Canopy Analytics
An Interactive Resource for Tree Discovery in the Portland Metro Area
Jackson Voelkel, Geospatial Research Analyst |
SUPR Lab | Portland State University
Portland Metro Area Trees
Important questions:
- How do we measure these trees?
- What trees are important (what is 'important', and to who)?
- How do we identify trees most in need of preservation?
... without climbing each one!
~180' up a 270' Douglas Fir
LiDAR
- Airborne Laser Scanning/Mapping
- ~12 points/m² on flat surface
- ~21cm point spacing
- ~63,600,000,000 (63.6 Billion) points in most recent flight
Incoming solar radiation (insolation) measured with and without Canopy
Toggle trees on/off [click and hold]
Exploring the Urban Forest
46ft
Steps:
- Identify every tree crown.
Toggle tree crowns on/off [click and hold]
Steps:
- Identify every tree crown.
- Describe each tree crown.
Machine Learning-derived evergreen/deciduous classification (~90% accuracy). Collaboration with Metro. Open Data.
Informing Statistical Models with Tree Data
Air Quality
Rao, M., George, L. A., Rosenstiel, T. N., Shandas, V., & Dinno, A. (2014). Assessing the relationship among urban trees, nitrogen dioxide, and respiratory health. Environmental Pollution, 194, 96-104.
The Canopy Analytics Tool
We know where all of the trees are!
What do we hope to accomplish?
- Increase public knowledge of the impact of trees.
- Educate policy makers to the connections trees have to the environment
- Nominate for Herritage Tree status that play major roles in:
- Reduction in the Urban Heat Island Effect
- Reduction in air pollutants
Future research
- More modeling!
- Tree species descriptions
- Explore the relationships between tree type and Air Quality / UHI
- New LiDAR: change detection
- permitted removals
- ... non-permitted removals
- Move beyond the Portland Metropolitan Area