AI-Driven Framework for Assessing Visitor Perceptions in Historic Urban Areas Using Social Media DOI
Wei Chen, Kai Zhou, Hu Bin

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 22, 2025

Abstract As urbanization progresses, preserving and adapting historical districts for sustainable development is crucial. These areas embody significant cultural heritage contribute to economic, social, sustainability. However, research on visitor perceptions, particularly spatial satisfaction, limited, especially in fine-grained analyses using social media data. This study introduces a framework evaluating perceptions Aspect-Based Sentiment Analysis (ABSA) enhanced by BO-DXGBoost model, cascaded system combining two XGBoost models fine-tuned through Bayesian Optimization (BO). The first model identifies aspect categories, while the second analyzes sentiment polarity intensity. Class imbalance addressed ADASYN RF-SMOTE, SHAP analysis visualizes feature influences predictions. provides quantitative insights into of offers robust approach management integration

Language: Английский

The impact of urban morphology on land surface temperature under seasonal and diurnal variations: marginal and interaction effects DOI

Zi Wang,

Rui Zhou, Yu Yang

et al.

Building and Environment, Journal Year: 2025, Volume and Issue: unknown, P. 112673 - 112673

Published: Feb. 1, 2025

Language: Английский

Citations

2
The Impact of Urban Spatial Forms on Marine Cooling Effects in Mainland and Island Regions: A Case Study of Xiamen, China DOI

Yuanping Shen,

Qiaqia Zhang,

Qunyue Liu

et al.

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106210 - 106210

Published: Feb. 1, 2025

Language: Английский

Citations

2
Impacts of Land Surface Temperature and Ambient Factors on Near-Surface Air Temperature Estimation: A Multisource Evaluation Using SHAP Analysis DOI
Songyang Li, Man Sing Wong, Rui Zhu

et al.

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106257 - 106257

Published: Feb. 1, 2025

Language: Английский

Citations

0
Impact Mechanisms of 2D and 3D Spatial Morphologies on Urban Thermal Environment in High-Density Urban Blocks: A Case Study of Beijing's Core Area DOI

Guo Jin Tang,

Xintong Du,

Siyuan Wang

et al.

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106285 - 106285

Published: March 1, 2025

Language: Английский

Citations

0
Carbon Emission Characteristics Research of Typical Drinking Water Treatment Plants in South China Based on Machine Learning Models DOI
Zexing Li,

Yueguang Lv,

Lingfei Zhang

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0
Field measurement and CFD simulation study on UHI in high-density blocks of Shanghai based on street canyons DOI
Deng Ying, Xiangfei Kong,

Haizhu Zhou

et al.

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106302 - 106302

Published: March 1, 2025

Language: Английский

Citations

0
Nonlinear Effects of Human Settlements on Seasonal Land Surface Temperature Variations at the Block Scale: A Case Study of the Central Urban Area of Chengdu DOI Creative Commons

Muze Zhang,

Tong Hou, Yuping Ma

et al.

Land, Journal Year: 2025, Volume and Issue: 14(4), P. 693 - 693

Published: March 25, 2025

The land surface temperature (LST) in the central urban area has shown a consistent upward trend over years, exacerbating heat island (SUHI) effect. Therefore, this study focuses on of Chengdu, using blocks as research scale. Gradient Boosting Decision Tree (GBDT) model and SHAP values are employed to explore nonlinear effects human settlements (HS) LST across different seasons. results show that (1) At block scale, overall impact HS all four seasons tracks following order: built environment (BE) > landscape pattern (LP) socio-economic development (SED). (2) LP is most important factor affecting summer, while BE greatest influence during spring, autumn, winter. (3) Most indicators exhibit seasonal variations their LST. impervious (ISA) exhibits significant positive autumn. In contrast, nighttime light index (NTL) functional mix degree (FMD) exert negative Additionally, normalized difference vegetation (NDVI) negatively affects both spring summer. Moreover, connectivity (CNT) density (FPD) demonstrate notable threshold (4) Certain interaction effects, some combinations these can effectively reduce This reveals HS–LST interactions through multidimensional analysis, offering block-scale planning strategies for sustainable thermal optimization.

Language: Английский

Citations

0
Precise Mitigation Strategies for Urban Heat Island Effect in Hong Kong's New Towns using Automated Machine Learning DOI Creative Commons
Yiyan Li, Hongsheng Zhang, Yinyi Lin

et al.

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106350 - 106350

Published: April 1, 2025

Language: Английский

Citations

0
Interpreting complex relationships between urban and meteorological factors and street-level urban heat islands: Application of random forest and SHAP method DOI

Tageui Hong,

Steve Hung Lam Yim,

Yeonsook Heo

et al.

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106353 - 106353

Published: April 1, 2025

Language: Английский

Citations

0
AI-Driven Framework for Assessing Visitor Perceptions in Historic Urban Areas Using Social Media DOI
Wei Chen, Kai Zhou, Hu Bin

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 22, 2025

Abstract As urbanization progresses, preserving and adapting historical districts for sustainable development is crucial. These areas embody significant cultural heritage contribute to economic, social, sustainability. However, research on visitor perceptions, particularly spatial satisfaction, limited, especially in fine-grained analyses using social media data. This study introduces a framework evaluating perceptions Aspect-Based Sentiment Analysis (ABSA) enhanced by BO-DXGBoost model, cascaded system combining two XGBoost models fine-tuned through Bayesian Optimization (BO). The first model identifies aspect categories, while the second analyzes sentiment polarity intensity. Class imbalance addressed ADASYN RF-SMOTE, SHAP analysis visualizes feature influences predictions. provides quantitative insights into of offers robust approach management integration

Language: Английский

Citations

0