Remote Sensing (Aug 2024)

Analyzing Thermal Environment Contributions and Driving Factors of LST Heterogeneity in Different Urban Development Zones

  • Youshui Zhang,
  • Carlos Alberto Silva,
  • Mengdi Chen

DOI
https://doi.org/10.3390/rs16162973
Journal volume & issue
Vol. 16, no. 16
p. 2973

Abstract

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Analyzing the impacts of urban landscape patterns on the thermal environment has become one of the key research areas in addressing urban heat islands (UHIs) and improving the living environment. A case study was carried out in Fuzhou, Fujian Province of China, and bi-temporal Landsat imagery was selected to calculate land surface temperature (LST), percent impervious surface area (ISA), and fractional vegetation cover (FVC). The urban area was further divided into three concentric urban zones, ranging from the city center to the urban periphery, based on urban development densities. The spatial pattern of LST and its variance were analyzed and compared between different zones and different dates. The thermal environment contribution of different zones was also quantified to indicate the change in urban landscape patterns resulting from urban expansion in different zones. Furthermore, Geodetector was used to explore the single factors and interaction factors controlling the spatial patterns of LST in each zone. The results showed that (i) urban expansion primarily increased in Zone 2 and Zone 3, and the areal proportion of high and sub-high LST areas increased from 56.11% and 21.08% to 62.03% and 32.49% in Zone 2 and Zone 3, respectively, from 2004 to 2021; (ii) the heat effect contribution of Zones 2 and 3 reached from 75.16% in 2004 to 89.40% in 2021, indicating that the increase in ISA with >LSTmean was more pronounced in Zone 3 and Zone 2 during the period; (iii) the driving factors of LST spatial distribution were regionally different because of the different landscape patterns, and the explanatory power for the heterogeneity of LST in Zone 1 was weaker than in Zone 2 and Zone 3 in the study area; (iv) the interaction of different factors had a higher explanatory power in the spatial distribution of LST than a single factor in each zone because the distributions of land cover types are heterogeneous in urban areas. The results of this study can be used to improve urban planning for urban ecology and UHI mitigation.

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