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Interview with an Expert: Marc Castellnou

At the height of the pandemic, the Robotto team sat down with wildfire expert Marc Castellnou to learn more about issues and challenges firefighters face when dealing with wildfires.


Marc Castellnou is President Patronat at the Pau Costa Foundation, Inspector Cap de l’Area Forestal with Bombers Generalitat, Associate Professor at the University of Lleida, and has published a number of studies focusing on the behavior of wildfires. With this expertise, Mr. Castellnou took our team through, what he has identified, to be the biggest challenges facing wildfire analytics and firefighting teams today. His input has driven our team to create software that specifically targets these pain points, helping his team in Spain focus on what’s important- keeping their community safe.


THE VALUE OF INFORMATION

Mr. Castellnou began by stating that there is currently an overflow of information. Firefighters are struggling to understand wildfire behavior by using all methods of data collection and analysis available to them. Today’s method includes sifting through information via radio, aerial monitoring, and personal point of view reports. This process creates a messy and thick data flow making it difficult to have a quality overview of the situation. In addition to this, community concern and rampant misinformation on social media has begun to pull their attention away from tackling the flames, as this parallel emergency requires immediate attention as to not cause panic within the community.


HOW DATA COLLECTION WORKS NOW
Visualization of mathematicall analysis provided by Marc Castellnou

The team was particularly interested in learning how fire departments currently analyze wildfires, and what information sources are consulted during this process. Mr. Catellnou outlined a five-step process in which various aspects of the fire service are utilized in an attempt to gain a better overview.

  1. Aerial teams ascertain an overview from above (fire start + 21 minutes)

  2. The on-site crew reports the fire’s behavior to command (fire start + 34 minutes)

  3. Fire analysts attempt to create a clear view of the scenario using mathematical polygons of fire potential, trying to understand what fire wants to do

  4. With this information department leaders identify where efforts will be made and where the fire naturally will spread due to topology and fuel sources

  5. Plans are then communicated to the community alongside fire updates and changes in fire suppression methods due to unpredicted fire behavior


FIRE BEHAVIOR PREDICTIONS

Mr. Castellnou spoke about a fire in which teams predicted westward movement as that was the indicated wind direction. This, however, did not happen as the fire was located in a canyon, creating an unpredictable situation where the fire moved north, surprising fire services. It is specifically here AI, according to Castellnou, has the potential to lend a hand, qualifying information and checking assumptions to give fire services a better understanding of what they are dealing with.


Graph of Connectivity provided by Marc Castellnou

Another method of influencing fire behavior currently used by the fire service is the graph of connectivity. Using this teams decide how to prioritize efforts to minimize burn sizes. The effectiveness of this, however, is dependent on the quality of aerial information coupled with quality mapping (including elevation, topology, and fuel types).


COMMUNICATING WITH THE COMMUNITY

Fire services are servants of their communities, and keeping their communities informed in times of disaster is a fundamental aspect of their job. With the growing number and intensity of wildfires, trust in their abilities has begun to wane, making community outreach and increasing credibility vital.


New methods of communication must remove uncertainty and increase the credibility within the local community of the fire service. Castellnou explained that “if you can not tell what you are doing and how you are doing it, you won’t get credibility”. This concern is particularly important in the age of broadcast and social media, as communities have begun to question the credibility and ability of fire services to do their jobs, increasing their active concerns which in turn detract from the focus and use precious man-hours as they work to contain the spread. However, Castellnou notes that if you address the community with an active fire stating “we are doing all that we can” the lack of details does nothing to calm fears.


To present the community with information that will achieve this goal (specifics of what the team is doing, where they see the fire status in the morning etc.) requires advanced modeling and data surveillance methods.


THE PROBLEM

“Within emergency services there are two problems, the one we as service members know we have and the one our bosses, our politicians, think we have” Mr. Castellnou stated, continuing to note that many believe their problem is increasing external credibility. This is of course important, but to do this, service members on the ground need improved fire data that allows them to get ahead of the problem.


What is the solution to this? Many in the fire service (who are not on the ground) believe the solution is more recourses, but according to Mr. Castellnou, this isn’t completely true. The solution according to this GRAF team lead is a better understanding, better information that allows them to create a successful strategy, a strategy that isn’t based on following the fire.


WHAT NEW TECHNOLOGY NEEDS TO PROVIDE

Our goal at Robotto is to create software that equips firefighters with the quality information they deserve. We do this by simplifying the fire surveillance and analysis process, allowing them to gain a better understanding of the problem at hand and keep their communities safe and satisfied with their abilities. As this is our main purpose, the team posed Mr. Castellnou a series of questions, during which he outlined the main goal any new software must achieve: Solutions need to explain the information (not raw data). The software should translate the information is observed into usable, actionable information that allows firefighters to best apply their know-how and resources.


In the year since this workshop took place, we have worked hard to ensure that our platform does exactly this: provide analyzed, actionable data that gives firefighters the information they need to apply their resources and know-how effectively therein by protecting their communities. This, in turn, keeps their communities calm as teams are able to not only get the job done but also communicate effectively, informing their communities on what they know about the fire and what they plan to do in order to keep them safe.



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