Intelligent Mining of Urban Ventilation Corridors Based on High-Precision Oblique Photographic Images

With the advancement of urbanization and the impact of industrial pollution, the issue of urban ventilation has attracted increasing attention. Research on urban ventilation corridors is a hotspot in the field of urban planning. Traditional studies on ventilation corridors mostly focus on qualitativ...

Full description

Saved in:
Bibliographic Details
Published inSensors (Basel, Switzerland) Vol. 21; no. 22; p. 7537
Main Authors Chen, Chaoxiang, Ye, Shiping, Bai, Zhican, Wang, Juan, Zhang, Zongbiao, Ablameyko, Sergey
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 12.11.2021
MDPI
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:With the advancement of urbanization and the impact of industrial pollution, the issue of urban ventilation has attracted increasing attention. Research on urban ventilation corridors is a hotspot in the field of urban planning. Traditional studies on ventilation corridors mostly focus on qualitative or simulated research on urban climate issues such as the intensified urban heat island effect, serious environmental pollution, and insufficient climate adaptability. Based on the high-precision urban remote sensing image data obtained by aeromagnetic oblique photography, this paper calculates the frontal area density of the city with reference to the urban wind statistics. Based on the existing urban patterns, template matching technology was used to automatically excavate urban ventilation corridors, which provides scientific and reasonable algorithmic support for the rapid construction of potential urban ventilation corridor paths. It also provides technical methods and decision basis for low-carbon urban planning, ecological planning and microclimate optimization design. This method was proved to be effective through experiments in Deqing city, Zhejiang Province, China.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1424-8220
1424-8220
DOI:10.3390/s21227537