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Int J Environ Res Public Health. 2016 Sep 2;13(9). pii: E880. doi: 10.3390/ijerph13090880.

Neighborhood Landscape Spatial Patterns and Land Surface Temperature: An Empirical Study on Single-Family Residential Areas in Austin, Texas.

Author information

1
Department of Landscape Architecture and Urban Planning, Texas A&M University, A318A Langford Architecture Center, 3137 TAMU, College Station, TX 77843-3137, USA. jhkim@arch.tamu.edu.
2
Department of Landscape Architecture and Urban Planning, Texas A&M University, A318A Langford Architecture Center, 3137 TAMU, College Station, TX 77843-3137, USA. dgu@tamu.edu.
3
Department of Landscape Architecture and Urban Planning, Texas A&M University, A318A Langford Architecture Center, 3137 TAMU, College Station, TX 77843-3137, USA. wonmin.sohn@tamu.edu.
4
Department of Ecological Landscape Architecture Design, Kangwon National University, Chuncheon 24341, Korea. sunghokil@kangwon.ac.kr.
5
Division of Architecture & Urban Design, Incheon National University, Incheon 406-772, Korea. hwan.kim@inu.ac.kr.
6
Department of Landscape Architecture, Seoul National University, Seoul 151-921, Korea. dklee7@snu.ac.kr.

Abstract

Rapid urbanization has accelerated land use and land cover changes, and generated the urban heat island effect (UHI). Previous studies have reported positive effects of neighborhood landscapes on mitigating urban surface temperatures. However, the influence of neighborhood landscape spatial patterns on enhancing cooling effects has not yet been fully investigated. The main objective of this study was to assess the relationships between neighborhood landscape spatial patterns and land surface temperatures (LST) by using multi-regression models considering spatial autocorrelation issues. To measure the influence of neighborhood landscape spatial patterns on LST, this study analyzed neighborhood environments of 15,862 single-family houses in Austin, Texas, USA. Using aerial photos, geographic information systems (GIS), and remote sensing, FRAGSTATS was employed to calculate values of several landscape indices used to measure neighborhood landscape spatial patterns. After controlling for the spatial autocorrelation effect, results showed that larger and better-connected landscape spatial patterns were positively correlated with lower LST values in neighborhoods, while more fragmented and isolated neighborhood landscape patterns were negatively related to the reduction of LST.

KEYWORDS:

FRAGSTATS; GIS; green spaces; land surface temperature; landscape indices; spatial autocorrelation; urban heat island effect

PMID:
27598186
PMCID:
PMC5036713
DOI:
10.3390/ijerph13090880
[Indexed for MEDLINE]
Free PMC Article

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