Easily among one of the worst climate disasters of the previous decade, the Australian bushfires have already permanently altered our geographical and ecological landscape as well as deeply impacted the socioeconomic fabric of our society.
dAs a company that specialises in data analytics and having seen, first-hand, the power of data, we’ve been thinking about how its use could have mitigated some of the damaging effects of the fires.
With an estimated 28 people dead, more than 3000 homes destroyed, and over a billion animals killed, the time for turning the other cheek, especially when it comes to all-encompassing climate disasters like this, is over. We explore how data could not only have been used to contain the fires but more importantly, how it can be used to prevent further catastrophes in an increasingly uncertain future.
Given the frequency of bushfires in Australia, leading to what is now known as bushfire season, understanding how fire can spread is crucial for disaster prevention and mitigation.
Using climate data and bushfire modelling tools, the trajectory of devastating fires can be predicted with surprising accuracy. The usefulness of this is practically tangible – one has to only think about the thousands, if not millions, of lives that can be saved to be convinced.
While the behaviour of fire is anything but simple and predictable, making flexibility a key aspect of any bushfire modelling exercise needs to be a priority. Fortunately, there are tools already in place to make this a reality, most notably ‘Spark’; an open framework for fire prediction and analysis.
Using these tools in the future will allow communities in Australia to take all steps necessary to evacuate and help wildlife authorities prevent such a colossal loss of wildlife from taking place.
Another way in which data can embolden us to meet climate disasters with improved preparedness and effectiveness is by using it to improve emergency response services, especially fire fighting services.
By pulling together data from calls and requests made – especially data pertaining to the location of callers, the time taken to respond to calls, and the level of danger present at each location, for instance – we can improve the responsiveness of these services and prevent certain climate crises, like fires, from escalating.
Even in this regard, steps have already been taken by The South Australian Fire and Emergency Services Commission to improve their service delivery, having analysed data gathered from approximately 300,000 individual incidents in the recent past.
While many of us will only inhabit this earth for a few more decades, our future generations will have to face the true horror of impending climate disasters.
For this reason, improving disaster preparedness needs to be a top priority for world leaders – as it is, we’re already quite late to the party.
Using a combination of data sources and tools, we’re now able to optimise evacuation routes for search and rescue operations using real-time traffic information and use Google Street View to improve the effectiveness of these missions, specifically in terms of compiling pre and post-disaster views of damaged properties.
Beyond disaster preparedness, this type of data is also extremely valuable in the context of recovery and during the rebuilding phase. For instance, we could create realistic damage estimated by pulling property values from certain sites or even use drone imagery and data to understand the true extent of rebuilding necessary.
Another important element of responding and recovering from natural disasters is the quantification of damage – in an era of data technology, what’s the best way to assess the economic impact of climate catastrophes?
Using data visualisation tools and an appropriate model, specifically for quantifying damage, to understand long-term human development trends that predict post-disaster resilience, especially in terms of the labour and job market, we can optimise the recovery process.
This type of exercise has already been conducted and while there are certain limitations to how accurate this can be, it’s only a matter of time until we refine these data models, helping us identify the right kind of support disaster-struck regions need, without wasting precious resources.
As we move towards a future run by data technology, preventing and mitigating the disastrous effects of climate change has to take precedence.
We’re already far beyond the point of no return – all we can do now is protect what resources we have left with all the tools available to us and preserve our planet for the generations to come.