Greenspace Pattern and the Surface Urban Heat Island: A Biophysically-Based Approach to Investigating the Effects of Urban Landscape Configuration
Surface urban heat islands (SUHIs) are influenced by the spatial distribution of green space, which in turn can be influenced by urban planning. When studying the relationship between structure and function it is critical that the scale of observation reflects the scale of the phenomenon being measu...
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doaj-62f127f732d24e538d3d631829f5f0a42020-11-25T02:50:06ZengMDPI AGRemote Sensing2072-42922019-10-011119232210.3390/rs11192322rs11192322Greenspace Pattern and the Surface Urban Heat Island: A Biophysically-Based Approach to Investigating the Effects of Urban Landscape ConfigurationElizabeth Jane Wesley0Nathaniel A. Brunsell1Department of Geography & Atmospheric Science, University of Kansas, Lawrence, KS 66045, USADepartment of Geography & Atmospheric Science, University of Kansas, Lawrence, KS 66045, USASurface urban heat islands (SUHIs) are influenced by the spatial distribution of green space, which in turn can be influenced by urban planning. When studying the relationship between structure and function it is critical that the scale of observation reflects the scale of the phenomenon being measured. To investigate the relationship between green space pattern and the SUHI in the Kansas City metropolitan area, we conducted a multi-resolution wavelet analysis of land surface temperature (LST) to determine the dominant length scales of LST production. We used these scales as extents for calculating landscape metrics on a high-resolution land cover map. We built regression models to investigate whether−controlling for the percent vegetated area−patch size, fragmentation, shape, complexity, and/or proximity can mitigate SUHIs. We found that while some of the relationships between landscape metrics and LST are significant, their explanatory power would be of little use in planning for green infrastructure. We also found that the relationships often reported between landscape metrics and LST are artifacts of the relationship between the percent of vegetation and LST. By using the dominant length scales of LST we provide a methodology for robust biophysically-based analysis of urban landscape pattern and demonstrate that the contributions of green space configuration to the SUHI are negligible. The simple result that increasing green space can lower LST regardless of configuration allows the prioritization of resources towards benefiting neighborhoods most vulnerable to the negative impacts of urban heat.https://www.mdpi.com/2072-4292/11/19/2322surface urban heat islandgreen space patterndominant length scalewavelet decompositionlandscape metricsscaling effects |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Elizabeth Jane Wesley Nathaniel A. Brunsell |
spellingShingle |
Elizabeth Jane Wesley Nathaniel A. Brunsell Greenspace Pattern and the Surface Urban Heat Island: A Biophysically-Based Approach to Investigating the Effects of Urban Landscape Configuration Remote Sensing surface urban heat island green space pattern dominant length scale wavelet decomposition landscape metrics scaling effects |
author_facet |
Elizabeth Jane Wesley Nathaniel A. Brunsell |
author_sort |
Elizabeth Jane Wesley |
title |
Greenspace Pattern and the Surface Urban Heat Island: A Biophysically-Based Approach to Investigating the Effects of Urban Landscape Configuration |
title_short |
Greenspace Pattern and the Surface Urban Heat Island: A Biophysically-Based Approach to Investigating the Effects of Urban Landscape Configuration |
title_full |
Greenspace Pattern and the Surface Urban Heat Island: A Biophysically-Based Approach to Investigating the Effects of Urban Landscape Configuration |
title_fullStr |
Greenspace Pattern and the Surface Urban Heat Island: A Biophysically-Based Approach to Investigating the Effects of Urban Landscape Configuration |
title_full_unstemmed |
Greenspace Pattern and the Surface Urban Heat Island: A Biophysically-Based Approach to Investigating the Effects of Urban Landscape Configuration |
title_sort |
greenspace pattern and the surface urban heat island: a biophysically-based approach to investigating the effects of urban landscape configuration |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2019-10-01 |
description |
Surface urban heat islands (SUHIs) are influenced by the spatial distribution of green space, which in turn can be influenced by urban planning. When studying the relationship between structure and function it is critical that the scale of observation reflects the scale of the phenomenon being measured. To investigate the relationship between green space pattern and the SUHI in the Kansas City metropolitan area, we conducted a multi-resolution wavelet analysis of land surface temperature (LST) to determine the dominant length scales of LST production. We used these scales as extents for calculating landscape metrics on a high-resolution land cover map. We built regression models to investigate whether−controlling for the percent vegetated area−patch size, fragmentation, shape, complexity, and/or proximity can mitigate SUHIs. We found that while some of the relationships between landscape metrics and LST are significant, their explanatory power would be of little use in planning for green infrastructure. We also found that the relationships often reported between landscape metrics and LST are artifacts of the relationship between the percent of vegetation and LST. By using the dominant length scales of LST we provide a methodology for robust biophysically-based analysis of urban landscape pattern and demonstrate that the contributions of green space configuration to the SUHI are negligible. The simple result that increasing green space can lower LST regardless of configuration allows the prioritization of resources towards benefiting neighborhoods most vulnerable to the negative impacts of urban heat. |
topic |
surface urban heat island green space pattern dominant length scale wavelet decomposition landscape metrics scaling effects |
url |
https://www.mdpi.com/2072-4292/11/19/2322 |
work_keys_str_mv |
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