Sky view factor analysis – implications for urban air temperature differences

Svensson, Marie K.

doi:10.1017/s1350482704001288

Cited by 235 publications

(115 citation statements)

References 26 publications

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“…Since one of the stated aims of the present study was to attempt to exclude the distance-from-centre factor, the use of relatively small source areas was crucial. In line with Svensson's (2004) findings, the results of this study show no improvement in R 2 between T a and SVF at sensor height (2 m) when compared with the SVF at ground level.…”

Section: Urban Surface Parameters and Temperature Variationssupporting

confidence: 89%

“…Both the surface and air temperatures within the city of Göteborg have been studied in relation to geometry for a long time (e.g. Eliasson, 1996;Upmanis, 1999;Lindberg, 2002;Lindberg et al, 2003;Svensson, 2004). These studies show that the surface and air temperatures generally decrease with increasing SVF.…”

Section: Urban Geometry and Intra-urban Temperature Variationsmentioning

confidence: 99%

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Modelling the urban climate using a local governmental geo‐database

Lindberg

2007

Meteorological Applications

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ABSTRACT:In this study, local government digital spatial data are used to describe urban geometry and analyse spatial variations of the urban climate within the central areas of Göteborg, Sweden. A high-resolution raster digital elevation model (1 m pixel resolution) consisting of building structures and ground heights is derived from a local government geodatabase, as well as land use patterns and artificial heat sources. Parameters such as the sky view factor (SVF) and daily averages of solar radiation are calculated. Results obtained from the model are compared with intra-urban air temperature variations which are derived from mobile measurements, as well as surface temperature variations derived from thermal infrared images. Results show that high-resolution digital elevation models in raster format are very useful sources of data for the investigation of intra-urban temperature variations. Results also show that the areal mean of SVF correlates with intra-urban air temperature variations to a higher degree than SVF that is taken from a point source location. The correlation between the modelled SVF and surface temperature is high during both spring and winter. Adding information about daily averages of global radiation for the spring measurement causes the correlation between SVF and surface temperature variations to increase.

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Section: Urban Surface Parameters and Temperature Variationssupporting

confidence: 89%

Section: Urban Geometry and Intra-urban Temperature Variationsmentioning

confidence: 99%

Modelling the urban climate using a local governmental geo‐database

Lindberg

2007

Meteorological Applications

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“…Others adopt a three-dimensional approach by examining the impact of sky view factor which is the amount of free sky uninterrupted by buildings, structures, or vegetation at a specific location [23][24][25][26][27][28]. A second focus is on urban density.…”

Section: Introductionmentioning

confidence: 99%

The Seasonal and Diurnal Influence of Surrounding Land Use on Temperature: Findings from Seoul, South Korea

Kim¹,

Kim²

2017

Sustainability

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Abstract:There is a growing interest in understanding how the built environment affects temperature in cities. This study explores the impact of land use on temperature and how it varies by season and time of day in Seoul, South Korea. Unlike other studies that rely on extracted data from remotely sensed information, this study uses land use data from local GIS and near-ground temperature data from a network of state-run weather stations. To deal with multicollinearity among the land use variables, partial least squares regression models were used for analysis. Results suggest that residential and commercial uses and roads increase the temperature while open spaces decrease it. In detail, central commercial use, high-density residential use, and roads were influential heaters, while greenery was an influential cooler throughout the year. This study suggests the need for place-based planning and design solutions that help build climate resilience of cities.

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“…Gál et al (2009) reported a strong linear negative association between annual mean temperatures and SVF. Other studies also showed statistically significant associations between SVF and urban temperature (Chen et al, 2012;Unger, 2009;Svensson, 2004). …”

Section: Literature Reviewmentioning

confidence: 81%

Spatial and Temporal Effects of Built Environment on Urban Air Temperature in Seoul City, Korea: An Application of Spatial Regression Models

Lee

Cho

2017

Journal of Asian Architecture and Building Engineering

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In this study we examined the relationships between the built environment and urban air temperature in Seoul city, Korea. We developed multivariate regression models that address the relationship between built environment characteristics and the ambient air temperature with spatial statistics techniques. In addition, we analyzed the difference in daytime and nighttime air temperature to identify the built environment characteristics that affect the intensity of the nocturnal urban heat island effect (UHI). The large sample size of AWS locations in Seoul makes it possible to analyze the factors that influence ambient air temperature and UHI effect. The analysis results indicate that the sky view factor (SVF) and gross floor area significantly influence the daytime air temperature, while the building coverage and albedo showed strong relationships with the nocturnal air temperature. This study also demonstrated the importance of advanced spatial statistics techniques that control spatial autocorrelation and spatial heteroscedasticity in urban air temperature research. Our models confirmed the need to capture the effects of spatial autocorrelations within our spatial data. The findings of this study are valuable for understanding the complicated associations between the built environment and urban air temperature and to develop public policies to mitigate UHI effects.

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Sky view factor analysis – implications for urban air temperature differences

Abstract: This study identifies the use of the sky view factor (SVF)

Cited by 235 publications

References 26 publications

Modelling the urban climate using a local governmental geo‐database

Modelling the urban climate using a local governmental geo‐database

The Seasonal and Diurnal Influence of Surrounding Land Use on Temperature: Findings from Seoul, South Korea

Spatial and Temporal Effects of Built Environment on Urban Air Temperature in Seoul City, Korea: An Application of Spatial Regression Models

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