Use of Local Climate Zones to investigate surface urban heat islands in Texas. Issue 8 (16th November 2020)

• Record Type: Journal Article
• Authors: Zhao, Chunhong; Jensen, Jennifer L. R.; Weng, Qihao; Currit, Nathan; Weaver, Russell
• Is Part Of: GIScience & remote sensing. Volume 57:Issue 8(2020)
• Page Start: 1083
• Page End: 1101
• Publication Date: 2020-11-16
• Subjects: Land surface temperature -- Landsat -- Local Climate Zones -- surface urban heat island -- Texas cities; Geodesy -- Periodicals; Cartography -- Periodicals; Aerial photogrammetry -- Periodicals; Remote sensing -- Periodicals; 526.05
• DOI: 10.1080/15481603.2020.1843869
• Languages: English
• ISSNs: 1548-1603

Abstract

ABSTRACT: Urban heat islands (UHIs) are a key topic in urban climate studies. However, systematic criteria for UHI comparisons were lacking prior to 2012, when the concept of Local Climate Zones (LCZs) was introduced. By relating remotely sensed land surface temperature (LST) to LCZs, we explored the applicability of LCZs in surface urban heat island (SUHI) investigations and compared the LST variation within and among LCZs for the Austin, San Antonio, and Dallas-Fort Worth metropolitan areas in Texas, United States. Landsat 8 images from one summer and one winter day in 2015 were used to obtain LSTs to measure and model SUHIs. LCZs that were characterized by different land covers had the greatest LST variations, and LCZs that were further characterized by various urban morphological properties (including building density and height of roughness) also showed significant LST differences. Moreover, LCZ 9 (sparsely built), LCZ 10 (heavy industry), LCZ D (low plants), LCZ E (bare rock or paved), and LCZ F (bare soil or sand) tended to contribute to contradictory heating/cooling effects in different metropolitan areas, primarily due to the spatial arrangement and geographic locations of LCZs. The close association between LCZs and LST demonstrates that LCZs are valuable for comparative analysis of the SUHI phenomenon between different cities and can be helpful for examination of the evolution of SUHIs over time. Our findings further suggest that understanding the spatial distribution of LCZs can benefit the development of mitigation strategies for SUHIs.