Drought and wildfires always seem to go together! The recent drought in California was accompanied by powerful fires that burnt several million acres of forest, including in the iconic Yosemite National Park.
The question that people often ask whenever there’s news of yet another fire resulting in severe damage to the forests is always – isn’t there a way to figure out which areas of the forest are most vulnerable to the fires? And until recently, most rangers and naturalists were estimating that vulnerability based on their experience and years of working in the same forest ecosystem.
Scientists from the University of California, Davis studied aerial imagery from the forests in California between the years 2012-2015 to predict the areas where most of the trees were dying, either due to a fire or after a fire had struck. What they found was that the areas that were the worst affected with the highest tree mortality were areas that were both dry and dense. From a commonsense point of view, that conclusion seems eminently reasonable – after all, when there are a number of trees clustered together, they all compete for the same water. In a normal year, there’s enough water for everyone – but in drought, there’s too much competition for the water which dries out the soil and that leaves them vulnerable to fire.
Calculating the density of trees in an area is easy enough with aerial imagery – estimating the dryness of the soil is more complicated. Traditionally, soil moisture has been calculated by taking soil samples, weighing them before and after drying and calculating the difference between the two weights. Doing this over a large forest though is not only prohibitively expensive but all the areas of the forest may not be accessible to scientists taking samples.
Enter NASA’s SMAP (Soil Moisture Active Passive) satellite. This satellite was launched in 2015 and collects data on the soil moisture in the top 5 cm of soil every 2-3 days all over the globe. The data from this satellite is used to monitor soil dryness and thus predict the impacts of fires in forests. That’s useful not only from an environmental perspective but also from a business perspective for companies that generate income from forests and their products. And from a social perspective, it can also be used to help people all over the world better prepare for droughts and floods.
It’s a classic use of data science in clean technology – using the latest in satellites and remote sensing to enable better decisions for the environment, society and business.