1.
Distinguishing N and P addition from
the air using imaging spectroscopy
Alex Young, Anna Schweiger, Melany Fisk, & Ruth Yanai
Twitter: @bearsofthemoss
Airborne imaging spectroscopy & field studies

2.
Oversold promises vs recent improvements
Low resolution
High resolution
Spatial resolution Spectral resolution

3.
NEON AOP
1. RGB photo
● 5 cm resolution
1. Hyperspectral data
● 450 wavelengths m-2
1. Lidar data
● 1-4 points m-2

4.
Laliberte, Schweiger, Legendre 2019 - Partitioning plant
spectral diversity into alpha and beta components

5.
NEON AOP
1. RGB photo
● 5 cm resolution
1. Hyperspectral data
● 450 wavelengths m-2
1. Lidar data
● 1-4 points m-2

6.
NEON AOP
1. RGB photo
● 5 cm resolution
1. Hyperspectral data
● 450 wavelengths m-2
1. Lidar data
● 1-4 points m-2

7.
Results
●N and P addition changed reflectence
where light is used for photosynthesis
●Basal area relationship
●N addition reduced reflectance
○ More chlorophyll, absorbed more light
● P addition increased reflectance
○ If you have thoughts, post in the chat!

8.
When we told the model the treatment class
(control, N, P, N+P) for 75% of the data (27 plots), on
average we had 83% accuracy for predicting the other
25% (9 plots)

9.
Field-measured resin-available N and P in soil align
with clustering of tree-top spectra
High
soil N
Low
soil N
Low
soil P
High
soil P

10.
●Trees are signals of belowground function
that can be easily observed remotely.
●Developing relationship of light reflectance
and nutrient availability may build on our
understanding of biogeochemistry.
●The NEON AOP could be brought to
Hubbard Brook.
Acknowledgements
• NEON online tutorials & data availability
• The MELNHE Project is funded by USDA NIFA (2019-67019-29464) and
NSF (DEB-1637685) . For more information, please visit
www.esf.edu/melnhe