Wildfire Prediction with Machine Learning

Posted on December 14, 2020

Neville Dubash headshot

Current wildfire prediction tools primarily use climate & meteorological data from Earth-based weather stations. This data can be sparse & costly to collect.

Coanda is using artificial intelligence & machine learning to access & draw useful information from a large ensemble of diverse satellite data in order to increase our capability to predict wildfire events autonomously. Apart from the direct benefits on public health & safety, this will translate into better use of resources & money, & reduction in losses due to wildfires.

The project successfully demonstrated a proof of concept model that improved wildfire occurrence prediction. Future work can include full automation of the calculations, extending coverage to all of Canada, & refinement through the use of supplementary data from a longer historical period.

Coanda is a leader in advanced mathematics & data science and offers a range of statistical & data analysis techniques to enhance the value of data for its clients.
You can download our overview document at the end of this article page: http://bit.ly/Coanda-CSA
Further information on the program can be found on the CSA website: https://bit.ly/3anhgeD

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