J
Jun Yang
Researcher at Liaoning Normal University
Publications - 80
Citations - 3185
Jun Yang is an academic researcher from Liaoning Normal University. The author has contributed to research in topics: Environmental science & Urban heat island. The author has an hindex of 22, co-authored 60 publications receiving 1597 citations. Previous affiliations of Jun Yang include Chinese Academy of Sciences & Northeastern University (China).
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Chaotic Dynamics in Smart Grid and Suppression Scheme via Generalized Fuzzy Hyperbolic Model
TL;DR: In this article, a method to control chaotic behavior of a typical Smart Grid based on generalized fuzzy hyperbolic model (GFHM) is presented, which is designed by solving a linear matrix inequality (LMI).
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Local climate zone ventilation and urban land surface temperatures: Towards a performance-based and wind-sensitive planning proposal in megacities
Jun Yang,Jun Yang,Shanhe Jin,Shanhe Jin,Xiangming Xiao,Xiangming Xiao,Cui Jin,Jianhong Xia,Xueming Li,Shijun Wang +9 more
TL;DR: Wang et al. as mentioned in this paper applied performance-based planning to assess the impact of urban building morphology on local climate surface temperatures under different wind conditions during 2017 in Shanghai, China using multi-source data, such as frontal area density (FAD), local climatic zone classification, land surface temperature (LST) data, and geographic information.
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Influences of urban spatial form on urban heat island effects at the community level in China
TL;DR: Wang et al. as mentioned in this paper explored the urban spatial form at the community scale using spatial autocorrelation and spatial regression methods to explore 2003-2018 spatial and temporal differentiation characteristics and driving factors of Land Surface Temperature (LST).
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Assessing the impacts of urbanization-associated green space on urban land surface temperature: A case study of Dalian, China
TL;DR: In this article, the spatial distribution of urban green space and land surface temperature (LST) in Dalian City, China, were obtained through remote sensing interpretation and inversion.
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Optimizing local climate zones to mitigate urban heat island effect in human settlements
TL;DR: Wang et al. as discussed by the authors used multi-source datasets, including Luojia1-01 nighttime light imagery, Landsat-8, Sentinel-2 and building vector data, to analyze the thermal characteristics of different local climate zones (LCZs).