On the 25th and 26th of October, Civita will join the Climathon to help Sydney prepare for the increasing heatwaves that will take on the city. The goal? Leveraging the power of data to make the city resilient.
“The impacts of extreme heat are deadly, on the rise globally and preventable.”
As this white paper from the Red Cross explains, the impacts of heatwaves can be decreased and even eliminated when the right policies and tools are in place.
The problem that many cities face globally is that this increase of intensity and frequency of heatwaves are a new phenomena. Only 20 years ago, the concept of heatwaves was not well known. For example, in 2003, Europe had faced a heatwave for which it was not prepared. Because no plan had been installed, the death toll was extremely high and is estimated to be around 70,000.
While measures have started to appear, the journey is long. While heatwaves have “taken more Australian lives than any other natural hazard in the past 200 years” , the country defined this extreme hot weather only 5 years ago. Today, the definition is “three or more days of unusually high maximum and minimum temperatures in any area”.
Even with the best policies and prevention, cities also need to adapt to two effects of heatwaves:
Their frequency and intensity are expected to rise globally due to Global Warming
Growing cities. Urban areas are the most at risk because of the Urban Heat Island Effect. This effect is cause by a higher human activity, the material (roads, roofs, etc.) that absorb the sun’s heat and the lack of vegetation. In Sydney, the Western part of the city is especially affected.
For this challenge, Civita will share a repo with multiple datasets and resources to help you assess:
The risk areas
Suburbs with the higher probability to experience an Urban Heat Island Effect;
Suburbs with the higher proportions of populations at risks: old people, outside workers, infants, etc.);
Districts that are less well served emergency services; etc.
New ways to prevent the indirect impact of heatwaves such as:
a higher water consumption;
a higher energy consumption;
the overload of health services; etc.
We will also provide historical and predictive GIS data from Munich RE of key measures such as the fire seasons, the rainfall and the hottest days. While you can find great libraries on R and Python to read them, we will use an open-source software called QGIS. To learn more about this tool, you should join us on the 17th of October for a special pre-Climathon.