1.1. Urban heat islands
The urban heat island (UHI) is an extensively studied phenomenon and refers to the difference in temperature between a conurbation and the surrounding rural area. There are many factors that contribute to the formation of the UHI. Urban geometry is often cited as the main cause (Oke, 1987), and is frequently parameterised in terms of the sky view factor (Bradley et al., 2002; Svensson, 2004, Unger, 2004) or surface volume compactness (Unger, 2006). Other major influences include the density and population of a conurbation (Oke, 1987) and its associated anthropogenic heat release (Smith et al., 2009), alongside landuse and vegetation cover (Stabler et al., 2005) which affect albedo, emissivity, and surface roughness. The cumulative effect of these factors can result in a maximum UHI of significant magnitude, such as the 7 °C measured in London (Watkins et al., 2002) or greater than 8 °C in New York City (Gedzelman et al., 2003).
A number of review papers illustrate the significant progress that has been made in the study of the UHI phenomenon, in particular, improving the nature and accuracy of measurements, and the development of models (Arnfield, 2003; Mckendry, 2003; Arnfield, 2005, 2006; Souch and Grimmond, 2006). However, despite the broad research effort, an area of research which still requires attention is the inclusion of the UHI phenomenon in climate models. Indeed, a UHI component is notably absent in many models, including the UK Met Office Hadley Centre Regional Climate Model (RCM) which has been used in the UK Climate Programme for both the UKCIP02 (Gawith et al., 2009) and UKCP09 (Jenkins et al., 2009) climate change projections. Including the UHI effect in climate models would improve the accessibility of climate data for planners (Gawith et al., 2009), and high-resolution measurements of UHI effects would be a useful input for model development and validation. This paper aims to produce a simple and transferable technique to quantify the average surface UHI in Birmingham, UK, which could be used by urban planners in conjunction with climate change scenarios, for example, relating to future health risk work and when making planning decisions at the neighbourhood scale.
Traditional measurements of the near-surface UHI are often made using pairs or urban/rural weather stations (Kukla et al., 1986; Karl et al., 1988) or air temperature transects (Johnson, 1985; Torok et al., 2001). However, due to a paucity of high-resolution air temperature measurements in most cities, high-resolution studies are limited to the measurement of surface temperatures and hence, the surface or ‘skin’ UHI as measured by satellites (Streutker, 2003). Surface temperatures are far easier to obtain due to the availability of products such as the thermal land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the National Aeronautics and Space Administration's (NASA) Aqua (EOS-PM1) or Terra (EOS-AM1) satellites. It is important to note that the relationship between air and surface temperature is not fully understood, and discussions (Arnfield, 2003; Weng, 2009) refer to both studies that report similarities (Nichol, 1994), and those that report differences (such as Weller and Thornes, 2001). In this paper, the surface UHI is investigated and no direct relationship to air temperature is suggested or inferred.
1.2. Thermal satellite remote sensing techniques
Satellite techniques for UHI measurement were first investigated in the 1970s (Matson et al., 1978; Price, 1979), but as comparisons between review papers by Gallo et al. (1995) and Weng (2009) illustrate, the field is rapidly changing and advancing.
The increased spatial coverage that satellite remote sensing techniques can provide in comparison to weather station data (Mendelsohn et al., 2007) is the main reason the technique is chosen for many studies of urban climate. Multiple studies have explicitly mentioned the potential and usefulness of the MODIS LST product in UHI research (Rajasekar and Weng, 2008; Cheval et al., 2009). In particular, the instantaneous observations, global coverage and promising quality of MODIS data is extremely valuable (Jin and Shepherd, 2005). Although MODIS has been operating on the Aqua satellite since 2002, it is only recently that a sufficient archive of data is freely available for analysis. It is for this reason why there is a limited amount of studies presently available in the literature that explicitly use MODIS data as a tool for urban climatology.
Compared to potential alternatives such as the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor or Landsat Thermal Mapper (TM)/Enhanced Thermal Mapper Plus (ETM+), the MODIS LST product is considered a coarse resolution (∼1 km) dataset. However, the high temporal resolution (twice daily per satellite) of MODIS makes it ideal for UHI studies. In comparison, the number of images available from ASTER or Landsat is significantly less than MODIS.
The MODIS LST product has already been used for surface UHI investigations in many countries and cities of varying sizes and scales across the globe (Jin et al., 2005). Notable studies include Hung et al. (2006) who used MODIS to quantify the UHI in eight Asian megacities, and Pongracz et al., (2006) who conducted a similar study on the ten most populated cities of Hungary. However, the most relevant study for this paper is recent research from Romania where MODIS was used to calculate the average intensity of the UHI in Bucharest for the month of July between 2000 and 2006 (Cheval and Dumitrescu, 2009) as well as under heatwave conditions in 2007 (Cheval et al., 2009).
Studies have explicitly pointed out the negative effects the UHI may have on health (Changnon et al., 1995; Rooney et al., 1998; Basu and Samet, 2002; Conti et al., 2005), particularly when combined with heatwave events. The UHI has also been shown to influence air quality (Huang et al., 2005) and atmospheric pollution (Sarrat et al., 2006) among other things. Heat risk studies (Lindley et al., 2006) explicitly mention the lack of a UHI component, despite UHI being described as one of the major problems of the 21st century (Rizwan et al., 2008). For this reason, this study focuses on the summer months of June, July, and August (JJA) as these are more likely to cause a heat health risk due to elevated summer temperatures and heatwaves (Rooney et al., 1998; Basu and Samet, 2002). Furthermore, it has been shown that for temperate cities in the northern hemisphere, such as Birmingham, winter UHIs are smaller in both extents and magnitude than summer equivalents (Hung et al., 2006).