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A Spatio-Temporal Bayesian Model for Estimating the Effects of Land Use Change on Urban Heat Island

Chongqing Key Laboratory of GIS Application, School of Geography and Tourism, Chongqing Normal University, Chongqing 401331, China
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ISPRS Int. J. Geo-Inf. 2019, 8(12), 522; https://doi.org/10.3390/ijgi8120522
Received: 21 August 2019 / Revised: 28 October 2019 / Accepted: 18 November 2019 / Published: 20 November 2019
The urban heat island (UHI) phenomenon has been identified and studied for over two centuries. As one of the most important factors, land use, in terms of both composition and configuration, strongly influences the UHI. As a result of the availability of detailed data, the modeling of the residual spatio-temporal autocorrelation of UHI, which remains after the land use effects have been removed, becomes possible. In this study, this key statistical problem is tackled by a spatio-temporal Bayesian hierarchical model (BHM). As one of the hottest areas in China, southwest China is chosen as our study area. Results from this study show that the difference of UHI levels between different cities in southwest China becomes large from 2000 to 2015. The variation of the UHI level is dominantly driven by temporal autocorrelation, rather than spatial autocorrelation. Compared with the composition of land use, the configuration has relatively minor influence upon UHI, due to the terrain in the study area. Furthermore, among all land use types, the water body is the most important UHI mitigation factor at the regional scale.
Keywords: urban heat island (UHI); Bayesian hierarchical model (BHM); land use; entropy index; green space; water body urban heat island (UHI); Bayesian hierarchical model (BHM); land use; entropy index; green space; water body
MDPI and ACS Style

Liu, X.; Xiao, Z.; Liu, R. A Spatio-Temporal Bayesian Model for Estimating the Effects of Land Use Change on Urban Heat Island. ISPRS Int. J. Geo-Inf. 2019, 8, 522.

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