Elsevier

Building and Environment

Volume 156, June 2019, Pages 21-32
Building and Environment

Inter-/intra-zonal seasonal variability of the surface urban heat island based on local climate zones in three central European cities

https://doi.org/10.1016/j.buildenv.2019.04.011Get rights and content

Highlights

  • Statistically significant seasonal SUHI variability between LCZs.

  • Highest SUHI differences between built and land cover classes occurred in summer.

  • Regional climate and city surrounding affect SUHI during winter, spring and autumn.

  • Statistically significant SUHI variability within LCZ land cover classes (A−C).

  • Density and tree/scrub pattern, together with land cover, affect seasonal SUHI.

Abstract

This study analyzes inter- and intra-zonal seasonal variability of surface urban heat islands (SUHIs) within the methodological framework of local climate zones (LCZs) in three central European cities (Prague, Brno and Novi Sad). These cities differ in urban area and structure as well as in topography and hinterland land-cover features. LCZs were delineated on the basis of a GIS-based classification method. Land surface temperature (LST) was derived from LANDSAT-8 scenes in the period 2013–2018. The first step was to detect seasonal SUHI intensity differences for built LCZ types and LST for land-cover types of LCZ. The results revealed the highest differences in summer and spring, and lowest in winter. The highest SUHI intensity values occur in densely built-up and industrial zones, and the lowest in sparsely-built city outskirts. The coolest LCZs based on LST were dense trees and water areas in spring and summer. The second step aimed to analyze the effects of vegetation on SUHI formation. Hence, 11 land cover subclasses (from dense trees to bush/scrub) were defined in order to research intra-zonal seasonal LST variability. The height and density of vegetation have substantial effects on intra-zonal variability of LST in land-cover types of LCZ, whereas differences between forest subclasses were relatively low. Finally, the character of the vegetation had a substantial influence on intra-zonal LCZ variability of LST and SUHI formation. Further research in this field could contribute to better understanding of micro- and mezzo-climate-scale patterns, as well as better adaptation to climate change in urban areas.

Introduction

Urbanization is one of the main driving forces of landscape change in Europe [1]. The territory of urban agglomerations, including urban and suburban landscapes, constitutes an ever-increasingly important part of the surface [2]. Urban landscape is characterized by structures, arrangements and compositions of land cover distinctly different from those of rural or natural landscapes. Significant proportions of urban areas are covered with artificial – mostly impervious – surfaces, which substantially impact upon the thermal regime of the landscape and thus modify the climate of urban areas. Increased temperatures in such places may significantly alter many aspects of all kinds of life, including biodiversity [3,4], population health [[5], [6], [7], [8]] and overall sustainability of urban areas [9,10]. Considering that global climate change has led to increases in summer climate indices in many urbanized regions, including central Europe [[11], [12], [13], [14], [15]], the importance of studying any additional heat load in urban areas at a local scale is currently of especially pressing importance.

Higher land surface temperatures (LSTs) in urban landscapes in comparison with surrounding (rural or natural) landscapes occur in particular response to lower albedo, higher degree of sealing and anthropogenic heat emission [16]. Compact areas of increased LST in urban areas give rise to a phenomenon known as the “surface urban heat island” (SUHI), something that has been the subject of many studies in recent decades [[17], [18], [19]]. Several investigations have demonstrated that the intensity and character of SUHI greatly influence the air temperature conditions of a city, contributing to the formation of UHIs – air-temperature-based urban heat islands [[18], [19], [20], [21], [22]]. However, the study of temperature differentiation between urban surfaces has long been limited to description of differences between urban, suburban and rural landscapes/areas [18]. This has reflected the comparatively low spatial resolution of the sensors used, as well as the absence of a uniform and generally-recognized classification of urban cover/use types appropriate to LST analyses. Conventional land use/cover classifications, e.g. CORINE Land Cover [23] 500-m MODIS Land Cover Maps [24], USGS Global Land Cover [25] and GlobeLand30 [26] have not permitted discrimination within the diversity of the urban building environment, whereas urban landscape classification has not reacted to the climatic perspective of the urban landscape [27]. This apparent impasse has recently been resolved, at least in part, by classification based on the concept of local climatic zones (LCZs) [28].

LCZs consist of areas of uniform surface cover structure, material, and human activity. They may cover areas ranging from hundreds of meters to several kilometers on the horizontal scale. There are several advantages associated with the LCZ concept as an approach to analysis: it is a global classification scheme with a limited number of classes (10 built and 7 land-cover types) and these classes are defined by physical properties of the urban environment. Although LCZs were originally conceived for the study of air temperature in urban and suburban landscapes, based on an assumption that each LCZ has a generally unique building height and density, as well as some predominant types of building material (concrete, masonry, metal, glass, wood, etc.), that provide different emissivity, the concept was soon recognized as being particularly suitable for studying LST variation in the urban landscape.

Indeed, recent studies have confirmed assumptions of significant or substantial LST differences among LCZs [[29], [30], [31]].

With the adoption of the LCZ concept for LST/SUHI studies, however, further research perspectives and pending queries have emerged, including the effects of day period, seasonality and/or thermal anisotropy on LST variability in particular LCZs [30]. With respect to the results of studies analyzing air temperature variability in LCZs [13,32,33], it is natural to assume that times of day and seasons generate different effects on LST in given LCZs. Indeed, Geletič et al. [30] presented diurnal/nocturnal LST differences between LCZs in the city of Brno (Czech Republic) and Wang et al. [34] recently reported on diurnal/nocturnal LST differences between LCZs in Phoenix (Arizona) and Las Vegas (Nevada). Seasonal variations of LST among LCZs have been covered recently by Gémes et al. [35], who used a single scene for February, May, July and September to express seasonal LST in LCZs in Szeged (Hungary). Further, Ziaul and Pal [36] presented figures from which seasonal variations in LST in the LCZs of English Bazar (India) may be identified.

While the first efforts to quantify seasonal variability of SUHI within the methodical framework of the LCZ concept are emerging, several studies have recently addressed seasonal variation in SUHI and/or seasonal differences of LST between land-cover/use in diverse world regions [[37], [38], [39], [40], [41], [42], [43], [44]]. The sheer quantity and scope of the above contributions presumably demonstrate the existence and importance of seasonal effects in SUHI analyses.

Based on the review above, we assume that wider recognition and employment of the LCZ concept in studies addressing SUHI analyses help to standardize research and facilitate further progress towards more advanced knowledge of the influence of factors such as building structure and material or vegetation state and type down to micro–mezzo-scale climate patterns.

Therefore, this study takes up the challenge of studying SUHI defined on the basis of LCZs and analyzing seasonal differences of LST among particular LCZs. More precisely, the aims of this study are to: i) investigate SUHI based on LCZs, ii) analyze seasonal variations of LST among LCZs and iii) analyze seasonal differences in the intra-zonal variability of LCZs A–C by imposing new subclasses, using the central European cities of Prague and Brno (Czech Republic) and Novi Sad (Serbia) as examples.

Section snippets

Study areas

In the Czech Republic, the study covers the two largest cities: Prague, the nation's capital and Brno, the regional capital of the eastern province of Moravia. It also takes in Novi Sad, the second-largest city in Serbia (Fig. 1; Table 1).

There are few marked differences in urban morphology and topography between the three cities. Brno and Prague both lie among hills. Their elevations range from under 200 m to over 500 m in Brno and under 200 m–400 m in Prague, while Novi Sad lies in the

Local climate zones and subclasses

The landscape classification used herein consists of 17 standard LCZs, of which 15 are defined by surface structure and cover and two by construction materials and anthropogenic heat emissions. The standard set is divided into “built types” 1–10, and “land-cover types” A–G [28]. Contained within the specialist literature are approach methodologies to LCZ mapping based on: (1) manual [46], (2) GIS-based [47,48], (3) remote sensing [49] and (4) combined methodology [50,51]. Since the satellite

Seasonal differences of LST in LCZs – SUHI intensity

SUHI was not well developed in the winter season in a few cases. In Prague and Novi Sad, LCZ G – in both cities dominated by substantial rivers – was the warmest LCZ in the winter season. Further, in Novi Sad the mean LCZ A DIF of LCZ D was even higher than LCZ A DIF of all built LCZs (“SUHI”). In these cases, we cannot, therefore, strictly speaking, use SUHI in significant discussion. Further, in Novi Sad only small differences in LCZ A DIF among built types of LCZ appeared. A higher LCZ A DIF

Discussion

The results of this study raise several important points and pending issues in SUHI analyses, as well as in the concept of Local Climate Zones, that should be discussed further. However, the advantages and disadvantages of the methods employed herein the must be given careful consideration before any further elaboration.

Conclusions

Urban areas of Prague, Brno (Czech Republic) and Novi Sad (Serbia) and their hinterlands were classified in terms of LCZs and subsequently analyses were performed as to their seasonal SUHI variability. On the assumption that SUHI patterns are strongly influenced by different vegetation situations, additional LCZ subclasses were delineated for three land-cover zones (LCZs A−C). The additional classification system had 11 subclasses, and 10 of them were delineated in the three cities analyzed.

Acknowledgements

This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Program I (NPU I), grant reference LO1415 and with institutional support, ref. RVO: 67985807. A partial contribution was made by the Ministry of Education, Science and Technological Development of the Republic of Serbia through project no. 176020. This work was supported by an internal grant from Palacký University, Olomouc ref. IGA_PrF_2018_018 “Regions and Cities:

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