategy for achieving public health benefits. However, existing studies have not reached an agreement on the associations between UGS greenery and engagement in health-related activities, largely due to limited dimensions of greenery measurement and insufficient evidence on health-related activities. To address these gaps, this study proposes a holistic analytical framework that integrates multi-dimensional greenery measurements (measured by the NDVI, GVI, and LVV metrics) with systematic observations of engagement in physical activity and social interaction across the general population, children, and seniors, allowing for a more comprehensive understanding of their varied associations. Conducting empirical research in the Xuanwu Lake Scenic Area, the results showed that (1) UGS greenery had stronger explanatory power for activity participant numbers than activity intensity across age groups; (2) top–down greenery (NDVI) was positively associated with engagement in health-related activities (although not statistically significant), while excessive eye-level (GVI) and spatial greenery (LVV) demonstrated negative effects; (3) UGS greenery alone did not sufficiently predict children’s engagement in health-related activities; and (4) greenery conditions in adjacent UGS samples also significantly impacted local health-related activities. These findings suggest that UGS greenery measured from a single dimension may not reliably predict engagement in health-related activities across age groups, thereby calling for balanced and context-sensitive greenery design in future UGS planning to support inclusive public health. Full article

This study investigates the socioeconomic determinants governing biomass energy transitions in rural areas of Eastern China through a multiregional spatial analysis. Drawing on time-series data from national and local statistical yearbooks, screened and processed to ensure consistency, the research analyzes evolving rural energy consumption patterns across nine cities in Heilongjiang, Jiangsu, and Guangdong provinces. Biomass energy potential was estimated by integrating crop production and domestic waste data with region-specific residue-to-product ratios, calorific values, and conversion efficiencies. These estimates were further spatialized through GIS-based surplus–deficit modeling to reveal regional disparities in supply–demand balance. The analysis identifies a critical income threshold, whereby lower-income regions exhibit rapid growth in energy consumption until reaching a saturation point around RMB 13,000, while higher-income areas experience continued increases in energy demand beyond the capacity of biomass resources to supply. The findings emphasize that an integrated approach, incorporating agricultural residue and domestic waste utilization, is essential for facilitating sustainable energy transitions, particularly in economically advanced regions. Furthermore, the study develops a scalable framework that integrates socioeconomic and spatial variables into biomass energy planning, underscoring the need for regional transition strategies to address not only resource endowments but also demographic mobility, urbanization dynamics, and income-driven consumption behaviors. Full article

Cities’ role as major hubs of human activity and economic development is essential in attaining sustainable development, fostering a balance between economic, social, and environmental development, especially in light of the growing concern over Anthropocene-induced environmental issues like global warming and climate change. The United Nations Sustainable Development Goals (SDGs) represent a historic call for coordinated international action in this area, with SDG 11 specifically identifying “Sustainable Cities and Communities” as a primary objective. Therefore, it is clear that a paradigm shift in our approach to these challenges in terms of our thinking, sensibility, behavior, and responses is necessary. Implicitly, in view of their pivotal role in environmental sustainability, development of “smart” cities as healthy, citizen-friendly, economically viable, and sustainable cities for our future generations in today’s globally integrated world, as predominant centers of human settlement and activity with multinational enterprises driving economic growth, gains the immediate attention of researchers. In this light, this study aims to identify and thereafter prioritize key indicators of a smart city using the structured and consistency-focused best–worst multi-criteria decision-making (BWM) method, suitable for expert-driven decision-making with limited comparisons. While the UN’s SDG 11 promotes safe and resilient cities, our findings suggest a disparity in how local officials prioritize certain dimensions such as safety or recreation. This disconnect warrants closer examination of localized policy drivers. The findings of this study indicate that according to experts, among others, the priority themes are, in order, water and sanitation, wastewater, health, the environment, and the economy. Thus, these represent a key take-away for multinational enterprises for identifying and assessing significant thrust domains and areas of opportunity for intervention and contribution to the UN SDGs. It also enables a replicable framework for synergy between the public and private sectors towards contrastive intervention in other cities across the globe. Full article

Since the reform and opening-up policy, the accelerated urbanization rate has triggered extensive construction of new towns, leading to architectural homogenization and environmental quality degradation. As urban development transitions toward a “quality improvement” paradigm, there is an urgent need to synergistically enhance the health performance of human settlements through the optimization of public space environments. The purpose of this study is to explore the impact of the built environment of urban streets on residents’ perceptions. In particular, in the context of rapid urbanization, how to improve the mental health and quality of life of residents by improving the street environment. Changbai Island Street in the Heping District of Shenyang City was selected for the study. Baidu Street View images combined with machine learning were employed to quantify physical characterizations like street plants and buildings. The ‘Place Pulse 2.0’ dataset was utilized to obtain data on residents’ perceptions of streets as beautiful, safe, boring, and lively. Correlation and regression analyses were used to reveal the relationship between physical characteristics such as green visual index, openness, and pedestrians. It was discovered that the green visual index had a positive effect on perceptions of it being beautiful and safe, while openness and building enclosure factors influenced perceptions of it being lively or boring. This study provides empirical data support for urban planning, emphasizing the need to focus on integrating environmental greenery, a sense of spatial enclosure, and traffic mobility in street design. Optimization strategies such as increasing green coverage, controlling building density, optimizing pedestrian space, and enhancing the sense of street enclosure were proposed. The results of the study not only help to understand the relationship between the built environment of streets and residents’ perceptions but also provide a theoretical basis and practical guidance for urban space design. Full article

Rapid urbanization is forcing the need to build urban environments that promote healthy and sustainable human settlements with a view to reducing the risks of various diseases. Previous studies have demonstrated that green rooftop spaces may stimulate restorative benefits and enhance their livability. However, this potential remains without empirical research support. To investigate the restoration of green rooftop spaces on human well-being, we conducted a field experiment using psychophysiology measurements. With the help of physiological indicators (SBP, DBP, HR, HRV) and psychological indicators (PRS, BPOMS), the changes of indicators in the experiment were analyzed. We recruited a total of 35 college students who were randomly assigned to one of four rooftop spaces for a field experiment. Physiological and psychological indicators were measured before and after recovery to analyze the effects of rooftop spaces on restorative benefits. Paired sample t-test results revealed that although there were differences in the physiological and psychological measurements related to environmental restorative benefits, both confirmed that green rooftop spaces exhibited stress-reduction effects on participants. Notably, all four rooftop spaces had psychophysiological restoration to varying degrees, with spaces featuring a higher degree of naturalness demonstrating better restoration. Furthermore, a grassy environment had effects on positive psychophysiological responses. Correlation analysis indicated that subjective perception evaluations of green rooftop spaces had positive effects on psychophysiological restoration. The results of the study are conducive to increasing awareness of the restorative value and potential of green rooftop spaces, which can be constructed by designers, thereby contributing to sustainable urban development. Full article

The environmental quality of rail transit spaces has increasingly attracted attention, as factors such as train noise and visual disturbances from elevated lines can impact pedestrians’ psychological perception through the audiovisual environment in these spaces. This study first collects audiovisual materials from rail transit spaces and pedestrian perception data through on-site surveys, measurements, VR environment simulations, and custom Deep Learning (DL) models. Using cluster analysis, the environments are categorized based on visual and auditory perceptions and evaluations of rail transit stations, delineating and classifying the spaces into different zones. The study further explores the interactive effects of audiovisual environmental factors on psychological perception within these zones. The results indicate that, based on audiovisual perception, the space within 300 m of a rail transit station can be divided into three zones and four distinct types of audiovisual perception spaces. The effect of the type of auditory environment on visual indicators was smaller than the effect of the visual environment on auditory indicators, and the category of vision had the greatest effect on the subjective indicators of hearing within Zones 1 and 2. This study not only provides a scientific basis for improving the environmental quality of rail transit station areas but also offers new perspectives and practical approaches for urban transportation planning and design. Full article

Earthquakes and the secondary hazards they trigger, such as landslides, collapses, and debris flows, profoundly reshape the land surface and cause significant casualties, property damage and ecological disruption. This study collected 312 strong ground motion records from 19 seismic events in China, with magnitudes ranging from Ms5.2 to Ms8.0. Using the Newmark sliding block method and programming, permanent displacements for earthquake-induced landslides with varying yield accelerations were calculated. Two models (Model 1 and Model 2) for predicting permanent displacements of earthquake-induced landslides were developed through multiple regression analysis. Results show that the goodness of fit (R²) for the permanent displacement (logu) in Model 1 and Model 2 is 0.866 and 0.923, respectively. Model 2 incorporates higher-order terms of yield acceleration ratio (a_y/PGA), which effectively reduce nonlinearity in the residuals observed in Model 1 and enhance its accuracy. Finally, these models were compared with classical empirical models. Models 1 and 2, by calculating permanent displacement from ground motion data, provide critical insights into the mechanisms of earthquake-induced landslides, and play a key role in enhancing emergency response strategies for seismic geological hazards. Full article

According to the China Building Energy Consumption and Carbon Emissions Research Report (2023), the construction industry accounts for 36.3% of total societal energy consumption, with residential buildings contributing significantly due to their extensive coverage and high operational frequency. Addressing energy efficiency and carbon reduction in this sector is critical for achieving national sustainability goals. This study proposes an optimization methodology for rural dwellings in Inner Mongolia, focusing on reducing energy demand while enhancing indoor thermal comfort and daylight performance. A parametric model was developed using Grasshopper, with energy consumption, thermal comfort (PPD), and Useful Daylight Illuminance (UDI) simulated through Ladybug and Honeybee tools. Key parameters analyzed include building morphology, envelope structures, and indoor thermal environments, followed by systematic optimization of building components. To refine multi-objective inputs, a specialized wall database was established, enabling categorization and dynamic visualization of material properties and construction methods. Comparative analysis demonstrated a 22.56% reduction in energy consumption, 19.26% decrease in occupant thermal dissatisfaction (PPD), and 25.44% improvement in UDI values post-optimization. The proposed framework provides a scientifically validated approach for improving energy efficiency and environmental adaptability in cold-climate rural architecture. Full article

This study examines the relative sea-level changes during the Upper Holocene period along the south coastline of Cyprus through the investigation of beachrock formations and their impact on archaeological sites. Beachrock, as a natural indicator of past relative sea levels, provides valuable insights into the dynamic interplay between sea-level fluctuations and human settlements. The research integrates field observations, mineralogical and geochemical analysis, geochronological studies, and archaeological data to reconstruct past sea-level variations and their implications for coastal archaeological sites. The results reveal significant fluctuations in relative sea levels during the Upper Holocene, influencing the development and occupation of coastal archaeological sites. By elucidating the complex relationship between sea-level changes and human activity, this study contributes to our understanding of past coastal environments and their socio-cultural dynamics. Moreover, it underscores the importance of considering geological factors in archaeological interpretations and coastal management strategies in the face of contemporary sea-level rise. Full article

The inappropriate thermal conditions resulting from increasingly severe climate issues have led to numerous complications for urban residents, decreased urban settlement comfort, and increased average and peak energy demands in built environments. Existing studies have demonstrated the significant influence of urban morphology (UM) on the urban thermal environment (UTE); however, at the meso-scale and macro-scale, UTE is often simplified to land surface temperature (LST) and building surface temperatures. To investigate the impact of UM on UTE, we developed an evaluation framework consisting of thermal sensing feedback (TSF) and LST. We employed the seven-level TSF scale to evaluate TSF data obtained from the Internet, emphasizing individualized thermal perceptions of urban spaces and reorienting UTE research towards a human-centric perspective. Using a regression model, we examined the relationships between two-dimensional and three-dimensional UM variables and UTE at the meso-scale in the central urban area of Shanghai, China, during August and December 2024. The results indicated the following: (1) The normalized difference vegetation index (NDVI), building density (BD), floor area ratio (FAR), impervious surface index (ISI), building height (BH), average building volume (ABV), sky view fraction (SVF), and building shape (BS_sh) effectively explained TSF. However, area weighted mean shape index (SHAPE_AM), aggregation index (AI), edge density (ED), elevation, building spacing (BS_sp), and spatial congestion degree (SCD) showed no significant correlation with TSF. (2) Significant variables, including NDVI, FAR, ISI, UM, BD, and BH, exhibited opposite effects on cold perception in winter compared to heat perception in summer, indicating a consistent influence on thermal perception across seasons. (3) In summer, the significant variables SVF, BS_sh, and ISI showed opposite effects on TSF and LST, while in winter, FAR demonstrated contrasting impacts on TSF and LST. The results of this study advance understanding of the mechanisms through which UM influences UTE, providing valuable insights for the development of sustainable, thermally comfortable urban environments. Full article

The building sector, responsible for 40% of global energy consumption, faces increasing demands for sustainability and energy efficiency. Accurate energy consumption forecasting is essential to optimise performance and reduce environmental impact. This study introduces a hybrid machine learning framework grounded in Sparse, Interpretable, and Transparent (SIT) modelling to enhance building energy management. Leveraging the REFIT Smart Home Dataset, the framework integrates occupancy pattern analysis, appliance-level energy prediction, and probabilistic uncertainty quantification. The framework clusters occupancy-driven energy usage patterns using K-means and Gaussian Mixture Models, identifying three distinct household profiles: high-energy frequent occupancy, moderate-energy variable occupancy, and low-energy irregular occupancy. A Random Forest classifier is employed to pinpoint key appliances influencing occupancy, with a drop-in accuracy analysis verifying their predictive power. Uncertainty analysis quantifies classification confidence, revealing ambiguous periods linked to irregular appliance usage patterns. Additionally, time-series decomposition and appliance-level predictions are contextualised with seasonal and occupancy dynamics, enhancing interpretability. Comparative evaluations demonstrate the framework’s superior predictive accuracy and transparency over traditional single machine learning models, including Support Vector Machines (SVM) and XGBoost in Matlab 2024b and Python 3.10. By capturing occupancy-driven energy behaviours and accounting for inherent uncertainties, this research provides actionable insights for adaptive energy management. The proposed SIT hybrid model can contribute to sustainable and resilient smart energy systems, paving the way for efficient building energy management strategies. Full article

The informal city, also known as the clandestine city and usually associated with the phenomenon of urban self-organisation, is a reality that cuts across all societies today and occurs in the most diverse regions of the globe, which raises the following question: Why do such different cultures, in such different geographies, adopt a common idea of an ‘informal city’ to live in? Despite the dramatic human condition that characterises slums and informal settlements, it is challenging to understand how these settlements can be adopted as a living space for so many and such diverse populations, admitting the interpretation that it is a utopia and an urban idealisation. Informal urbanisation processes occur outside the system and on the fringes of the practice of ‘institutional urban planning’, as a necessary and immediate response to the absence of public land policies, housing market failures or situations arising from social and economic crises. The object of this study is to find out to what extent the configuration of space, the territorialisation model and the morphology of the informal city, characterised by an entropic urbanism, correspond to an urban organisational structure that occurs when it is up to society to provide its own habitat and urban environment. Full article

Humanity’s long-term presence in space entails the establishment of sustainable space ecosystems in both orbital and planetary environments. Sustainable ecosystems are characterized by minimal resource depletion, reduction in space debris, reusable and renewable materials and components, among other factors. However, achieving sustainability in space is challenging due to limited resources, harsh environmental conditions, and the need for continuous operation. Intelligent robotic systems with diverse manipulation and locomotion capabilities using artificial intelligence (AI) are capable of In-Situ Resource Utilization and carrying out autonomous production and maintenance operations. Modular reconfigurable systems and heterogeneous teams allow for optimized task allocation strategies, thus expanding the task domain. Efficient human–robot interaction methods can assist astronauts and future space inhabitants in their routine tasks as well as during critical missions. We also emphasize the importance of collaboration among space agencies, roboticists and AI scientists for shared resources and knowledge, and the development of technology standards and interfaces for systems collaboration. Such cooperative efforts are vital to ensure the long-term viability of space exploration and settlement. This paper explores how AI-driven autonomous robots are being developed at the German Research Center for Artificial Intelligence and University of Bremen (Germany) to address these challenges. Full article