Author
Listed:
- Fang Pei
(School of Economics and Management, Civil Aviation Flight University of China, Guanghan 618307, China
Sichuan Provincial Engineering Research Center of Smart Operation and Maintenance of Civil Aviation Airports, Guanghan 618307, China)
- Xiantao Chen
(School of Economics and Management, Civil Aviation Flight University of China, Guanghan 618307, China)
- Yongzhong Mu
(School of Economics and Management, Civil Aviation Flight University of China, Guanghan 618307, China)
- Cheng Pei
(Airport College, Civil Aviation Flight University of China, Guanghan 618307, China)
- Jiadong Zeng
(College of Civil Engineering and Architecture, Hainan University, Haikou 570228, China)
Abstract
Coastal cities exposed to extreme wind events are facing increasing challenges in emergency management under climate change. Accurate and high-resolution wind environment information over complex urban terrain is essential for disaster risk assessment and evidence-based emergency planning; however, such information is often unavailable in conventional management practices. This study proposes an integrated UAV–CFD framework to support urban wind risk assessment by combining multi-source geospatial data and high-resolution numerical simulation. A refined urban terrain model with a spatial resolution of 0.5 m was constructed through the fusion of Google Earth data and UAV oblique photogrammetry, and subsequently coupled with a computational fluid dynamics (CFD) model to analyze the urban wind environment. Field measurements obtained from a 50 m wind observation tower were used to validate the simulation results. The results reveal significant wind speed amplification caused by complex terrain and building configurations, with a maximum amplification factor of 1.95 due to the canyon effect. The relative errors between simulated and measured wind speeds and turbulence intensity were generally within 15%, demonstrating the reliability of the proposed framework. By providing high-resolution and spatially explicit wind risk information, this study offers practical decision-support for emergency management, urban planning, and resilience-oriented disaster mitigation in coastal cities.
Suggested Citation
Fang Pei & Xiantao Chen & Yongzhong Mu & Cheng Pei & Jiadong Zeng, 2026.
"High-Resolution Urban Wind Risk Assessment for Emergency Management Using UAV–CFD Integrated Modeling,"
Sustainability, MDPI, vol. 18(7), pages 1-17, March.
Handle:
RePEc:gam:jsusta:v:18:y:2026:i:7:p:3268-:d:1907580
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:18:y:2026:i:7:p:3268-:d:1907580. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.