Search Results (7)

Urban happiness prediction presents a complex challenge, due to the nonlinear and multifaceted relationships among socio-economic, environmental, and infrastructural factors. This study introduces an advanced hybrid model combining a gradient boosting machine (GBM) and neural network (NN) to address these complexities. Unlike traditional approaches, this hybrid leverages a GBM to handle structured data features and an NN to extract deeper nonlinear relationships. The model was evaluated against various baseline machine learning and deep learning models, including a random forest, CNN, LSTM, CatBoost, and TabNet, using metrics such as RMSE, MAE, R², and MAPE. The GBM + NN hybrid achieved superior performance, with the lowest RMSE of 0.3332, an R² of 0.9673, and an MAPE of 7.0082%. The model also revealed significant insights into urban indicators, such as a 10% improvement in air quality correlating to a 5% increase in happiness. These findings underscore the potential of hybrid models in urban analytics, offering both predictive accuracy and actionable insights for urban planners. Full article

The acceleration of urbanization has resulted in a heightened awareness of the impacts of urban environments on residents’ emotional states. This present study focuses on the Lixia District of Jinan City. By using urban street view big data and deep learning methods, we undertook a detailed analysis of the impacts of urban color features on residents’ emotional perceptions. In particular, a substantial corpus of street scene image data was extracted and processed. This was performed using a deep convolutional neural network (DCNN) and semantic segmentation technology (PSPNet), which enabled the simulation and prediction of the subjective perception of the urban environment by humans. Furthermore, the color complexity and coordination in the street scene were quantified and combined with residents’ emotional feedback to carry out a multi-dimensional analysis. The findings revealed that color complexity and coordination were significant elements influencing residents’ emotional perceptions. A high color complexity is visually appealing, but can lead to fatigue, discomfort, and boredom; a moderate complexity stimulates vitality and pleasure; high levels of regional harmony and aesthetics can increase perceptions of beauty and security; and low levels of coordination can increase feelings of depression. The environmental characteristics of different areas and differences in the daily activities of residents resulted in regional differences regarding the impacts of color features on emotional perception. This study corroborates the assertion that environmental color coordination has the capacity to enhance residents’ emotions, thereby providing an important reference point for urban planning. Planning should be based on the functional characteristics of the region, and color complexity and coordination should be reasonably regulated to optimize the emotional experiences of residents. Differentiated color management enhances urban aesthetics, livability, and residents’ happiness and promotes sustainable development. In the future, the influences of color and environmental factors on emotions can be explored in depth, with a view to assist in the formulation of fine urban design. Full article

The campus environment directly impacts college students’ psychological and emotional well-being, influencing their behavioral performance and the development of their personalities. Investigating the complex relationship between the campus spatial environment and students’ emotions is crucial for designing urban environments that support mental health. Using Yuelu Mountain National University Science and Technology City as a case study, this research developed a framework to analyze campus environment characteristics and emotional perception. The study quantitatively assessed emotional perceptions, examined the specific contributions of different campus environment elements to individual emotions, and created an emotion prediction map to explore these relationships in depth. The results indicate that “campus greenery” and “diversity” negatively affect “disappointment” and “depression”, while “sky views” positively impact “happiness” and “sense of security”. Additionally, “diversity” positively affects “relaxation”, and “campus greenery” and “diversity” have negative effects on “disappointment” and “depression”, with “diversity” having a particularly strong positive effect on “relaxation”. The pronounced spatial clustering of emotional perceptions on campus further underscores the significant influence of the campus environment on individual emotional experiences. As the first study to explore the mechanisms underlying the emotional perceptions of Chinese college students in relation to the campus environment, this research overcomes the limitations of traditional environmental assessment indicators by identifying campus environmental elements and psychological factors that better align with the psychological needs of college students. This provides a scientific basis for optimizing campus environments based on the emotional perceptions of students, thereby supporting mental health promotion and guiding campus environment construction. Moreover, the research methodology is broadly applicable. The integration of campus environment image data and deep learning offers a significant tool for assessing campus space and environmental perception, thereby enhancing human-centered environmental assessment and prediction while more accurately reflecting architectural space perception. Full article

Because adolescent leisure is important to development, we consider its role in Portuguese adolescent wellbeing. Data for this study came from 303 adolescents in grades 10, 11, and 12 living in a large urban area in northern Portugal. Self-report data were collected in classrooms using a cross-sectional design in two urban high schools. Hypothesis testing used seven hierarchical linear regression models. Except for subjective happiness, experiencing boredom in leisure and/or the ability to make a boring situation more interesting were strong predictors of each wellbeing experience in the predicted direction. Perceptions of healthy leisure were associated with higher levels of life satisfaction, subjective happiness, self-esteem, and positive affect. Active leisure was important to adolescent self efficacy and positive affect. Those who could restructure a boring situation into something more interesting exhibited higher levels of wellbeing experience. Adolescents who perceived parental autonomy control were more likely to experience boredom in leisure. Full article

(1) Background: Research indicates that most elderly widows are at a high risk of experiencing negative psychological symptoms. It is common for elderly women in rural and remote areas to live alone without family support to cope with stress due to the mass rural-to-urban migration of China’s youth labor force. Such a situation further worsens their psychological health and well-being. However, the prevalence of and risk factors associated with negative psychological symptoms (loneliness, depression, and anxiety) among remote elderly widows living alone in China are currently unclear; (2) Methods: A cross-sectional study was conducted in Hunan Province, China. The loneliness was assessed through the University of California at Los Angeles Loneliness Scale (ULS-8). The depression and anxiety were assessed with the Short Form Geriatric Depression Scale (GDS-15) and Generalized Anxiety Disorder Scale (GAD-7), respectively. The Chi-square test and correlation analysis were conducted to identify factors associated with negative psychological symptoms. Logistic regression was performed to predict risk and protective factors contributing to loneliness, depression, and anxiety symptoms. The significance level was set as p < 0.05; (3) Results: A total of 271 remote elderly widows living alone were enrolled in the present study. Additionally, 234 valid questionnaires were returned (valid response rate = 86.3%). The prevalence of loneliness, depression and anxiety was 8.1%, 44.0%, and 16.7%, respectively. Acute or chronic medical conditions, marital happiness, being the primary caregiver before widowhood and anticipating the death of the spouse differed significantly in the distribution of negative psychological symptoms. Logistic regression analysis predicted that participants who were satisfied with their marriage had a lower likelihood to experience loneliness, depression, and anxiety (p < 0.05). Being the spouse’s primary caregiver before widowhood was more likely to have symptoms of loneliness (p < 0.01). Those with various acute or chronic medical conditions were more likely to suffer from depression (p < 0.01); (4) Conclusions: Remote elderly widows living alone in China are prone to loneliness, depression, and anxiety symptoms. Being the primary caregiver before widowhood and having many acute or chronic medical conditions are risk factors for loneliness and depression, respectively. Marital happiness is the protective factor against negative psychological symptoms. To accomplish the goal of equitable access to mental health care in China, evidence-based policy and resource development to support psycho-social interventions that prevent and manage negative psychological symptoms for remote elderly widows living alone are urgently needed. Full article

Interacting with urban spaces that are green and blue is believed to promote mental well-being and positive emotions. Therefore, there is an incentive to strategically design urban forest landscapes in a given space to evoke more positive emotion. In this study, we conducted a pilot study in Northeast China with 24 parks from 11 cities across 3 provinces. The subjects of the study are the visitors and a total of 1145 photos and selfies were collected from open micro-twitters in Sino Weibo (~50 individuals per park). Facial expressions of happy and sad emotions were recognized and rated as percent scores by FireFACE v1.0. Demographically, male adolescents smiled more than male visitors in other age groups and female teens. Females expressed more positive emotions than males according to their positive response index (PRI; happy-sad). Multivariate linear regression indicated positive contribution of green space to happy scores (estimate of 0.0040) and a stronger negative contribution of blue area to sad scores (estimate of −0.1392). Therefore, an urban forest landscape can be optimized by mapping green- and blue-spaces to predict spatial distributions of positive emotions. Male teens are recommended more as frequent visitors than people in other age ranges. Full article

Urbanization deletes and degrades natural ecosystems, threatens biodiversity, and alienates people from the experience of nature. Nature-based solutions (NbS) that are inspired and supported by nature have the potential to deliver multifunctional environmental and social benefits to address these challenges in urban areas under context-specific conditions. NbS implementation often relies on a one-size-fits-all approach, although interventions that maximize one benefit (e.g., biodiversity conservation) may have no influence on, or even negatively affect, others (e.g., social justice). Furthermore, the current pathways from NbS to various benefits do not rely on a deep understanding of the underlying processes, prohibiting the identification of optimal solutions that maximize synergies across pathways. We present a comprehensive socio-ecological framework that addresses these issues by recognizing that cities are human-dominated environments that are foremost built and maintained to support humans. Our framework demonstrates how we can use experiments and niche species models to understand and predict where species will be and where people will be healthy and happy in a comparable manner. This knowledge can then be integrated into decision support tools that use optimization algorithms to understand trade-offs, identify synergies, and provide planners with the tools needed to tailor context-specific NbS to yield greener, more resilient cities with happier people and reduced inequality. Full article