Field Measurements

As you might come to expect, the UHI, when broken down to its key components is just a temperature difference between two locations. Of course there is a much deeper complex relationship between multiple atmospheric and physical forcings that bring out the true breadths and detail of the UHI, but such relationships aren’t important for simply identifying the UHI. 

Considering the UHI can fluctuate on a hourly basis, observations are often taken under favourable conditions as described by Anfield (2003) within calm/clear summer evenings. A well-known observational technique is to use a pair or more of fixed or mobile stations along a transect to measure near-surface air temperature between urban and rural regions. The technique was first implemented by a researcher named Luke Howard (1818) in the city of London but was later adopted as a very useful technique for UHI research. 

Measurements of Temperature are the only required variable for identifying a UHI but in order to develop a deeper understanding of the dynamics involved, measurements of Humidity, wind velocity, air pressure and pollution are also widely documented. Additionally, when taking transect measurements, researchers must take note of two very important variables, which include:

• Sky View Factor: A measure of the total visible sky at 180º from the surface position of interest. Measurements can be achieved affordably using a fisheye lens on a camera facing upwards from the surface (Figures 1, 2, 3), whereby the higher the percentage of visible sky in the image, there would be less trapping of heat in the system.

• Land Use Variable: These include the material make-up of the land where the measurements are taken (Tarmac, Glass, Soil, Water…), particularly with relation to Albedo and specific heat capacity. Higher Albedo and Lower Heat Capacity would suggest a weaker warming effect to be experienced in the vicinity. 

The largest issues associated with the use of fixed and mobile stations, suggested by Mirzaei and Haghighat (2010) is that they are very limited. They are time consuming and can only measure a limited number of parameters, hence requiring the remaining parameters to be ignored or estimated. Additionally, they would need to be run for very extended periods of time to weed out the effects of unexpected influences to the measurements (Pedestrians, Vehicles…). The techniques work well for identifying and potentially quantifying the intensity of the UHI but may only be suitable for generalisations based off of trends whilst dynamic relationships cannot be determined due to the missing parameters.

Figure 1: Skyview experienced within a densely foliated rural station. This is a good example of a rural station which may be unsuitable for UHI measurements due to the potential for heat to be trapped within the dense foliage.

Figure 2: Skyview experienced within a city center. The skyview is obstructed by the high towering buildings, attributing to the increase in trapped heat.

Figure 3: Skyview experienced within a coastal region. The sky view is not highly obstructed, almost similar to what would be expected of a hilly grassland. The high sky visibility suggests low trapping of heat. Nevertheless, a UHI could still develop, albeit a weak one.