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dc.contributor.authorWesley, Elizabeth Jane
dc.contributor.authorBrunsell, Nathaniel A.
dc.date.accessioned2021-02-09T21:24:53Z
dc.date.available2021-02-09T21:24:53Z
dc.date.issued2019-10-05
dc.identifier.citationWesley, E.J.; Brunsell, N.A. Greenspace Pattern and the Surface Urban Heat Island: A Biophysically-Based Approach to Investigating the Effects of Urban Landscape Configuration. Remote Sens. 2019, 11, 2322. https://doi.org/10.3390/rs11192322en_US
dc.identifier.urihttp://hdl.handle.net/1808/31405
dc.descriptionThis work is licensed under a Creative Commons Attribution 4.0 International License.en_US
dc.description.abstractSurface 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.en_US
dc.publisherMDPIen_US
dc.rightsc 2019 by the authors. Licensee MDPI, Basel, Switzerland.en_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.subjectSurface urban heat islanden_US
dc.subjectGreen space patternen_US
dc.subjectDominant length scaleen_US
dc.subjectWavelet decompositionen_US
dc.subjectLandscape metricsen_US
dc.subjectScaling effectsen_US
dc.titleGreenspace Pattern and the Surface Urban Heat Island: A Biophysically-Based Approach to Investigating the Effects of Urban Landscape Configurationen_US
dc.typeArticleen_US
kusw.kuauthorWesley, Elizabeth Jane
kusw.kuauthorBrunsell, Nathaniel A.
kusw.kudepartmentGeography & Atmospheric Scienceen_US
dc.identifier.doi10.3390/rs11192322en_US
dc.identifier.orcidhttps://orcid.org/0000-0001-9366-0478en_US
dc.identifier.orcidhttps://orcid.org/0000-0002-4460-8283en_US
kusw.oaversionScholarly/refereed, publisher versionen_US
kusw.oapolicyThis item meets KU Open Access policy criteria.en_US
dc.rights.accessrightsopenAccessen_US


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c 2019 by the authors. Licensee MDPI, Basel, Switzerland.
Except where otherwise noted, this item's license is described as: c 2019 by the authors. Licensee MDPI, Basel, Switzerland.