A multi-modal social media data analysis framework: Exploring the complex relationships among urban environment, public activity, and public perception—A case study of Xi’an, China

Ecological Indicators, Год журнала: 2025, Номер 171, С. 113118 - 113118

Опубликована: Янв. 29, 2025

Язык: Английский

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Evaluating and Diagnosing Urban Function and Perceived Quality Based on Multi-Source Data and Deep Learning Using Dalian as an Example

Buildings, Год журнала: 2025, Номер 15(7), С. 998 - 998

Опубликована: Март 21, 2025

Currently, coordinated development in terms of perceived urban quality and function has become a key problem. However, there is an imbalance between the street environment amenities. It necessary to explore current status propose optimization strategies promote spaces. Dalian, China, was selected as study area. Based on space syntax, high-accessibility low-accessibility streets were sites. An evaluation system constructed part study. included quality. Data density diversity amenities obtained by establishing points interest (POIs). The subjective psychological perception calculated using view images (SVIs). Then, coupling analysis based conducted results indicated that differences levels regard spatial Dalian. Specifically, mainly concentrated central higher than streets. found had highest proportions advantage opportunity beauty lowest maintenance among improvement Openness As result analysis, this not only helps optimize layout improve environment, but also provides practical guidance for future design. Additionally, will help environments enhance overall livability environment.

Язык: Английский

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Nonlinear impacts of landscape and climatological interactions on urban thermal environment during a hot and rainy summer

Ecological Indicators, Год журнала: 2024, Номер 166, С. 112551 - 112551

Опубликована: Авг. 31, 2024

Investigating the nonlinear impacts of urban landscape and climatic parameters on temperatures, a critical issue within climatology. Chengdu, characterized by its hot, rainy summers rapid development, serves as an ideal model to illustrate these dynamics. Our investigation utilizes advanced analytical methods such Random Forests (RF), SHapley additive explanation (SHAP), Partial Dependence Plots (PDP) analyze how factors influence air temperature (AT) land surface (LST). Significant findings reveal profound thermal heterogeneity across Chengdu's fabric, underscored spatially distinct phenomena where some regions exhibit strong contrasts in due varying factors. The study identifies relative humidity rainfall key drivers variations during summer months, reflecting specific idiosyncrasies. These insights are critical, they highlight planning green infrastructure can be strategically used mitigate adverse effects. research not only enhances understanding complex interplays microclimates but also offers new perspectives heat management. It contributes scientific community providing evidence-based strategies for planners counter island effect enhance resilience against climate change. This comprehensive analysis underscores importance incorporating multiple variables into models, lays groundwork more refined environmental policies practices.

Язык: Английский

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Quantifying the Impact of Street Greening during Full-Leaf Seasons on Emotional Perception: Guidelines for Resident Well-Being

Forests, Год журнала: 2024, Номер 15(1), С. 119 - 119

Опубликована: Янв. 7, 2024

Quantifying the emotional impact of street greening during full-leaf seasons in spring, summer, and fall is important for well-being-focused urban construction. Current perception models usually focus on influence objects identified through semantic segmentation view images lack explanation. Therefore, interpretability that quantify greening’s effects are needed. This study aims to measure explain emotions help planners make decisions. would improve living environment, foster positive emotions, residents recover from negative emotions. In Hangzhou, China, we used Baidu Map API obtain when plants were state. Semantic was separate plant parts images, enabling calculation Green View Index, Plant Level Diversity, Color Richness, Tree–Sky Factor. We created a dataset specifically designed purpose perception, including four distinct categories: pleasure, relaxation, boredom, anxiety. generated combination machine learning algorithms human evaluation. Scores range 1 5, with higher values indicating stronger lower less intense ones. The random forest model Shapley Additive Explanation (SHAP) algorithm employed identify key indicators affect Emotions most affected by Diversity Index. These have an intricate non-linear relationship. Specifically, Index (often presence 20–35 fully grown trees within 200 m images) greater significantly promoted responses. Our provided local planning departments support renewal Based our research, recommend following actions: (1) increase amount visible green areas low Index; (2) seasonal flowering like camellia, ginkgo, goldenrain enhance diversity colors; (3) trim safety visibility; (4) introduce evergreen cinnamomum camphor, osmanthus, pine.

Язык: Английский

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Towards equal neighborhood evolution? A longitudinal study of soundscape and visual evolution and housing value fluctuations in shenzhen

Journal of Environmental Management, Год журнала: 2024, Номер 370, С. 122829 - 122829

Опубликована: Окт. 10, 2024

Язык: Английский

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Analyzing spatiotemporal truck emission pattern using explainable machine learning: A case study in Xi’an, China

Transportation Research Part D Transport and Environment, Год журнала: 2024, Номер 137, С. 104489 - 104489

Опубликована: Окт. 31, 2024

Язык: Английский

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Exploring tourists' perceptions of ecosystem services in national parks to guide the optimization of management

Journal of Cleaner Production, Год журнала: 2025, Номер unknown, С. 145134 - 145134

Опубликована: Фев. 1, 2025

Язык: Английский

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Research on the Nonlinear and Interactive Effects of Multidimensional Influencing Factors on Urban Innovation Cooperation: A Method Based on an Explainable Machine Learning Model

Systems, Год журнала: 2025, Номер 13(3), С. 187 - 187

Опубликована: Март 7, 2025

Within globalization, the significance of urban innovation cooperation has become increasingly evident. However, faces challenges due to various factors—social, economic, and spatial—making it difficult for traditional methods uncover intricate nonlinear relationships among them. Consequently, this research concentrates on cities within Yangtze River Delta region, employing an explainable machine learning model that integrates eXtreme Gradient Boosting (XGBoost), SHapley Additive exPlanations (SHAP), Partial Dependence Plots (PDPs) investigate interactive effects multidimensional factors impacting cooperation. The findings indicate XGBoost outperforms LR, SVR, RF, GBDT in terms accuracy effectiveness. Key results are summarized as follows: (1) Urban exhibits different phased characteristics. (2) There exist between factors, them, Scientific Technological dimension contributes most (30.59%) significant positive promoting effect later stage after surpassing a certain threshold. In Social Economic (23.61%), number Internet Users (IU) individually. Physical Space (20.46%) generally mutation points during early stages development, with overall predominantly characterized by trends. (3) Through application PDP, is further determined IU synergistic per capita Foreign Direct Investment (FDI), public library collections (LC), city night light data (NPP), while exhibiting negative antagonistic Average Annual Wage Staff (AAS) Enterprises above Designated Size Industry (EDS). (4) For at developmental stages, tailored development proposals should be formulated based single-factor contribution multifactor interaction effects. These insights enhance our understanding elucidate influencing factors.

Язык: Английский

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How to Quantify Multidimensional Perception of Urban Parks? Integrating Deep Learning-Based Social Media Data Analysis with Questionnaire Survey Methods

Urban forestry & urban greening, Год журнала: 2025, Номер unknown, С. 128754 - 128754

Опубликована: Март 1, 2025

Язык: Английский

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How do different ski resort attributes affect skiers' positive sentiments? Evidence from China

Journal of Destination Marketing & Management, Год журнала: 2025, Номер 36, С. 100998 - 100998

Опубликована: Март 12, 2025

Язык: Английский

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