Finding Trees for the Forest

On a crispy Monday morning in mid September, the Spatial Analysis Lab (SAL) team set out with Albert Kim (SDS), Stephaine Choi (CEEDs), and Olivia Handoko (SDS ‘21) to measure and collect data for our very own, home grown “perfect plasticity approximation” method for the  Topics in Statistical and Data Sciences – Ecological Forecasting class (SDS 390). Albert explains, “this method is used for approximating a forest’s overstory using three variables that are measurable from the ground: location, species, and tree size (as measured by diameter at breast height)”.   But, how do you confirm the area of canopy overstory?  Enter the SAL with drones capacities to map areas at 1 – 2 cm per pixel and high-end GPS equipment with similar precision. 

Our initial plan imagined a trip to the MacLeish Field Station to collect data from previously censused tree plots and to compare those to a fresh, accurate aerial image captured by drone. We would also verify and refine tree location on the ground with GPS.  As we learned more about the methods, it became clear we would not be adding to existing and active research (underway at Microsoft).  Jon admitted the SAL often engages in work that we know will fail, muttering this would be “pre-determined failure”, but still very worthwhile to demonstrate the difficulty of doing science.  This led to the idea of documenting the process for students to view, and our virtual field trip was born. Albert embraced the idea and added Stephanie as videographer and Olivia as field assistant.  Consultations with Marney Pratt (BIO) advised Albert to dial down ambitious, let go of the “whole hog” approach, and conduct our “science is hard” experience on Smith campus — in what is known as “Area D” (see map).

All things considered, our “pre-determined failure” became quite productive (productive failure?).  As the crispiness of the morning burned off, we measured trees, flew drones in, around, and above the canopy, collected highly accurate coordinates on our ground control, generated a high resolution aerial image of “Area D”, and enjoyed a very agreeable collaboration.

In retrospect, the morning ticked many, if not all, of the boxes that define the SAL:

  • doing science — engaging in the process and practicing our methods
  • getting outside to observe, measure, and try to understand the landscape we are mapping
  • collaborating with new partners
  • teaching others and learning what we can do better or differently
  • practicing our tradecraft
  • and finally, enjoying lunch at Woodstar before getting too hangry

Map of “Area D” with processed imagery

Acknowledgements and talent:

  • Albert — chief scientist and highest paid actor
  • Stephanie — videographer, editor, keeper of the peace
  • Tracy — lead GPS wrangler, drone co-pilot
  • Olivia  — good natured SDS student, on-screen talent
  • Jon — pilot in command, should have worn boots

p.s. — Albert and Olivia learned the basics of flying a drone and no one was hurt or lost.  
p.s.s .— No robots were hurt or harmed during this event.