The Gradient Effect on the Relationship between the Underlying Factor and Land Surface Temperature in Large Urbanized Region

Yixu Wang,Dongchuan Wang,Mingxue Xu,Jun Li,Ying Xu,Lei Yao,Nan Jiang

doi:10.3390/land10010020

Abstract

Although research relating to the urban heat island (UHI) phenomenon has been significantly increasing in recent years, there is still a lack of a continuous and clear recognition of the potential gradient effect on the UHI—landscape relationship within large urbanized regions. In this study, we chose the Beijing-Tianjin-Hebei (BTH) region, which is a large scaled urban agglomeration in China, as the case study area. We examined the causal relationship between the LST variation and underlying surface characteristics using multi-temporal land cover and summer average land surface temperature (LST) data as the analyzed variables. This study then further discussed the modeling performance when quantifying their relationship from a spatial gradient perspective (the grid size ranged from 6 to 24 km), by comparing the ordinary least squares (OLS) and geographically weighted regression (GWR) methods. The results indicate that: (1) both the OLS and GWR analysis confirmed that the composition of built-up land contributes as an essential factor that is responsible for the UHI phenomenon in a large urban agglomeration region; (2) for the OLS, the modeled relationship between the LST and its drive factor showed a significant spatial gradient effect, changing with different spatial analysis grids; and, (3) in contrast, using the GWR model revealed a considerably robust and better performance for accommodating the spatial non-stationarity with a lower scale dependence than that of the OLS model. This study highlights the significant spatial heterogeneity that is related to the UHI effect in large-extent urban agglomeration areas, and it suggests that the potential gradient effect and uncertainty induced by different spatial scale and methodology usage should be considered when modeling the UHI effect with urbanization. This would supplement current UHI study and be beneficial for deepening the cognition and enlightenment of landscape planning for UHI regulation.

Highlights

IntroductionAs one of the many factors that influence the urban thermal environment, the landscape features of the underlying surface represent the most commonly used driving factor for examining the quantization relationship with urban heat island (UHI) in most of the related studies [8]
For urban heat island (UHI), previous studies have tended to use the difference in the surface air temperature in order to characterize the UHI intensity [9]; with the development of Earth observation technology, the remotely sensed land surface temperature (LST) has been widely used as a more geo-convenient way to record the heterogeneity of the land surface thermal environment [1,10]
We will focus on the performance of this positive driver for the UHI phenomenon in the subsequent analysis, i.e., the built-up land density

Summary

Introduction

As one of the many factors that influence the urban thermal environment, the landscape features of the underlying surface represent the most commonly used driving factor for examining the quantization relationship with UHI in most of the related studies [8] This requires the conversion of these environmental factors into quantitative indicators in advance for statistical causal analysis. For investigating the landscape features of the underlying surface, researchers can access the detailed land cover and change information for most parts of the Earth’s system while using modern remote sensing and geographic information technology. These land surface details can be further quantized into numerical landscape metrics following the landscape ecology theory, and they fall into two categories, as landscape composition and configuration characteristics [11]

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Conclusion