Clean Technology Meets Data Science: News and Articles

  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 bot...

  Data science has been used extensively in building climate models, downscaling climate models to regions, monitoring and evaluating the accuracy of climate models through  paleoclimate data as well as developing methods to mitigate the effects of climate change and develop alternative markets. Today’s post will look at some of the more straightforward uses of data, machine learning and spatial statistics in monitoring carbon emissions as well as building alternative market systems. The first of course is   monitoring and measuring carbon emissions   and emissions of other gases that contribute to the changing climate. Our first example comes from Europe. Researchers in Europe    created a tool to map the 177 regions in 27 countries of the EU and the carbon footprint associated with them. They used a database (EXIOBASE 2.3 multiregional input-output database) with detailed information about the world economy in 2007 and built a model that looked at the dif...