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

Xin Liu,Zuolin Xiao,Rui Liu

doi:10.3390/ijgi8120522

Xin Liu, Zuolin Xiao + Show 1 more

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https://doi.org/10.3390/ijgi8120522

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Abstract

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.

Highlights

The process of urbanization has significant impact on the climatic change by influencing the water balance, energy process and air movement [1], which can potentially lead to a warmer thermal climate in urban areas
The spatial and temporal dependence parameters exhibit different levels of values in the unit interval (Table 1). Both spatial and temporal autocorrelation are present in the urban heat island (UHI) data, our results suggest that after adjusting for the covariate effects, stronger temporal autocorrelation is present in the UHI data, while spatial autocorrelation is relatively weak in the UHI
Due to the limitation of data availability and modeling skill, the residual spatio-temporal autocorrelation of UHI cannot be separated from the covariate effects, which violates the constraint of statistical independence underpinning the correlation models

Summary

Introduction

The process of urbanization has significant impact on the climatic change by influencing the water balance, energy process and air movement [1], which can potentially lead to a warmer thermal climate in urban areas. Most cities in the world show a higher temperature in the city center than in its rural area, which is called the urban heat island (UHI) phenomenon. When calculating the Heat Island Intensity, there are two different ways to distinguish “rural” and “urban” areas: UHI-driven and land-cover driven approaches [4,12]. The former approach separates rural from urban by the temperature pattern, e.g., range and magnitude, while the latter defines the urban and rural areas by different land uses, e.g., urban-green space and urban-rural [4]. Comparison between the two has been conducted [4,12], the choice of the definition is mainly determined by the data availability and the nature of the study

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Results

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