October 2, 2015

Having too much fun with climate analytics

I like to solve hard problems. So much so that when I get a particularly good one it’s often difficult to do anything else. This personality quirk has been great for my engineering career but not so good for consistently blogging. Maybe you’ve noticed.

The good news is that I’m finally coming up for air and have lots to blog about.

Since February, I’ve been collaborating with scientists from Acadia National Park, the Earthwatch Institute, and the Schoodic Institute to study how climate change may be altering the life-cycles of and interactions between species at the park. This area of science is called Phenology but for fun we decided to name the project Whenology - a play on words based on the important of life-cycle timing.

To do this, we’re combining NOAA weather data, NASA MODIS vegetation index data, and field observation data collected the citizen science organizations HawkWatch, eBird, and USA National Phenology Network. This may be the first time these data have been combined in this way. It’s been very exciting to help explore this relatively new area of research.

The team just completed a pilot feasibility project focused on raptor migrations in the Acadia region. My part included writing code in R, Python, and Spark to transform, combine, analyze, and visualize these data. I integrated this work into an RShiny application to enable non-technical team members to also explore the data. I also used d3js to create dynamic visualizations for the project’s first website focused on education.

In (near?) future posts, I plan to share tips and tricks that I “discovered” while working on the pilot project. Work on the next project phase is about to begin. I hope to be less obsessed this time around but it’s going to be hard :-).

Be sure to checkout the project website!

Tags:  DataScience , SocialGood , R , Python , Projects , Spark , Visualization