Urban Heat Island (UHI) effect in Mumbai

During a cricket match you may have heard TV commentators remark something like this - "The temperature in Mumbai is 34 degrees but it feels much warmer here at the Wankhede..."

The commentator feels correctly, actually. This is a small demonstration of the Urban Heat Island effect. Due to factors such as stadium build, 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) phenomenon occurs when there is a significant difference between the actual temperature of an urban area and the average temperature of nearby non-urban areas (this acts as a substitute for the normal temperature of the urban area at that point in time).

UHI occurs because urban areas generate & absorb more heat as well as release less heat due to factors such as construction density, insulating building materials used, population density, less ground storage of rainfall and less evaporation / plant transpiration when compared to non-urban areas. Here's a useful National Geographic explainer.

A high UHI is indicative of excessive urbanization, high pollution, high population stress levels and higher incidences of heat related conditions such as dehydration and blood pressure. As you would imagine, UHI results are very useful for urban planners in terms of planning future city development as well as in terms of increasing the usage of eco-friendly construction materials.

The result of the UHI Mumbai exercise is depicted in the map below -

Prepared using thermal remote sensing feature - SLSTR - Level 2 LST product - in Copernicus Sentinel 3B satellite as on 22nd May 2019, 16:10 Hrs. Much thanks to RUS Copernicus and GitHub for the invaluable training material. Nearby non-urban areas fall just outside the Mumbai extent.

As you would observe in the map - the maximum UHI i.e. differential to base temperature is found to be at 1.6 degrees Celsius which doesn't strike as drastic at first glance.

The temperature differential is aggregated at Ward level (each polygon on the map) in Mumbai. The original data was actually computed at a pixel level (1 pixel = 20 metres. appx). However, to depict that on a map would be visually chaotic - hence mean temperature per ward was used - an aggregation of all pixels within, for better representation. At an individual pixel level, the maximum temperature differential to base was found to be higher - a maximum of 3.0 degrees Celsius (nearly double of the maximum mean range displayed in the map above).

More importantly, the UHI effect is most prominent during the night hours. This is because the non-urban areas cool down much quicker than the urban areas leading to a large temperature differential. However, due to Sentinel satellite imagery not available during that point in time, I have attempted to analyse the UHI effect at the closest possible alternative time (4 pm) during peak summer condition (May). As a result, the map result is only indicative of Actual UHI - the darker shades would not lose much intensity at the night hours as these regions would not release much heat then whereas the paler shades would grow even more paler at night, due to the relatively higher intensity of cooling.

Given these readings are on a warm summer afternoon, it is not difficult to imagine that the UHI for the most affected urban regions in Mumbai (darkest shade) can be as high as 7 -10 degrees Celsius during the night hours. It is to say that if afternoon temperature is 35 degrees, the night temperature should naturally be 25 degrees due to cooling, but it actually falls only to 32 degrees due to UHI effect.

The map result seems quite indicative to me from a location point of view. Large swathes of the main city area i.e. South Mumbai - from Colaba and Churchgate to Parel and Sion have the darkest shade i.e maximum temperature differential - UHI. Going north, dense urban areas such as Vile Parle and Andheri also have the darkest shade. In contrast, the region to the east of Eastern Express Highway as well as Sanjay Gandhi National Park and adjacent areas have the palest shade i.e. least temperature differential due to the limited urban features in these regions.

Because the data is aggregated at a Ward level - there are some visualization anomalies as well - dense central suburbs such as Powai, Vikhroli and Bhandup have slightly less temperature differential as per the map result. This is because the UHI of these areas is balanced out by the presence of large water bodies (Powai lake) and green areas (Aarey colony) resulting in the mean temperature at Ward level to go down.

What else can you interpret? Do you see any more ways how UHI results can be useful?

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Regards,

Arpit