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dc.contributor.authorChen, C.-
dc.contributor.authorYe, Sh.-
dc.contributor.authorBai, Z.-
dc.contributor.authorJuan, W.-
dc.contributor.authorZongbiao, Z.-
dc.contributor.authorAblameyko, S.-
dc.date.accessioned2022-11-08T11:52:27Z-
dc.date.available2022-11-08T11:52:27Z-
dc.date.issued2021-
dc.identifier.citationSensors 2021;21(22)ru
dc.identifier.urihttps://elib.bsu.by/handle/123456789/288421-
dc.description.abstractWith 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 highprecision 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. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/)ru
dc.description.sponsorshipFunding: This research was funded by Zhejiang Province Basic Public Welfare Research Program Project,grant number LGJ19F020002.ru
dc.language.isoenru
dc.publisherMDPIru
dc.rightsinfo:eu-repo/semantics/openAccessru
dc.subjectЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Кибернетикаru
dc.subjectЭБ БГУ::ТЕХНИЧЕСКИЕ И ПРИКЛАДНЫЕ НАУКИ. ОТРАСЛИ ЭКОНОМИКИ::Автоматика. Вычислительная техникаru
dc.subjectЭБ БГУ::ТЕХНИЧЕСКИЕ И ПРИКЛАДНЫЕ НАУКИ. ОТРАСЛИ ЭКОНОМИКИ::Жилищно-коммунальное хозяйство. Домоводство. Бытовое обслуживаниеru
dc.titleIntelligent mining of urban ventilation corridors based on high‐precision oblique photographic imagesru
dc.typearticleru
dc.rights.licenseCC BY 4.0ru
dc.identifier.DOI10.3390/s21227537-
dc.identifier.scopus85118891515-
Располагается в коллекциях:Кафедра веб-технологий и компьютерного моделирования (статьи)

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