During a Cricket match telecast, you may have heard the commentators utter something on these lines- 'The temperature in Mumbai is 34 degrees but it feels much warmer here at the Wankhede...'. Lest you believe otherwise, the commentators are actually spot on. They are feeling the Urban Heat Island (UHI) effect. Due to factors such as the Construction material used to build the stadium, limited Winds and Crowd noise: the temperature within the stadium is actually a few notches higher than the average temperature of the city at that particular time.
Urban Heat Island (UHI) is used to describe a phenomena where there is a significant difference between the Actual temperature of an Urban area and the Average temperature of surrounding non-Urban areas at a given point in time.
UHI occurs because Urban areas generate, absorb and retain more heat due to factors such as Infrastructure Density, Insulating Building Materials used, Air Pollution, Less Groundwater, Less Evotranspiration, & so on when compared to the non-Urban areas in its immediate surroundings. Here's a useful National Geographic explainer. A high UHI is indicative of excessive Urbanization, high Pollution and high Population and is also a harbinger of Heat-related medical conditions such as Dehydration and Blood Pressure.
As you would imagine, UHI is useful for Urban Planners and Architects who can use the information to chart Future Infrastructure Development sustainably as well as adopt the use of eco-friendly Construction materials. Air Conditioner (AC) manufacturers can also use this information to good effect - by stationing their Field Sales team and shoring up its Retail presence in areas with high UHI.
The Ward-level classification of my UHI study for the metropolis of Mumbai, India as on 22nd May 2019 is depicted in the Map output below:
Prepared using Thermal Remote Sensing - SLSTR - Level 2 LST product - captured using Copernicus' Sentinel-3B satellite as on 22nd May 2019, 16:10 Hrs.
Much thanks to RUS Copernicus and GitHub for the training material. Surrounding non-Urban areas used for comparison fall just outside the city extent of Mumbai.
As you would observe from the map output - the maximum UHI - i.e. maximum differential to base temperature - is found to be 1.59 degrees Celsius which at first may not appear very alarming. However, do note that the temperature differential is aggregated at a macro level - Ward level (each polygon on the map). The original data output generated was actually computed at a pixel level (1 pixel = 20 metres). At an individual pixel level, the maximum temperature differential to base was found to be significantly higher - a maximum of 3.0 degrees Celsius. However, to depict this UHI information on the map output would have been visually chaotic - hence, I chose to aggregate the Temperature results at a Ward level.
Besides, the UHI effect is most prominent during the Night hours, whereas I've use Sentinel imagery dataset captured during Afternoon (16:10) and that too during peak Summer (May 2019). This is because Sentinel-3 dataset captured during Night hours wasn't available for the selected time period.
Why is UHI prominent at night, you may be wondering?
Because the non-Urban areas cool down much quickly than the Urban areas during the night i.e heat retention in Urban areas is more, leading to a large Temperature Differential and thus a higher UHI. As a result, my output is, in a way, only a conservative estimate of the real UHI. In fact, I may not be wrong in imagining that the maximum UHI for Mumbai can be as high as 7 -10 degrees Celsius during the night hours. To help you understand better, imagine that the afternoon temperature in your Urban area of residence is 35 degrees and you expect the Night Temperature to fall to a pleasant 25 degrees due to Cooling, but in reality the Temperature only falls to 32 degrees due to UHI effect - the surrounding non-Urban areas could actually be experiencing the natural 25 degrees temperature that you are craving for at the same point in time!
The final output for Mumbai also makes sense to me intuitively. Large swathes of the main city area i.e. from Colaba to Sion i.e. South Mumbai have the darkest shade of UHI i.e. maximum Temperature Differential from the non-Urban surroundings. As one goes further north in the city, dense Suburban settlements such as Vile Parle and Andheri also have a high UHI which is understandable. In contrast, the region to the east of Eastern Express Highway as well as what comprises Sanjay Gandhi National Park near Borivali and its adjacent areas have less UHI i.e. lower Temperature Differential compared to the non-Urban surroundings (whose temperature we incorporate as the baseline) due to the presence of comparatively limited Urban infrastructure in these within-Mumbai city zones.
Because the temperature data is aggregated at a Ward level - there are some visual anomalies as well, which should be taken into consideration. For example, you'd have observed that the Central Suburbs such as Powai, Vikhroli, Bhandup & Goregaon have less UHI when compared to other similarly dense settlements across Mumbai. This is because the mean UHI is being balanced out by the presence of large non-dense features within the Ward - due to Water Bodies (eg. Powai Lake in Powai) as well as due to Green Zones (eg. Aarey Colony in Goregaon).
What else can you infer from the final UHI output? Can you think of more ways in which UHI data could be useful? Let me know.
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