Surface urban heat island effect and urban landscape patterns in Chinese cities : new measurements and multi-scale linkages

Abstract

The urban heat island (UHI) effect, a phenomenon whereby urban areas experience higher temperatures than rural areas, has become one of the most critical urban environmental issues globally, particularly in high-density and rapidly growing cities. The surface UHI (SUHI) represents the urban-rural difference in land surface temperature (LST), which becomes a major research focus in UHI literature. The existing literature indicates a considerable linkage between SUHIs or LST and urban landscape patterns (ULPs), though most previous studies focused on a single spatial scale, which has led to inconsistent findings. Moreover, insufficient attention had been paid to vertical ULPs and variations in their thermal effects over space and time. Furthermore, the technical inadequacies and oversimplifications inherited in the SUHI conceptualization (e.g., the urban-rural dichotomy) cause huge uncertainties in current measurements, and how and to what extent the physical features of cities (i.e., ULPs) influence SUHIs remains a subject of debate and require further investigation. This study aims to develop a systematic SUHI estimation approach that reflects the continuous transition of thermal environments along the urban-rural gradient to reduce part of the possible biases and uncertainties in SUHI estimation, and it proposes a three-level quantification framework for ULPs based on Conzen’s theory and existing two-dimensional (2D) and three-dimensional (3D) spatial metrics and datasets. Finally, it also examines the impacts of ULPs on LST on multiple scales across a large number of cities. Through multi-scale and comparative ULP-LST linkage analyses, the current study specifically aims to answer the following central research question: How do ULPs affect SUHIs/LST on multiple scales, over distinct time periods, and in different cities? This main question can be further divided into the following three parts: (1) How can the intensity and footprints of SUHIs be measured at the city level, how do they change, and what affects these changes across time and space? (2) How do 3D ULPs affect LST in urban areas at the street block level, and do the impacts of ULPs vary across time, cities, and different types of LST? (3) Does the effect of key ULP indicators on LST exhibit a scale effect, and is there an abrupt change or threshold value in terms of the effect of surrounding landscapes at the street block level? This study contributes to the existing literature in the following ways. First, it develops a systematic SUHI estimation approach based on temperature profiles along the urban-rural gradient and geomorphic analogy using a typical UHI described by Oke. The study justifies the advantages of the proposed approach in reducing possible biases and uncertainties in SUHI measures by comparing it to two methods used in previous studies. The accurate SUHI estimates aid in understanding the spatiotemporal variation in the SUHI effect and the associated driving factors. Second, a comprehensive three-level quantification system of ULPs related to LST/SUHI is proposed based on existing theories and findings on the thermal effect of urban built environments. The study uses 2D and 3D spatial metrics to quantify ULPs and provides a database of ULP indicators for 38 Chinese megacities. Third, the study identifies the varying relationships between ULPs and LST over time and space. Through comparative analyses of ULP-LST linkages, the study reveals how and to what extent ULPs affect the thermal environment on different scales, over distinct time periods, and in multiple cities, and it identifies the most influential ULP indicators based on the cross-city comparison. Fourth, the study expands the analytical focus on the thermal effect of ULPs on LST to the surrounding urban landscape and takes advantage of the multiscalar approach to investigate the change patterns of ULP metrics and their impacts within multiple buffer zones and identify the optimal buffer distances from which the ULP indicators yield the greatest influence on LST.