Tianshun Gu
Datos Biográficos
| ID | 4417731 |
|---|---|
| NOMBRE | Tianshun Gu |
| NOMBRES | Tianshun |
| APELLIDO | Gu |
| FIRMA | GU T |
| AFILIACIONES | China University of Geosciences |
| ORCID | 0000-0001-6359-8028 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 6 |
| TOTAL DE CITAS | 2 |
| TOTAL COMO AUTOR | 6 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2024 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2026 |
| ÍNDICE H | 1 |
Reshaping inequalities in subjective well-being across multiple urban contexts
Against the backdrop of widening intra-urban disparities in well-being, a core challenge lies in identifying and regulating environment-related well-being indicators across multiple urban settings in ways that respond to heterogeneous resident needs and enhance perceived fairness. This study innovatively incorporates inequality in subjective well-being (SWB) as a feedback mechanism into the regulation framework of objective urban well-being (OUW)…
Unveiling flood resilience anomalies in urban blocks using an explainable spatial intelligence framework
Unveiling the spatial heterogeneity of factors influencing physical and perceived recovery disparities under extreme rainstorms
Attribution analysis of urban social resilience differences under rainstorm disaster impact
With the frequent occurrence of extreme rainstorms in global cities, understanding differences in social resilience is crucial for constructing climate-adaptive communities. However, quantitatively analyzing the compound effects and interactions of social resilience determinants remains challenging. Here, we developed an advanced interpretable spatial machine learning framework to analyze social resilience across 2,221 blocks in Zhengzhou City, C…
Spatial heterogeneity of urban resilience
Unraveling the factors behind self-reported trapped incidents in the extraordinary urban flood disaster
Unraveling the factors behind self-reported trapped incidents in the extraordinary urban flood disaster
Unveiling the spatial heterogeneity of factors influencing physical and perceived recovery disparities under extreme rainstorms
Attribution analysis of urban social resilience differences under rainstorm disaster impact
With the frequent occurrence of extreme rainstorms in global cities, understanding differences in social resilience is crucial for constructing climate-adaptive communities. However, quantitatively analyzing the compound effects and interactions of social resilience determinants remains challenging. Here, we developed an advanced interpretable spatial machine learning framework to analyze social resilience across 2,221 blocks in Zhengzhou City, C…
Spatial heterogeneity of urban resilience
Reshaping inequalities in subjective well-being across multiple urban contexts
Against the backdrop of widening intra-urban disparities in well-being, a core challenge lies in identifying and regulating environment-related well-being indicators across multiple urban settings in ways that respond to heterogeneous resident needs and enhance perceived fairness. This study innovatively incorporates inequality in subjective well-being (SWB) as a feedback mechanism into the regulation framework of objective urban well-being (OUW)…
Unveiling flood resilience anomalies in urban blocks using an explainable spatial intelligence framework
Disaster Management and Resilience (4 obras) · Flood Risk Assessment and Management (4 obras) · Geography (3 obras) · Computer Science (2 obras) · Environmental planning (2 obras) · Environmental resource management (2 obras) · Environmental Science (2 obras) · Flood myth (2 obras) · Land Use and Ecosystem Services (2 obras) · Urban resilience (2 obras)